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Hepatocellular Carcinoma: Leading Causes of Mortality Predicted
TOPLINE:
Alcohol-associated liver disease (ALD) will likely become the leading cause of HCC-related mortality by 2026, and metabolic dysfunction–associated steatotic liver disease (MASLD) is projected to become the second leading cause by 2032, a new analysis found.
METHODOLOGY:
- HCC accounts for 75%-85% of primary liver cancers and most liver cancer deaths. Researchers have observed an upward trend in the incidence of and mortality from HCC in the past 2 decades.
- This cross-sectional study analyzed 188,280 HCC-related deaths among adults aged 25 and older to determine trends in mortality rates and project age-standardized mortality rates through 2040. Data came from the National Vital Statistics System database from 2006 to 2022.
- Researchers stratified mortality data by etiology of liver disease (ALD, hepatitis B virus, hepatitis C virus, and MASLD), age groups (25-64 or 65 and older years), sex, and race/ethnicity.
- Demographic data showed that 77.4% of deaths occurred in men, 55.6% in individuals aged 65 years or older, and 62.3% in White individuals.
TAKEAWAY:
- Overall, the age-standardized mortality rate for HCC-related deaths increased from 3.65 per 100,000 persons in 2006 to 5.03 in 2022 and was projected to increase to 6.39 per 100,000 persons by 2040.
- Sex- and age-related disparities were substantial. Men had much higher rates of HCC-related mortality than women (8.15 vs 2.33 per 100,000 persons), with a projected rate among men of 9.78 per 100,000 persons by 2040. HCC-related mortality rates for people aged 65 years or older were 10 times higher than for those aged 25-64 years (18.37 vs 1.79 per 100,000 persons) in 2022 and was projected to reach 32.81 per 100,000 persons by 2040 in the older group.
- Although hepatitis C virus–related deaths were projected to decline from 0.69 to 0.03 per 100,000 persons by 2034, ALD- and MASLD-related deaths showed increasing trends, with both projected to become the two leading causes of HCC-related mortality in the next few years.
- Racial disparities were also evident. By 2040, the American Indian/Alaska Native population showed the highest increase in projected HCC-related mortality rates, which went from 5.46 per 100,000 persons in 2006 to a project increase to 14.71 per 100,000 persons.
IN PRACTICE:
“HCC mortality was projected to continue increasing in the US, primarily due to rising rates of deaths attributable to ALD and MASLD,” the authors wrote.
This “study highlights the importance of addressing these conditions to decrease the burden of liver disease and liver disease mortality in the future,” Emad Qayed, MD, MPH, Emory University School of Medicine, Atlanta, wrote in an accompanying editorial.
SOURCE:
The study was led by Sikai Qiu, MM, The Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China, and was published online in JAMA Network Open.
LIMITATIONS:
The National Vital Statistics System database used in this study captured only mortality data without access to detailed clinical records or individual medical histories. Researchers could not analyze socioeconomic factors or individual-level risk factors owing to data anonymization requirements. Additionally, the inclusion of the COVID-19 pandemic period could have influenced observed trends and reliability of future projections.
DISCLOSURES:
This study was supported by grants from the National Natural Science Foundation of China. Several authors reported receiving consulting fees, speaking fees, or research support from various sources.
This article was created using several editorial tools, including AI, as part of the process. Human editors reviewed this content before publication. A version of this article appeared on Medscape.com.
TOPLINE:
Alcohol-associated liver disease (ALD) will likely become the leading cause of HCC-related mortality by 2026, and metabolic dysfunction–associated steatotic liver disease (MASLD) is projected to become the second leading cause by 2032, a new analysis found.
METHODOLOGY:
- HCC accounts for 75%-85% of primary liver cancers and most liver cancer deaths. Researchers have observed an upward trend in the incidence of and mortality from HCC in the past 2 decades.
- This cross-sectional study analyzed 188,280 HCC-related deaths among adults aged 25 and older to determine trends in mortality rates and project age-standardized mortality rates through 2040. Data came from the National Vital Statistics System database from 2006 to 2022.
- Researchers stratified mortality data by etiology of liver disease (ALD, hepatitis B virus, hepatitis C virus, and MASLD), age groups (25-64 or 65 and older years), sex, and race/ethnicity.
- Demographic data showed that 77.4% of deaths occurred in men, 55.6% in individuals aged 65 years or older, and 62.3% in White individuals.
TAKEAWAY:
- Overall, the age-standardized mortality rate for HCC-related deaths increased from 3.65 per 100,000 persons in 2006 to 5.03 in 2022 and was projected to increase to 6.39 per 100,000 persons by 2040.
- Sex- and age-related disparities were substantial. Men had much higher rates of HCC-related mortality than women (8.15 vs 2.33 per 100,000 persons), with a projected rate among men of 9.78 per 100,000 persons by 2040. HCC-related mortality rates for people aged 65 years or older were 10 times higher than for those aged 25-64 years (18.37 vs 1.79 per 100,000 persons) in 2022 and was projected to reach 32.81 per 100,000 persons by 2040 in the older group.
- Although hepatitis C virus–related deaths were projected to decline from 0.69 to 0.03 per 100,000 persons by 2034, ALD- and MASLD-related deaths showed increasing trends, with both projected to become the two leading causes of HCC-related mortality in the next few years.
- Racial disparities were also evident. By 2040, the American Indian/Alaska Native population showed the highest increase in projected HCC-related mortality rates, which went from 5.46 per 100,000 persons in 2006 to a project increase to 14.71 per 100,000 persons.
IN PRACTICE:
“HCC mortality was projected to continue increasing in the US, primarily due to rising rates of deaths attributable to ALD and MASLD,” the authors wrote.
This “study highlights the importance of addressing these conditions to decrease the burden of liver disease and liver disease mortality in the future,” Emad Qayed, MD, MPH, Emory University School of Medicine, Atlanta, wrote in an accompanying editorial.
SOURCE:
The study was led by Sikai Qiu, MM, The Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China, and was published online in JAMA Network Open.
LIMITATIONS:
The National Vital Statistics System database used in this study captured only mortality data without access to detailed clinical records or individual medical histories. Researchers could not analyze socioeconomic factors or individual-level risk factors owing to data anonymization requirements. Additionally, the inclusion of the COVID-19 pandemic period could have influenced observed trends and reliability of future projections.
DISCLOSURES:
This study was supported by grants from the National Natural Science Foundation of China. Several authors reported receiving consulting fees, speaking fees, or research support from various sources.
This article was created using several editorial tools, including AI, as part of the process. Human editors reviewed this content before publication. A version of this article appeared on Medscape.com.
TOPLINE:
Alcohol-associated liver disease (ALD) will likely become the leading cause of HCC-related mortality by 2026, and metabolic dysfunction–associated steatotic liver disease (MASLD) is projected to become the second leading cause by 2032, a new analysis found.
METHODOLOGY:
- HCC accounts for 75%-85% of primary liver cancers and most liver cancer deaths. Researchers have observed an upward trend in the incidence of and mortality from HCC in the past 2 decades.
- This cross-sectional study analyzed 188,280 HCC-related deaths among adults aged 25 and older to determine trends in mortality rates and project age-standardized mortality rates through 2040. Data came from the National Vital Statistics System database from 2006 to 2022.
- Researchers stratified mortality data by etiology of liver disease (ALD, hepatitis B virus, hepatitis C virus, and MASLD), age groups (25-64 or 65 and older years), sex, and race/ethnicity.
- Demographic data showed that 77.4% of deaths occurred in men, 55.6% in individuals aged 65 years or older, and 62.3% in White individuals.
TAKEAWAY:
- Overall, the age-standardized mortality rate for HCC-related deaths increased from 3.65 per 100,000 persons in 2006 to 5.03 in 2022 and was projected to increase to 6.39 per 100,000 persons by 2040.
- Sex- and age-related disparities were substantial. Men had much higher rates of HCC-related mortality than women (8.15 vs 2.33 per 100,000 persons), with a projected rate among men of 9.78 per 100,000 persons by 2040. HCC-related mortality rates for people aged 65 years or older were 10 times higher than for those aged 25-64 years (18.37 vs 1.79 per 100,000 persons) in 2022 and was projected to reach 32.81 per 100,000 persons by 2040 in the older group.
- Although hepatitis C virus–related deaths were projected to decline from 0.69 to 0.03 per 100,000 persons by 2034, ALD- and MASLD-related deaths showed increasing trends, with both projected to become the two leading causes of HCC-related mortality in the next few years.
- Racial disparities were also evident. By 2040, the American Indian/Alaska Native population showed the highest increase in projected HCC-related mortality rates, which went from 5.46 per 100,000 persons in 2006 to a project increase to 14.71 per 100,000 persons.
IN PRACTICE:
“HCC mortality was projected to continue increasing in the US, primarily due to rising rates of deaths attributable to ALD and MASLD,” the authors wrote.
This “study highlights the importance of addressing these conditions to decrease the burden of liver disease and liver disease mortality in the future,” Emad Qayed, MD, MPH, Emory University School of Medicine, Atlanta, wrote in an accompanying editorial.
SOURCE:
The study was led by Sikai Qiu, MM, The Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China, and was published online in JAMA Network Open.
LIMITATIONS:
The National Vital Statistics System database used in this study captured only mortality data without access to detailed clinical records or individual medical histories. Researchers could not analyze socioeconomic factors or individual-level risk factors owing to data anonymization requirements. Additionally, the inclusion of the COVID-19 pandemic period could have influenced observed trends and reliability of future projections.
DISCLOSURES:
This study was supported by grants from the National Natural Science Foundation of China. Several authors reported receiving consulting fees, speaking fees, or research support from various sources.
This article was created using several editorial tools, including AI, as part of the process. Human editors reviewed this content before publication. A version of this article appeared on Medscape.com.
Physician Union Drives Skyrocketed in 2023 and 2024, Data Show
While fewer than 10% of US physicians are unionized, the number of official union drives among private-sector doctors have skyrocketed in the last 2 years, compared with 2 decades prior, according to a new study.
Researchers counted 21 union drives in 2023 and 12 in the first 5 months of 2024, compared with 0-6 drives each year between 2000 and 2022.
If the 2023 and 2024 drives succeed, unions will represent 3523 new physicians — nearly equal to the 3541 doctors who sought unionization between 2000 and 2022.
“We were able to document a significant uptick in union petitions and success in certification drives,” said corresponding author Hayden Rooke-Ley, JD, of the Center for Advancing Health Policy Through Research, Brown University School of Public Health, Providence, Rhode Island. “We were surprised to see such a marked shift in 2023.”
About 72,000 physicians, an estimated 8% of all US doctors, are covered by unions, including some in the public sector. Physicians who are self-employed, now comprising less than a fifth of all doctors, are not eligible to join labor unions.
The study authors launched their research to better understand trends in physician unionization in light of high-profile union drives, especially among residents. Rooke-Ley said: “We suspected that declining morale and increased corporate employment for physicians were leading them to consider unionization.”
The researchers gathered data from the National Labor Relations Board about union drives by potential bargaining units that included physicians. From 2000 to 2022, 44 union petitions were filed. The number jumped to 33 from 2023-2024.
“Tip of the Iceberg”
“This is the tip of the iceberg,” said ethicist Joseph F. Kras, MD, DDS, MA, an associate professor of anesthesiology at Washington University in St. Louis, Missouri, and corresponding author of a recent Anesthesia & Analgesia report about physician unionization.
“We are independent by nature,” Kras said. “But when you put us in an employed environment and start treating us as widgets, then we will act like employees of Amazon, Starbucks, and other companies and join together to push back against the increasing emphasis on profit over all at the expense of our independent judgment on what’s best for the patient.”
Of the 66 unionization efforts between 2000 and 2024 that were decided, 62% were certified, according to the JAMA study. The drives targeted hospitals (49%), community health centers (38%), and nonhospital corporate owners (13%).
The researchers only analyzed private-sector unionization and did not include physicians who are unionized at public institutions.
What’s Behind Union Drives?
Alyssa Burgart, MD, MA, an ethicist and clinical associate professor of anesthesiology and pediatrics at Stanford University in California, told this news organization that physician unionization “is a big topic with a lot of really strong opinions.”
Many doctors wrongly assume they can’t unionize because they’re physicians, said Burgart, a coauthor of the Anesthesia & Analgesia report.
Supporters of unionization believe it’s a strategy to be “recognized not as simply as a single physician with a concern,” she said. “When you’re among clinicians who can speak as a more unified group, organizations are more likely to take that seriously.”
A union may also be able to hold employers to account in areas such as the gender wage gap, sexual harassment, and bias in hiring and firing, Burgart said. And union supporters believe they’ll make more money if they collectively bargain.
Other factors driving interest in unions include “increasing physician burnout, increasing physician exhaustion, and immense frustration with the ways that private equity is influencing how physicians need to work in order to practice,” she said.
Earlier in 2024, physicians in Delaware’s ChristianaCare health system voted 288-130 to be represented by Doctors Council/Service Employees International, according to the union.
“We have still not been able to staff up enough to where us physicians can get back to just focusing on taking care of patients,” a unionization leader told WHYY.
The JAMA study examined news reports regarding most of the 2023-2024 union drives and found that supporters claimed they were motivated by working conditions (85%), lack of voice in management (81%), patient care concerns (54%), and pay (4%).
Critics Worry They’ll Lose Pay Because of Unions
Skeptics of unionization worry about whether “I’m going to be required to stand by some union stance that is actually out of alignment with my values as a physician,” Burgart said. And, she said, critics such as highly paid surgeons fear that adjustments to salaries because of union contracts could cause them to lose income.
In regard to compensation, a 2024 study surveyed unionized residents — along with faculty and staff — at general surgery programs and found evidence that unionization didn’t improve resident well-being or benefits, although it “provided a mechanism for resident voice and agency.”
“It is critical to study the outcomes of those who unionized to ensure that the reasons for unionizing were realized over time,” said that study’s coauthor Karl Bilimoria, MD, MS, chair of surgery at Indiana University School of Medicine, Indianapolis. “The unintended consequences of unionization must be examined along with the potential improvements.”
Rooke-Ley discloses consulting fees from the American Economic Liberties Project, National Academy of State Health Policy, and 32BJ Funds. Kras and Burgart disclose previous union membership. Bilimoria has no disclosures.
A version of this article first appeared on Medscape.com.
While fewer than 10% of US physicians are unionized, the number of official union drives among private-sector doctors have skyrocketed in the last 2 years, compared with 2 decades prior, according to a new study.
Researchers counted 21 union drives in 2023 and 12 in the first 5 months of 2024, compared with 0-6 drives each year between 2000 and 2022.
If the 2023 and 2024 drives succeed, unions will represent 3523 new physicians — nearly equal to the 3541 doctors who sought unionization between 2000 and 2022.
“We were able to document a significant uptick in union petitions and success in certification drives,” said corresponding author Hayden Rooke-Ley, JD, of the Center for Advancing Health Policy Through Research, Brown University School of Public Health, Providence, Rhode Island. “We were surprised to see such a marked shift in 2023.”
About 72,000 physicians, an estimated 8% of all US doctors, are covered by unions, including some in the public sector. Physicians who are self-employed, now comprising less than a fifth of all doctors, are not eligible to join labor unions.
The study authors launched their research to better understand trends in physician unionization in light of high-profile union drives, especially among residents. Rooke-Ley said: “We suspected that declining morale and increased corporate employment for physicians were leading them to consider unionization.”
The researchers gathered data from the National Labor Relations Board about union drives by potential bargaining units that included physicians. From 2000 to 2022, 44 union petitions were filed. The number jumped to 33 from 2023-2024.
“Tip of the Iceberg”
“This is the tip of the iceberg,” said ethicist Joseph F. Kras, MD, DDS, MA, an associate professor of anesthesiology at Washington University in St. Louis, Missouri, and corresponding author of a recent Anesthesia & Analgesia report about physician unionization.
“We are independent by nature,” Kras said. “But when you put us in an employed environment and start treating us as widgets, then we will act like employees of Amazon, Starbucks, and other companies and join together to push back against the increasing emphasis on profit over all at the expense of our independent judgment on what’s best for the patient.”
Of the 66 unionization efforts between 2000 and 2024 that were decided, 62% were certified, according to the JAMA study. The drives targeted hospitals (49%), community health centers (38%), and nonhospital corporate owners (13%).
The researchers only analyzed private-sector unionization and did not include physicians who are unionized at public institutions.
What’s Behind Union Drives?
Alyssa Burgart, MD, MA, an ethicist and clinical associate professor of anesthesiology and pediatrics at Stanford University in California, told this news organization that physician unionization “is a big topic with a lot of really strong opinions.”
Many doctors wrongly assume they can’t unionize because they’re physicians, said Burgart, a coauthor of the Anesthesia & Analgesia report.
Supporters of unionization believe it’s a strategy to be “recognized not as simply as a single physician with a concern,” she said. “When you’re among clinicians who can speak as a more unified group, organizations are more likely to take that seriously.”
A union may also be able to hold employers to account in areas such as the gender wage gap, sexual harassment, and bias in hiring and firing, Burgart said. And union supporters believe they’ll make more money if they collectively bargain.
Other factors driving interest in unions include “increasing physician burnout, increasing physician exhaustion, and immense frustration with the ways that private equity is influencing how physicians need to work in order to practice,” she said.
Earlier in 2024, physicians in Delaware’s ChristianaCare health system voted 288-130 to be represented by Doctors Council/Service Employees International, according to the union.
“We have still not been able to staff up enough to where us physicians can get back to just focusing on taking care of patients,” a unionization leader told WHYY.
The JAMA study examined news reports regarding most of the 2023-2024 union drives and found that supporters claimed they were motivated by working conditions (85%), lack of voice in management (81%), patient care concerns (54%), and pay (4%).
Critics Worry They’ll Lose Pay Because of Unions
Skeptics of unionization worry about whether “I’m going to be required to stand by some union stance that is actually out of alignment with my values as a physician,” Burgart said. And, she said, critics such as highly paid surgeons fear that adjustments to salaries because of union contracts could cause them to lose income.
In regard to compensation, a 2024 study surveyed unionized residents — along with faculty and staff — at general surgery programs and found evidence that unionization didn’t improve resident well-being or benefits, although it “provided a mechanism for resident voice and agency.”
“It is critical to study the outcomes of those who unionized to ensure that the reasons for unionizing were realized over time,” said that study’s coauthor Karl Bilimoria, MD, MS, chair of surgery at Indiana University School of Medicine, Indianapolis. “The unintended consequences of unionization must be examined along with the potential improvements.”
Rooke-Ley discloses consulting fees from the American Economic Liberties Project, National Academy of State Health Policy, and 32BJ Funds. Kras and Burgart disclose previous union membership. Bilimoria has no disclosures.
A version of this article first appeared on Medscape.com.
While fewer than 10% of US physicians are unionized, the number of official union drives among private-sector doctors have skyrocketed in the last 2 years, compared with 2 decades prior, according to a new study.
Researchers counted 21 union drives in 2023 and 12 in the first 5 months of 2024, compared with 0-6 drives each year between 2000 and 2022.
If the 2023 and 2024 drives succeed, unions will represent 3523 new physicians — nearly equal to the 3541 doctors who sought unionization between 2000 and 2022.
“We were able to document a significant uptick in union petitions and success in certification drives,” said corresponding author Hayden Rooke-Ley, JD, of the Center for Advancing Health Policy Through Research, Brown University School of Public Health, Providence, Rhode Island. “We were surprised to see such a marked shift in 2023.”
About 72,000 physicians, an estimated 8% of all US doctors, are covered by unions, including some in the public sector. Physicians who are self-employed, now comprising less than a fifth of all doctors, are not eligible to join labor unions.
The study authors launched their research to better understand trends in physician unionization in light of high-profile union drives, especially among residents. Rooke-Ley said: “We suspected that declining morale and increased corporate employment for physicians were leading them to consider unionization.”
The researchers gathered data from the National Labor Relations Board about union drives by potential bargaining units that included physicians. From 2000 to 2022, 44 union petitions were filed. The number jumped to 33 from 2023-2024.
“Tip of the Iceberg”
“This is the tip of the iceberg,” said ethicist Joseph F. Kras, MD, DDS, MA, an associate professor of anesthesiology at Washington University in St. Louis, Missouri, and corresponding author of a recent Anesthesia & Analgesia report about physician unionization.
“We are independent by nature,” Kras said. “But when you put us in an employed environment and start treating us as widgets, then we will act like employees of Amazon, Starbucks, and other companies and join together to push back against the increasing emphasis on profit over all at the expense of our independent judgment on what’s best for the patient.”
Of the 66 unionization efforts between 2000 and 2024 that were decided, 62% were certified, according to the JAMA study. The drives targeted hospitals (49%), community health centers (38%), and nonhospital corporate owners (13%).
The researchers only analyzed private-sector unionization and did not include physicians who are unionized at public institutions.
What’s Behind Union Drives?
Alyssa Burgart, MD, MA, an ethicist and clinical associate professor of anesthesiology and pediatrics at Stanford University in California, told this news organization that physician unionization “is a big topic with a lot of really strong opinions.”
Many doctors wrongly assume they can’t unionize because they’re physicians, said Burgart, a coauthor of the Anesthesia & Analgesia report.
Supporters of unionization believe it’s a strategy to be “recognized not as simply as a single physician with a concern,” she said. “When you’re among clinicians who can speak as a more unified group, organizations are more likely to take that seriously.”
A union may also be able to hold employers to account in areas such as the gender wage gap, sexual harassment, and bias in hiring and firing, Burgart said. And union supporters believe they’ll make more money if they collectively bargain.
Other factors driving interest in unions include “increasing physician burnout, increasing physician exhaustion, and immense frustration with the ways that private equity is influencing how physicians need to work in order to practice,” she said.
Earlier in 2024, physicians in Delaware’s ChristianaCare health system voted 288-130 to be represented by Doctors Council/Service Employees International, according to the union.
“We have still not been able to staff up enough to where us physicians can get back to just focusing on taking care of patients,” a unionization leader told WHYY.
The JAMA study examined news reports regarding most of the 2023-2024 union drives and found that supporters claimed they were motivated by working conditions (85%), lack of voice in management (81%), patient care concerns (54%), and pay (4%).
Critics Worry They’ll Lose Pay Because of Unions
Skeptics of unionization worry about whether “I’m going to be required to stand by some union stance that is actually out of alignment with my values as a physician,” Burgart said. And, she said, critics such as highly paid surgeons fear that adjustments to salaries because of union contracts could cause them to lose income.
In regard to compensation, a 2024 study surveyed unionized residents — along with faculty and staff — at general surgery programs and found evidence that unionization didn’t improve resident well-being or benefits, although it “provided a mechanism for resident voice and agency.”
“It is critical to study the outcomes of those who unionized to ensure that the reasons for unionizing were realized over time,” said that study’s coauthor Karl Bilimoria, MD, MS, chair of surgery at Indiana University School of Medicine, Indianapolis. “The unintended consequences of unionization must be examined along with the potential improvements.”
Rooke-Ley discloses consulting fees from the American Economic Liberties Project, National Academy of State Health Policy, and 32BJ Funds. Kras and Burgart disclose previous union membership. Bilimoria has no disclosures.
A version of this article first appeared on Medscape.com.
FROM JAMA
‘We Don’t Hire Female Doctors With Children’
Hatice became pregnant while working as a medical resident, and her career took a noticeable hit. Her training was downgraded, and her job applications went unanswered. This news organization spoke with her about her experiences and the disadvantages faced by young female doctors with children.
Hatice, can you tell us about your career path?
I initially started my clinical year at a hospital in Cologne, Germany. Then, 8 months in, I got pregnant with my first child during the first COVID-19 wave. After my maternity leave, I returned to the clinic, and that’s when the problems began.
Where did the issues arise?
Suddenly, I wasn’t allowed into the operating rooms (ORs) and was instead sent to the outpatient clinic. I had to fight for every OR slot until, eventually, I said, “This can’t go on. I want to stay in the hospital and gain my surgical experience, but not if I have to keep struggling for it.”
So, initially, it was about wanting to improve the quality of your ongoing training, as they gave you no path forward for further development? And you attribute this to your maternity leave.
It wasn’t just my perception — I was told as much directly. I returned from maternity leave and was told to work in outpatients and cover shifts. I went to my supervisor and explained that I was unhappy with this. We have an OR log, and I wanted to complete my required cases. He replied, “Well, that’s your fault for getting pregnant right away.”
In the Cologne/Düsseldorf/Bonn area, there is no shortage of doctors in training. This means that as soon as I leave, there will be new recruits. So my boss actually said to me at the time, “If you’re gone, you’re gone, then the next candidate will come along.”
Did you return to work part-time after your maternity leave, or full-time?
I returned full-time and took on all my usual duties. Fortunately, my husband takes on a lot at home. He spent a significant time on parental leave and has often been the one to care for our child when they’re sick. So, if you didn’t know, you wouldn’t necessarily realize at work that I have a child.
What happened next?
I discussed the situation with the senior physician responsible for the OR assignments, but she told me not to worry, as I would eventually get the required signature at the end of my training. But that wasn’t my issue — I wanted the professional training. Feeling stuck, I decided to look for other positions.
Did you apply elsewhere to improve your situation?
Yes, but most of my applications went unanswered, which I didn’t understand. When I followed up, I actually received verbal replies from three hospitals, stating, “We don’t hire women with children.”
You’ve shared your experiences publicly on social media. How has the response been? Have other female doctors had similar experiences?
I think the problem of discrimination against women with children is still taboo. You’d think, with the shortage of doctors, that jobs would be available. But I’ve heard from former classmates who now have children that they face similar career obstacles, especially in fields such as internal medicine, where fulfilling rotations is challenging owing to scheduling bias.
This raises the question of adapting working conditions. In your case, it seems that a change in employer attitudes is also needed. What’s your perspective?
It varies depending on the region. I’ve applied across Germany and found that areas outside major cities such as Cologne, Düsseldorf, and Frankfurt tend to be better. In urban centers with a large applicant pool, the atmosphere is different. In smaller areas, finding a job is easier, especially if you’re fluent in German and experienced.
Do you believe that changing the mindset of employers regarding female staff with children could happen with a generational shift?
Honestly, I doubt it. It’s not just an issue at management level — it’s also present among residents. When someone takes leave, colleagues have to cover, which leads to resentment. Yet many female residents will eventually have children themselves. And it’s often overlooked that many men now share childcare responsibilities or take parental leave. Improving staffing levels would help alleviate these pressures.
Returning to structural issues, how is your situation now — can you continue your training?
I’ve since changed positions and am very happy. I didn’t expect such a positive reception with a child in tow.
Lastly, what changes do you think are needed? Is it enough to speak out about such experiences, or are further solutions necessary?
It’s good that topics such as burnout are openly discussed now. With children, there’s a risk for burnout, as you strive to meet all expectations to avoid career setbacks. But there also needs to be an acceptance that women who are hired may become pregnant and may have more than one child. I’m hopeful that over time, this will become normalized, especially as medicine becomes a more female-dominated field.
Is there anything else you’d like to share?
I wish there were more solidarity among women. It’s disheartening to see competition and infighting. More mutual support among women would make a huge difference.
Thank you, Hatice, and best of luck in your career.
Hatice, who prefers not to disclose her last name for privacy, is a fourth-year ENT specialist in training and shares her journey as a young doctor on Instagram under the name dein.hno.arzt.
This article was translated from Coliquio using several editorial tools, including AI, as part of the process. Human editors reviewed this content before publication.
A version of this article first appeared on Medscape.com.
Hatice became pregnant while working as a medical resident, and her career took a noticeable hit. Her training was downgraded, and her job applications went unanswered. This news organization spoke with her about her experiences and the disadvantages faced by young female doctors with children.
Hatice, can you tell us about your career path?
I initially started my clinical year at a hospital in Cologne, Germany. Then, 8 months in, I got pregnant with my first child during the first COVID-19 wave. After my maternity leave, I returned to the clinic, and that’s when the problems began.
Where did the issues arise?
Suddenly, I wasn’t allowed into the operating rooms (ORs) and was instead sent to the outpatient clinic. I had to fight for every OR slot until, eventually, I said, “This can’t go on. I want to stay in the hospital and gain my surgical experience, but not if I have to keep struggling for it.”
So, initially, it was about wanting to improve the quality of your ongoing training, as they gave you no path forward for further development? And you attribute this to your maternity leave.
It wasn’t just my perception — I was told as much directly. I returned from maternity leave and was told to work in outpatients and cover shifts. I went to my supervisor and explained that I was unhappy with this. We have an OR log, and I wanted to complete my required cases. He replied, “Well, that’s your fault for getting pregnant right away.”
In the Cologne/Düsseldorf/Bonn area, there is no shortage of doctors in training. This means that as soon as I leave, there will be new recruits. So my boss actually said to me at the time, “If you’re gone, you’re gone, then the next candidate will come along.”
Did you return to work part-time after your maternity leave, or full-time?
I returned full-time and took on all my usual duties. Fortunately, my husband takes on a lot at home. He spent a significant time on parental leave and has often been the one to care for our child when they’re sick. So, if you didn’t know, you wouldn’t necessarily realize at work that I have a child.
What happened next?
I discussed the situation with the senior physician responsible for the OR assignments, but she told me not to worry, as I would eventually get the required signature at the end of my training. But that wasn’t my issue — I wanted the professional training. Feeling stuck, I decided to look for other positions.
Did you apply elsewhere to improve your situation?
Yes, but most of my applications went unanswered, which I didn’t understand. When I followed up, I actually received verbal replies from three hospitals, stating, “We don’t hire women with children.”
You’ve shared your experiences publicly on social media. How has the response been? Have other female doctors had similar experiences?
I think the problem of discrimination against women with children is still taboo. You’d think, with the shortage of doctors, that jobs would be available. But I’ve heard from former classmates who now have children that they face similar career obstacles, especially in fields such as internal medicine, where fulfilling rotations is challenging owing to scheduling bias.
This raises the question of adapting working conditions. In your case, it seems that a change in employer attitudes is also needed. What’s your perspective?
It varies depending on the region. I’ve applied across Germany and found that areas outside major cities such as Cologne, Düsseldorf, and Frankfurt tend to be better. In urban centers with a large applicant pool, the atmosphere is different. In smaller areas, finding a job is easier, especially if you’re fluent in German and experienced.
Do you believe that changing the mindset of employers regarding female staff with children could happen with a generational shift?
Honestly, I doubt it. It’s not just an issue at management level — it’s also present among residents. When someone takes leave, colleagues have to cover, which leads to resentment. Yet many female residents will eventually have children themselves. And it’s often overlooked that many men now share childcare responsibilities or take parental leave. Improving staffing levels would help alleviate these pressures.
Returning to structural issues, how is your situation now — can you continue your training?
I’ve since changed positions and am very happy. I didn’t expect such a positive reception with a child in tow.
Lastly, what changes do you think are needed? Is it enough to speak out about such experiences, or are further solutions necessary?
It’s good that topics such as burnout are openly discussed now. With children, there’s a risk for burnout, as you strive to meet all expectations to avoid career setbacks. But there also needs to be an acceptance that women who are hired may become pregnant and may have more than one child. I’m hopeful that over time, this will become normalized, especially as medicine becomes a more female-dominated field.
Is there anything else you’d like to share?
I wish there were more solidarity among women. It’s disheartening to see competition and infighting. More mutual support among women would make a huge difference.
Thank you, Hatice, and best of luck in your career.
Hatice, who prefers not to disclose her last name for privacy, is a fourth-year ENT specialist in training and shares her journey as a young doctor on Instagram under the name dein.hno.arzt.
This article was translated from Coliquio using several editorial tools, including AI, as part of the process. Human editors reviewed this content before publication.
A version of this article first appeared on Medscape.com.
Hatice became pregnant while working as a medical resident, and her career took a noticeable hit. Her training was downgraded, and her job applications went unanswered. This news organization spoke with her about her experiences and the disadvantages faced by young female doctors with children.
Hatice, can you tell us about your career path?
I initially started my clinical year at a hospital in Cologne, Germany. Then, 8 months in, I got pregnant with my first child during the first COVID-19 wave. After my maternity leave, I returned to the clinic, and that’s when the problems began.
Where did the issues arise?
Suddenly, I wasn’t allowed into the operating rooms (ORs) and was instead sent to the outpatient clinic. I had to fight for every OR slot until, eventually, I said, “This can’t go on. I want to stay in the hospital and gain my surgical experience, but not if I have to keep struggling for it.”
So, initially, it was about wanting to improve the quality of your ongoing training, as they gave you no path forward for further development? And you attribute this to your maternity leave.
It wasn’t just my perception — I was told as much directly. I returned from maternity leave and was told to work in outpatients and cover shifts. I went to my supervisor and explained that I was unhappy with this. We have an OR log, and I wanted to complete my required cases. He replied, “Well, that’s your fault for getting pregnant right away.”
In the Cologne/Düsseldorf/Bonn area, there is no shortage of doctors in training. This means that as soon as I leave, there will be new recruits. So my boss actually said to me at the time, “If you’re gone, you’re gone, then the next candidate will come along.”
Did you return to work part-time after your maternity leave, or full-time?
I returned full-time and took on all my usual duties. Fortunately, my husband takes on a lot at home. He spent a significant time on parental leave and has often been the one to care for our child when they’re sick. So, if you didn’t know, you wouldn’t necessarily realize at work that I have a child.
What happened next?
I discussed the situation with the senior physician responsible for the OR assignments, but she told me not to worry, as I would eventually get the required signature at the end of my training. But that wasn’t my issue — I wanted the professional training. Feeling stuck, I decided to look for other positions.
Did you apply elsewhere to improve your situation?
Yes, but most of my applications went unanswered, which I didn’t understand. When I followed up, I actually received verbal replies from three hospitals, stating, “We don’t hire women with children.”
You’ve shared your experiences publicly on social media. How has the response been? Have other female doctors had similar experiences?
I think the problem of discrimination against women with children is still taboo. You’d think, with the shortage of doctors, that jobs would be available. But I’ve heard from former classmates who now have children that they face similar career obstacles, especially in fields such as internal medicine, where fulfilling rotations is challenging owing to scheduling bias.
This raises the question of adapting working conditions. In your case, it seems that a change in employer attitudes is also needed. What’s your perspective?
It varies depending on the region. I’ve applied across Germany and found that areas outside major cities such as Cologne, Düsseldorf, and Frankfurt tend to be better. In urban centers with a large applicant pool, the atmosphere is different. In smaller areas, finding a job is easier, especially if you’re fluent in German and experienced.
Do you believe that changing the mindset of employers regarding female staff with children could happen with a generational shift?
Honestly, I doubt it. It’s not just an issue at management level — it’s also present among residents. When someone takes leave, colleagues have to cover, which leads to resentment. Yet many female residents will eventually have children themselves. And it’s often overlooked that many men now share childcare responsibilities or take parental leave. Improving staffing levels would help alleviate these pressures.
Returning to structural issues, how is your situation now — can you continue your training?
I’ve since changed positions and am very happy. I didn’t expect such a positive reception with a child in tow.
Lastly, what changes do you think are needed? Is it enough to speak out about such experiences, or are further solutions necessary?
It’s good that topics such as burnout are openly discussed now. With children, there’s a risk for burnout, as you strive to meet all expectations to avoid career setbacks. But there also needs to be an acceptance that women who are hired may become pregnant and may have more than one child. I’m hopeful that over time, this will become normalized, especially as medicine becomes a more female-dominated field.
Is there anything else you’d like to share?
I wish there were more solidarity among women. It’s disheartening to see competition and infighting. More mutual support among women would make a huge difference.
Thank you, Hatice, and best of luck in your career.
Hatice, who prefers not to disclose her last name for privacy, is a fourth-year ENT specialist in training and shares her journey as a young doctor on Instagram under the name dein.hno.arzt.
This article was translated from Coliquio using several editorial tools, including AI, as part of the process. Human editors reviewed this content before publication.
A version of this article first appeared on Medscape.com.
Skin Cancer Risk Elevated Among Blood, Marrow Transplant Survivors
TOPLINE:
with a cumulative incidence of 27.4% over 30 years, according to the results of a cohort study.
METHODOLOGY:
- The retrospective cohort study included 3880 BMT survivors (median age, 44 years; 55.8% men; 4.9% Black, 12.1 Hispanic, and 74.7% non-Hispanic White individuals) who underwent transplant between 1974 to 2014.
- Participants completed the BMT Survivor Study survey and were followed up for a median of 9.5 years.
- The primary outcomes were the development of subsequent cutaneous malignant neoplasms (BCC, SCC, or melanoma).
TAKEAWAY:
- The 30-year cumulative incidence of any cutaneous malignant neoplasm was 27.4% — 18% for BCC, 9.8% for SCC, and 3.7% for melanoma.
- A higher risk for skin cancer was reported for patients aged 50 years or more (subdistribution hazard ratio [SHR], 2.23; 95% CI, 1.83-2.71), and men (SHR, 1.40; 95% CI, 1.18-1.65).
- Allogeneic BMT with chronic graft-vs-host disease (cGVHD) increased the risk for skin cancer (SHR, 1.84; 95% CI, 1.37-2.47), compared with autologous BMT, while post-BMT immunosuppression increased risk for all types (overall SHR, 1.53; 95% CI, 1.26-1.86).
- The risk for any skin cancer was significantly lower in Black individuals (SHR, 0.14; 95% CI, 0.05-0.37), Hispanic individuals (SHR, 0.29; 95%CI, 0.20-0.62), and patients of other races or who were multiracial (SHR, 0.22; 95% CI, 0.13-0.37) than in non-Hispanic White patients.
IN PRACTICE:
In the study, “risk factors for post-BMT cutaneous malignant neoplasms included pretransplant treatment with a monoclonal antibody, cGVHD, and posttransplant immunosuppression,” the authors wrote, adding that the findings “could inform targeted surveillance of BMT survivors.” Most BMT survivors, “do not undergo routine dermatologic surveillance, highlighting the need to understand risk factors and incorporate risk-informed dermatologic surveillance into survivorship care plans.”
SOURCE:
The study was led by Kristy K. Broman, MD, MPH, University of Alabama at Birmingham, and was published online on December 18 in JAMA Dermatology.
LIMITATIONS:
Limitations included self-reported data and possible underreporting of melanoma cases in the SEER database. Additionally, the study did not capture other risk factors for cutaneous malignant neoplasms such as skin phototype, ultraviolet light exposure, or family history. The duration of posttransplant immunosuppression was not collected, and surveys were administered at variable intervals, though all were completed more than 2 years post BMT.
DISCLOSURES:
The study was supported by the National Cancer Institute (NCI) and the Leukemia and Lymphoma Society. Broman received grants from NCI, the National Center for Advancing Translational Sciences, the American Society of Clinical Oncology, and the American College of Surgeons. Another author reported receiving grants outside this work.
This article was created using several editorial tools, including artificial intelligence, as part of the process. Human editors reviewed this content before publication. A version of this article first appeared on Medscape.com.
TOPLINE:
with a cumulative incidence of 27.4% over 30 years, according to the results of a cohort study.
METHODOLOGY:
- The retrospective cohort study included 3880 BMT survivors (median age, 44 years; 55.8% men; 4.9% Black, 12.1 Hispanic, and 74.7% non-Hispanic White individuals) who underwent transplant between 1974 to 2014.
- Participants completed the BMT Survivor Study survey and were followed up for a median of 9.5 years.
- The primary outcomes were the development of subsequent cutaneous malignant neoplasms (BCC, SCC, or melanoma).
TAKEAWAY:
- The 30-year cumulative incidence of any cutaneous malignant neoplasm was 27.4% — 18% for BCC, 9.8% for SCC, and 3.7% for melanoma.
- A higher risk for skin cancer was reported for patients aged 50 years or more (subdistribution hazard ratio [SHR], 2.23; 95% CI, 1.83-2.71), and men (SHR, 1.40; 95% CI, 1.18-1.65).
- Allogeneic BMT with chronic graft-vs-host disease (cGVHD) increased the risk for skin cancer (SHR, 1.84; 95% CI, 1.37-2.47), compared with autologous BMT, while post-BMT immunosuppression increased risk for all types (overall SHR, 1.53; 95% CI, 1.26-1.86).
- The risk for any skin cancer was significantly lower in Black individuals (SHR, 0.14; 95% CI, 0.05-0.37), Hispanic individuals (SHR, 0.29; 95%CI, 0.20-0.62), and patients of other races or who were multiracial (SHR, 0.22; 95% CI, 0.13-0.37) than in non-Hispanic White patients.
IN PRACTICE:
In the study, “risk factors for post-BMT cutaneous malignant neoplasms included pretransplant treatment with a monoclonal antibody, cGVHD, and posttransplant immunosuppression,” the authors wrote, adding that the findings “could inform targeted surveillance of BMT survivors.” Most BMT survivors, “do not undergo routine dermatologic surveillance, highlighting the need to understand risk factors and incorporate risk-informed dermatologic surveillance into survivorship care plans.”
SOURCE:
The study was led by Kristy K. Broman, MD, MPH, University of Alabama at Birmingham, and was published online on December 18 in JAMA Dermatology.
LIMITATIONS:
Limitations included self-reported data and possible underreporting of melanoma cases in the SEER database. Additionally, the study did not capture other risk factors for cutaneous malignant neoplasms such as skin phototype, ultraviolet light exposure, or family history. The duration of posttransplant immunosuppression was not collected, and surveys were administered at variable intervals, though all were completed more than 2 years post BMT.
DISCLOSURES:
The study was supported by the National Cancer Institute (NCI) and the Leukemia and Lymphoma Society. Broman received grants from NCI, the National Center for Advancing Translational Sciences, the American Society of Clinical Oncology, and the American College of Surgeons. Another author reported receiving grants outside this work.
This article was created using several editorial tools, including artificial intelligence, as part of the process. Human editors reviewed this content before publication. A version of this article first appeared on Medscape.com.
TOPLINE:
with a cumulative incidence of 27.4% over 30 years, according to the results of a cohort study.
METHODOLOGY:
- The retrospective cohort study included 3880 BMT survivors (median age, 44 years; 55.8% men; 4.9% Black, 12.1 Hispanic, and 74.7% non-Hispanic White individuals) who underwent transplant between 1974 to 2014.
- Participants completed the BMT Survivor Study survey and were followed up for a median of 9.5 years.
- The primary outcomes were the development of subsequent cutaneous malignant neoplasms (BCC, SCC, or melanoma).
TAKEAWAY:
- The 30-year cumulative incidence of any cutaneous malignant neoplasm was 27.4% — 18% for BCC, 9.8% for SCC, and 3.7% for melanoma.
- A higher risk for skin cancer was reported for patients aged 50 years or more (subdistribution hazard ratio [SHR], 2.23; 95% CI, 1.83-2.71), and men (SHR, 1.40; 95% CI, 1.18-1.65).
- Allogeneic BMT with chronic graft-vs-host disease (cGVHD) increased the risk for skin cancer (SHR, 1.84; 95% CI, 1.37-2.47), compared with autologous BMT, while post-BMT immunosuppression increased risk for all types (overall SHR, 1.53; 95% CI, 1.26-1.86).
- The risk for any skin cancer was significantly lower in Black individuals (SHR, 0.14; 95% CI, 0.05-0.37), Hispanic individuals (SHR, 0.29; 95%CI, 0.20-0.62), and patients of other races or who were multiracial (SHR, 0.22; 95% CI, 0.13-0.37) than in non-Hispanic White patients.
IN PRACTICE:
In the study, “risk factors for post-BMT cutaneous malignant neoplasms included pretransplant treatment with a monoclonal antibody, cGVHD, and posttransplant immunosuppression,” the authors wrote, adding that the findings “could inform targeted surveillance of BMT survivors.” Most BMT survivors, “do not undergo routine dermatologic surveillance, highlighting the need to understand risk factors and incorporate risk-informed dermatologic surveillance into survivorship care plans.”
SOURCE:
The study was led by Kristy K. Broman, MD, MPH, University of Alabama at Birmingham, and was published online on December 18 in JAMA Dermatology.
LIMITATIONS:
Limitations included self-reported data and possible underreporting of melanoma cases in the SEER database. Additionally, the study did not capture other risk factors for cutaneous malignant neoplasms such as skin phototype, ultraviolet light exposure, or family history. The duration of posttransplant immunosuppression was not collected, and surveys were administered at variable intervals, though all were completed more than 2 years post BMT.
DISCLOSURES:
The study was supported by the National Cancer Institute (NCI) and the Leukemia and Lymphoma Society. Broman received grants from NCI, the National Center for Advancing Translational Sciences, the American Society of Clinical Oncology, and the American College of Surgeons. Another author reported receiving grants outside this work.
This article was created using several editorial tools, including artificial intelligence, as part of the process. Human editors reviewed this content before publication. A version of this article first appeared on Medscape.com.
The Protein Problem: The Unsolved Mystery of AI Drug Dev
The question has been lingering for years in medical science circles. Since 2020, when the artificial intelligence (AI) model AlphaFold made it possible to predict protein structures, would the technology open the drug discovery floodgates?
Short answer: No. At least not yet.
The longer answer goes something like this:
A drug target (such as a mutation) is like a lock. The right drug (a protein designed to bind to the mutation, stopping its activity) is the key. But proteins are fidgety and flexible.
“They’re basically molecular springs,” said Gabriel Monteiro da Silva, PhD, a computational chemistry research scientist at Genesis Therapeutics. “Your key can bend and alter the shape of the lock, and if you don’t account for that, your key might fail.”
This is the protein problem in drug development. Another issue making this challenge so vexing is that proteins don’t act in isolation. Their interactions with other proteins, ribonucleic acid, and DNA can affect how they bind to molecules and the shapes they adopt.
Newer versions of AlphaFold, such as AlphaFold Multimer and AlphaFold 3 (the code for which was recently revealed for academic use), can predict many interactions among proteins and between proteins and other molecules. But these tools still have weak points scientists are trying to overcome or work around.
“Those kinds of dynamics and multiple conformations are still quite challenging for the AI models to predict,” said James Zou, PhD, associate professor of biomedical data science at Stanford University in California.
“We’re finding more and more that the only way we can make these structures useful for drug discovery is if we incorporate dynamics, if we incorporate more physics into the model,” said Monteiro da Silva.
Monteiro da Silva spent 3 years during his PhD at Brown University, Providence, Rhode Island, running physics-based simulations in the lab, trying to understand why proteins carrying certain mutations are drug resistant. His results showed how “the changing landscape of shapes that a protein can take” prevented the drug from binding.
It took him 3 years to model just four mutations.
AI can do better — and the struggle is fascinating. By developing models that build on the predictive power of AlphaFold, scientists are uncovering new details about protein activity — insights that can lead to new therapeutics and reveal why existing ones stop working — much faster than they could with traditional methods or AlphaFold alone.
New Windows into Protein Dynamics
A notable step, “but that’s just the starting point,” said Pedro Beltrao, PhD, an associate professor at Institute of Molecular Systems Biology, ETH Zurich in Switzerland. “It’s still very difficult, given a pocket, to actually design the drug or figure out what the pocket binds.”
Going back to the lock-and-key analogy: While he was at Brown, with a team of researchers in the Rubenstein Group, Monteiro da Silva helped create a model to better understand how mutations affect “the shape and dynamics of the lock.” They manipulated the amino acid sequences of proteins, guiding their evolution. This enabled them to use AlphaFold to predict “protein ensembles” and how frequently those ensembles appear. Each ensemble represents the many different shapes a protein can take under given conditions.
“Essentially, it tries to find the most common shapes that a protein will take over an arbitrary amount of time,” Monteiro da Silva said. “If we can predict these ensembles at scale and fast, then we can screen many mutations that cause resistance and develop drugs that will not be affected by that resistance.”
To evaluate their method, the researchers focused on ABL1, a well-studied kinase that causes leukemia. ABL1 can be drugged – unless it carries or develops a mutation that causes drug resistance. Currently there are no drugs that work against proteins carrying those mutations, according to Monteiro da Silva. The researchers used their hybrid AI-meets-physics method to investigate how drugs bind to different ABL1 mutations, screening 100 mutations in just 1 month.
“It’s not going to be perfect for every one of them. But if we have 100 and we get 20 with good accuracy, that’s better than doing four over 3 years,” Monteiro da Silva said.
A forthcoming paper will make their model publicly available in “an easy-to-use graphical interface” that they hope clinicians and medicinal chemists will try out. It can also complement other AI-based tools that dig into protein dynamics, according to Monteiro da Silva.
Complementary Tools to Speed Up Discovery
Another aspect of the protein problem is scale. One protein can interact with hundreds of other proteins, which in turn may interact with hundreds more, all of which comprise the human interactome.
Feixiong Cheng, PhD, helped build PIONEER, a deep learning model that predicts the three-dimensional (3D) structure of interactions between proteins across the interactome.
Most disease mutations disrupt specific interactions between proteins, making their affinity stronger or weaker, explained Cheng. To treat a disease without causing major side effects, scientists need a precise understanding of those interactions.
“From the drug discovery perspective, we cannot just focus on single proteins. We have to understand the protein environment, in particular how the protein interacts with other proteins,” said Cheng, director of Cleveland Clinic Genome Center, Cleveland.
PIONEER helps by blending AlphaFold’s protein structure predictions with next-generation sequencing, a type of genomic research that identifies mutations in the human genome. The model predicts the 3D structure of the places where proteins interact — the binding sites, or interfaces — across the interactome.
“We tell you not only that a binds b, but where on a and where on b the two proteins interact,” said Haiyuan Yu, PhD, director of the Center for Innovative Proteomics, Cornell University, and co-creator of PIONEER.
This can help scientists understand “why a mutation, protein, or even network is a good target for therapeutic discovery,” Cheng said.
The researchers validated PIONEER’s predictions in the lab, testing the impacts of roughly 3000 mutations on 7000 pairs of interacting proteins. Based on their findings, they plan to develop and test treatments for lung and endometrial cancer.
PIONEER can also help scientists home in on how a mutation causes a disease, such as by showing recurrent mutations.
“If you find cancer mutations hitting an interface again and again and again, it means that this is likely to be driving cancer progression,” said Beltrao.
Beltrao’s lab and others have looked for recurrent mutations by using AlphaFold Multimer and AlphaFold 3 to directly model protein interactions. It’s a much slower approach (Pioneer is more than 5000 faster than AlphaFold Multimer, according to Cheng). But it could allow scientists to model interfaces that are not shown by PIONEER.
“You will need many different things to try to come up with a structural modeling of the interactome, and all these will have limitations,” said Beltrao. “Their method is a very good step forward, and there’ll be other approaches that are complementary, to continue to add details.”
And It Wouldn’t be an AI Mission Without ChatGPT
Large language models, such as ChatGPT, are another way that scientists are adding details to protein structure predictions. Zou used GPT-4 to “fine tune” a protein language model, called evolutionary scale modeling (ESM-2), which predicts protein structures directly from a protein sequence.
First, they trained ChatGPT on thousands of papers and studies containing information about the functions, biophysical properties, and disease relevance of different mutations. Next, they used the trained model to “teach” ESM-2, boosting its ability “to predict which mutations are likely to have larger effects or smaller effects,” Zou said. The same could be done for a model like AlphaFold, according to Zou.
“They are quite complementary in that the large language model contains a lot more information about the functions and the biophysics of different mutations and proteins as captured in text,” he said, whereas “you can’t give AlphaFold a piece of paper.”
Exactly how AlphaFold makes its predictions is another mystery. “It will somehow learn protein dynamics phenomenologically,” said Monteiro da Silva. He and others are trying to understand how that happens, in hopes of creating even more accurate predictive models. But for the time being, AI-based methods still need assistance from physics.
“The dream is that we achieve a state where we rely on just the fast methods, and they’re accurate enough,” he said. “But we’re so far from that.”
A version of this article first appeared on Medscape.com.
The question has been lingering for years in medical science circles. Since 2020, when the artificial intelligence (AI) model AlphaFold made it possible to predict protein structures, would the technology open the drug discovery floodgates?
Short answer: No. At least not yet.
The longer answer goes something like this:
A drug target (such as a mutation) is like a lock. The right drug (a protein designed to bind to the mutation, stopping its activity) is the key. But proteins are fidgety and flexible.
“They’re basically molecular springs,” said Gabriel Monteiro da Silva, PhD, a computational chemistry research scientist at Genesis Therapeutics. “Your key can bend and alter the shape of the lock, and if you don’t account for that, your key might fail.”
This is the protein problem in drug development. Another issue making this challenge so vexing is that proteins don’t act in isolation. Their interactions with other proteins, ribonucleic acid, and DNA can affect how they bind to molecules and the shapes they adopt.
Newer versions of AlphaFold, such as AlphaFold Multimer and AlphaFold 3 (the code for which was recently revealed for academic use), can predict many interactions among proteins and between proteins and other molecules. But these tools still have weak points scientists are trying to overcome or work around.
“Those kinds of dynamics and multiple conformations are still quite challenging for the AI models to predict,” said James Zou, PhD, associate professor of biomedical data science at Stanford University in California.
“We’re finding more and more that the only way we can make these structures useful for drug discovery is if we incorporate dynamics, if we incorporate more physics into the model,” said Monteiro da Silva.
Monteiro da Silva spent 3 years during his PhD at Brown University, Providence, Rhode Island, running physics-based simulations in the lab, trying to understand why proteins carrying certain mutations are drug resistant. His results showed how “the changing landscape of shapes that a protein can take” prevented the drug from binding.
It took him 3 years to model just four mutations.
AI can do better — and the struggle is fascinating. By developing models that build on the predictive power of AlphaFold, scientists are uncovering new details about protein activity — insights that can lead to new therapeutics and reveal why existing ones stop working — much faster than they could with traditional methods or AlphaFold alone.
New Windows into Protein Dynamics
A notable step, “but that’s just the starting point,” said Pedro Beltrao, PhD, an associate professor at Institute of Molecular Systems Biology, ETH Zurich in Switzerland. “It’s still very difficult, given a pocket, to actually design the drug or figure out what the pocket binds.”
Going back to the lock-and-key analogy: While he was at Brown, with a team of researchers in the Rubenstein Group, Monteiro da Silva helped create a model to better understand how mutations affect “the shape and dynamics of the lock.” They manipulated the amino acid sequences of proteins, guiding their evolution. This enabled them to use AlphaFold to predict “protein ensembles” and how frequently those ensembles appear. Each ensemble represents the many different shapes a protein can take under given conditions.
“Essentially, it tries to find the most common shapes that a protein will take over an arbitrary amount of time,” Monteiro da Silva said. “If we can predict these ensembles at scale and fast, then we can screen many mutations that cause resistance and develop drugs that will not be affected by that resistance.”
To evaluate their method, the researchers focused on ABL1, a well-studied kinase that causes leukemia. ABL1 can be drugged – unless it carries or develops a mutation that causes drug resistance. Currently there are no drugs that work against proteins carrying those mutations, according to Monteiro da Silva. The researchers used their hybrid AI-meets-physics method to investigate how drugs bind to different ABL1 mutations, screening 100 mutations in just 1 month.
“It’s not going to be perfect for every one of them. But if we have 100 and we get 20 with good accuracy, that’s better than doing four over 3 years,” Monteiro da Silva said.
A forthcoming paper will make their model publicly available in “an easy-to-use graphical interface” that they hope clinicians and medicinal chemists will try out. It can also complement other AI-based tools that dig into protein dynamics, according to Monteiro da Silva.
Complementary Tools to Speed Up Discovery
Another aspect of the protein problem is scale. One protein can interact with hundreds of other proteins, which in turn may interact with hundreds more, all of which comprise the human interactome.
Feixiong Cheng, PhD, helped build PIONEER, a deep learning model that predicts the three-dimensional (3D) structure of interactions between proteins across the interactome.
Most disease mutations disrupt specific interactions between proteins, making their affinity stronger or weaker, explained Cheng. To treat a disease without causing major side effects, scientists need a precise understanding of those interactions.
“From the drug discovery perspective, we cannot just focus on single proteins. We have to understand the protein environment, in particular how the protein interacts with other proteins,” said Cheng, director of Cleveland Clinic Genome Center, Cleveland.
PIONEER helps by blending AlphaFold’s protein structure predictions with next-generation sequencing, a type of genomic research that identifies mutations in the human genome. The model predicts the 3D structure of the places where proteins interact — the binding sites, or interfaces — across the interactome.
“We tell you not only that a binds b, but where on a and where on b the two proteins interact,” said Haiyuan Yu, PhD, director of the Center for Innovative Proteomics, Cornell University, and co-creator of PIONEER.
This can help scientists understand “why a mutation, protein, or even network is a good target for therapeutic discovery,” Cheng said.
The researchers validated PIONEER’s predictions in the lab, testing the impacts of roughly 3000 mutations on 7000 pairs of interacting proteins. Based on their findings, they plan to develop and test treatments for lung and endometrial cancer.
PIONEER can also help scientists home in on how a mutation causes a disease, such as by showing recurrent mutations.
“If you find cancer mutations hitting an interface again and again and again, it means that this is likely to be driving cancer progression,” said Beltrao.
Beltrao’s lab and others have looked for recurrent mutations by using AlphaFold Multimer and AlphaFold 3 to directly model protein interactions. It’s a much slower approach (Pioneer is more than 5000 faster than AlphaFold Multimer, according to Cheng). But it could allow scientists to model interfaces that are not shown by PIONEER.
“You will need many different things to try to come up with a structural modeling of the interactome, and all these will have limitations,” said Beltrao. “Their method is a very good step forward, and there’ll be other approaches that are complementary, to continue to add details.”
And It Wouldn’t be an AI Mission Without ChatGPT
Large language models, such as ChatGPT, are another way that scientists are adding details to protein structure predictions. Zou used GPT-4 to “fine tune” a protein language model, called evolutionary scale modeling (ESM-2), which predicts protein structures directly from a protein sequence.
First, they trained ChatGPT on thousands of papers and studies containing information about the functions, biophysical properties, and disease relevance of different mutations. Next, they used the trained model to “teach” ESM-2, boosting its ability “to predict which mutations are likely to have larger effects or smaller effects,” Zou said. The same could be done for a model like AlphaFold, according to Zou.
“They are quite complementary in that the large language model contains a lot more information about the functions and the biophysics of different mutations and proteins as captured in text,” he said, whereas “you can’t give AlphaFold a piece of paper.”
Exactly how AlphaFold makes its predictions is another mystery. “It will somehow learn protein dynamics phenomenologically,” said Monteiro da Silva. He and others are trying to understand how that happens, in hopes of creating even more accurate predictive models. But for the time being, AI-based methods still need assistance from physics.
“The dream is that we achieve a state where we rely on just the fast methods, and they’re accurate enough,” he said. “But we’re so far from that.”
A version of this article first appeared on Medscape.com.
The question has been lingering for years in medical science circles. Since 2020, when the artificial intelligence (AI) model AlphaFold made it possible to predict protein structures, would the technology open the drug discovery floodgates?
Short answer: No. At least not yet.
The longer answer goes something like this:
A drug target (such as a mutation) is like a lock. The right drug (a protein designed to bind to the mutation, stopping its activity) is the key. But proteins are fidgety and flexible.
“They’re basically molecular springs,” said Gabriel Monteiro da Silva, PhD, a computational chemistry research scientist at Genesis Therapeutics. “Your key can bend and alter the shape of the lock, and if you don’t account for that, your key might fail.”
This is the protein problem in drug development. Another issue making this challenge so vexing is that proteins don’t act in isolation. Their interactions with other proteins, ribonucleic acid, and DNA can affect how they bind to molecules and the shapes they adopt.
Newer versions of AlphaFold, such as AlphaFold Multimer and AlphaFold 3 (the code for which was recently revealed for academic use), can predict many interactions among proteins and between proteins and other molecules. But these tools still have weak points scientists are trying to overcome or work around.
“Those kinds of dynamics and multiple conformations are still quite challenging for the AI models to predict,” said James Zou, PhD, associate professor of biomedical data science at Stanford University in California.
“We’re finding more and more that the only way we can make these structures useful for drug discovery is if we incorporate dynamics, if we incorporate more physics into the model,” said Monteiro da Silva.
Monteiro da Silva spent 3 years during his PhD at Brown University, Providence, Rhode Island, running physics-based simulations in the lab, trying to understand why proteins carrying certain mutations are drug resistant. His results showed how “the changing landscape of shapes that a protein can take” prevented the drug from binding.
It took him 3 years to model just four mutations.
AI can do better — and the struggle is fascinating. By developing models that build on the predictive power of AlphaFold, scientists are uncovering new details about protein activity — insights that can lead to new therapeutics and reveal why existing ones stop working — much faster than they could with traditional methods or AlphaFold alone.
New Windows into Protein Dynamics
A notable step, “but that’s just the starting point,” said Pedro Beltrao, PhD, an associate professor at Institute of Molecular Systems Biology, ETH Zurich in Switzerland. “It’s still very difficult, given a pocket, to actually design the drug or figure out what the pocket binds.”
Going back to the lock-and-key analogy: While he was at Brown, with a team of researchers in the Rubenstein Group, Monteiro da Silva helped create a model to better understand how mutations affect “the shape and dynamics of the lock.” They manipulated the amino acid sequences of proteins, guiding their evolution. This enabled them to use AlphaFold to predict “protein ensembles” and how frequently those ensembles appear. Each ensemble represents the many different shapes a protein can take under given conditions.
“Essentially, it tries to find the most common shapes that a protein will take over an arbitrary amount of time,” Monteiro da Silva said. “If we can predict these ensembles at scale and fast, then we can screen many mutations that cause resistance and develop drugs that will not be affected by that resistance.”
To evaluate their method, the researchers focused on ABL1, a well-studied kinase that causes leukemia. ABL1 can be drugged – unless it carries or develops a mutation that causes drug resistance. Currently there are no drugs that work against proteins carrying those mutations, according to Monteiro da Silva. The researchers used their hybrid AI-meets-physics method to investigate how drugs bind to different ABL1 mutations, screening 100 mutations in just 1 month.
“It’s not going to be perfect for every one of them. But if we have 100 and we get 20 with good accuracy, that’s better than doing four over 3 years,” Monteiro da Silva said.
A forthcoming paper will make their model publicly available in “an easy-to-use graphical interface” that they hope clinicians and medicinal chemists will try out. It can also complement other AI-based tools that dig into protein dynamics, according to Monteiro da Silva.
Complementary Tools to Speed Up Discovery
Another aspect of the protein problem is scale. One protein can interact with hundreds of other proteins, which in turn may interact with hundreds more, all of which comprise the human interactome.
Feixiong Cheng, PhD, helped build PIONEER, a deep learning model that predicts the three-dimensional (3D) structure of interactions between proteins across the interactome.
Most disease mutations disrupt specific interactions between proteins, making their affinity stronger or weaker, explained Cheng. To treat a disease without causing major side effects, scientists need a precise understanding of those interactions.
“From the drug discovery perspective, we cannot just focus on single proteins. We have to understand the protein environment, in particular how the protein interacts with other proteins,” said Cheng, director of Cleveland Clinic Genome Center, Cleveland.
PIONEER helps by blending AlphaFold’s protein structure predictions with next-generation sequencing, a type of genomic research that identifies mutations in the human genome. The model predicts the 3D structure of the places where proteins interact — the binding sites, or interfaces — across the interactome.
“We tell you not only that a binds b, but where on a and where on b the two proteins interact,” said Haiyuan Yu, PhD, director of the Center for Innovative Proteomics, Cornell University, and co-creator of PIONEER.
This can help scientists understand “why a mutation, protein, or even network is a good target for therapeutic discovery,” Cheng said.
The researchers validated PIONEER’s predictions in the lab, testing the impacts of roughly 3000 mutations on 7000 pairs of interacting proteins. Based on their findings, they plan to develop and test treatments for lung and endometrial cancer.
PIONEER can also help scientists home in on how a mutation causes a disease, such as by showing recurrent mutations.
“If you find cancer mutations hitting an interface again and again and again, it means that this is likely to be driving cancer progression,” said Beltrao.
Beltrao’s lab and others have looked for recurrent mutations by using AlphaFold Multimer and AlphaFold 3 to directly model protein interactions. It’s a much slower approach (Pioneer is more than 5000 faster than AlphaFold Multimer, according to Cheng). But it could allow scientists to model interfaces that are not shown by PIONEER.
“You will need many different things to try to come up with a structural modeling of the interactome, and all these will have limitations,” said Beltrao. “Their method is a very good step forward, and there’ll be other approaches that are complementary, to continue to add details.”
And It Wouldn’t be an AI Mission Without ChatGPT
Large language models, such as ChatGPT, are another way that scientists are adding details to protein structure predictions. Zou used GPT-4 to “fine tune” a protein language model, called evolutionary scale modeling (ESM-2), which predicts protein structures directly from a protein sequence.
First, they trained ChatGPT on thousands of papers and studies containing information about the functions, biophysical properties, and disease relevance of different mutations. Next, they used the trained model to “teach” ESM-2, boosting its ability “to predict which mutations are likely to have larger effects or smaller effects,” Zou said. The same could be done for a model like AlphaFold, according to Zou.
“They are quite complementary in that the large language model contains a lot more information about the functions and the biophysics of different mutations and proteins as captured in text,” he said, whereas “you can’t give AlphaFold a piece of paper.”
Exactly how AlphaFold makes its predictions is another mystery. “It will somehow learn protein dynamics phenomenologically,” said Monteiro da Silva. He and others are trying to understand how that happens, in hopes of creating even more accurate predictive models. But for the time being, AI-based methods still need assistance from physics.
“The dream is that we achieve a state where we rely on just the fast methods, and they’re accurate enough,” he said. “But we’re so far from that.”
A version of this article first appeared on Medscape.com.
Smoking Cessation Offers Benefits at Any Age
This transcript has been edited for clarity.
I would like to briefly talk about a very interesting paper and one that probably has about as much to inform the doctor-patient relationship as any paper you can think of.
The title itself gives you a little bit of that answer before I even discuss the outcome. The paper is “The Benefits of Quitting Smoking at Different Ages,” recently published in The American Journal of Preventive Medicine.
I’m not going to even begin to attempt to explore the statistics of the analysis, but I think the conclusions are both fascinating and important. I will read the first sentence of the results and then just comment on some of the others because there’s just so much data here and I really want to focus on the punchline.
The results section said that, compared with people who never smoked, those who smoke currently, aged 35, 45, 55, 65, or 75, (those were all the groups they looked at), and who have smoked throughout adulthood until that age will lose an average of 9.1, 8.3, 7.3, 5.9, and 4.4 years of life, respectively — obviously, it’s a lot — if they continue to smoke for the rest of their lives.
We know that. It’s terrible. That’s why people should never smoke. Period. End of story. There’s no social value. There’s no health value of smoking. It’s a deadly recreational activity for multiple illnesses, and obviously, cancer is prominent among them.
Here’s the conclusion of the paper that I think is interesting. That doctor, whether it’s a primary care doctor, an oncologist, an ob/gyn, or a family doctor, is seeing Mr Smith or Mrs Jones in the office today, whether they know that patient well or not very well, and they’re still smoking. However, if the person we’re describing here quits smoking at these ages, how much life do they add back, compared with if they continued?
They may say: “Oh, I’ve been smoking all my life. What difference does it make? The die is cast.” Wrong! If you’ve been smoking your whole adult life — so let’s just say that you started at age 18, age 20, age 15, or even age 12 — but you quit smoking at the age of 35, you’re going to add 8 years of life on average. If you quit smoking when you’re 65, having smoked your whole adult life, you will add 1.7 years of life. That’s 1.7 years to be with your family, to be with your grandchildren, and enjoy life. If you ask, “Oh, what difference does it make?” It makes a big difference.
I’ll share another statistic and I’ll be done. I think this is really an interesting one. The chances of gaining at least a year of life among those who quit smoking at the age of 65 was 23.4%. There is a 1 out of 4 chance that you’re going to live an additional year if you stop at age 65. Even if you stop smoking at age 75, you have a 14% chance of living at least an additional year longer than you would have if you didn’t stop smoking.
There is much to think about here, much to consider, and much to discuss potentially with patients.
Dr. Markman is Professor of Medical Oncology and Therapeutics Research, City of Hope Comprehensive Cancer Center; President, Medicine & Science, City of Hope Atlanta, Chicago, Phoenix. He reported conflicts of interest with GlaxoSmithKline and AstraZeneca.
A version of this article first appeared on Medscape.com.
This transcript has been edited for clarity.
I would like to briefly talk about a very interesting paper and one that probably has about as much to inform the doctor-patient relationship as any paper you can think of.
The title itself gives you a little bit of that answer before I even discuss the outcome. The paper is “The Benefits of Quitting Smoking at Different Ages,” recently published in The American Journal of Preventive Medicine.
I’m not going to even begin to attempt to explore the statistics of the analysis, but I think the conclusions are both fascinating and important. I will read the first sentence of the results and then just comment on some of the others because there’s just so much data here and I really want to focus on the punchline.
The results section said that, compared with people who never smoked, those who smoke currently, aged 35, 45, 55, 65, or 75, (those were all the groups they looked at), and who have smoked throughout adulthood until that age will lose an average of 9.1, 8.3, 7.3, 5.9, and 4.4 years of life, respectively — obviously, it’s a lot — if they continue to smoke for the rest of their lives.
We know that. It’s terrible. That’s why people should never smoke. Period. End of story. There’s no social value. There’s no health value of smoking. It’s a deadly recreational activity for multiple illnesses, and obviously, cancer is prominent among them.
Here’s the conclusion of the paper that I think is interesting. That doctor, whether it’s a primary care doctor, an oncologist, an ob/gyn, or a family doctor, is seeing Mr Smith or Mrs Jones in the office today, whether they know that patient well or not very well, and they’re still smoking. However, if the person we’re describing here quits smoking at these ages, how much life do they add back, compared with if they continued?
They may say: “Oh, I’ve been smoking all my life. What difference does it make? The die is cast.” Wrong! If you’ve been smoking your whole adult life — so let’s just say that you started at age 18, age 20, age 15, or even age 12 — but you quit smoking at the age of 35, you’re going to add 8 years of life on average. If you quit smoking when you’re 65, having smoked your whole adult life, you will add 1.7 years of life. That’s 1.7 years to be with your family, to be with your grandchildren, and enjoy life. If you ask, “Oh, what difference does it make?” It makes a big difference.
I’ll share another statistic and I’ll be done. I think this is really an interesting one. The chances of gaining at least a year of life among those who quit smoking at the age of 65 was 23.4%. There is a 1 out of 4 chance that you’re going to live an additional year if you stop at age 65. Even if you stop smoking at age 75, you have a 14% chance of living at least an additional year longer than you would have if you didn’t stop smoking.
There is much to think about here, much to consider, and much to discuss potentially with patients.
Dr. Markman is Professor of Medical Oncology and Therapeutics Research, City of Hope Comprehensive Cancer Center; President, Medicine & Science, City of Hope Atlanta, Chicago, Phoenix. He reported conflicts of interest with GlaxoSmithKline and AstraZeneca.
A version of this article first appeared on Medscape.com.
This transcript has been edited for clarity.
I would like to briefly talk about a very interesting paper and one that probably has about as much to inform the doctor-patient relationship as any paper you can think of.
The title itself gives you a little bit of that answer before I even discuss the outcome. The paper is “The Benefits of Quitting Smoking at Different Ages,” recently published in The American Journal of Preventive Medicine.
I’m not going to even begin to attempt to explore the statistics of the analysis, but I think the conclusions are both fascinating and important. I will read the first sentence of the results and then just comment on some of the others because there’s just so much data here and I really want to focus on the punchline.
The results section said that, compared with people who never smoked, those who smoke currently, aged 35, 45, 55, 65, or 75, (those were all the groups they looked at), and who have smoked throughout adulthood until that age will lose an average of 9.1, 8.3, 7.3, 5.9, and 4.4 years of life, respectively — obviously, it’s a lot — if they continue to smoke for the rest of their lives.
We know that. It’s terrible. That’s why people should never smoke. Period. End of story. There’s no social value. There’s no health value of smoking. It’s a deadly recreational activity for multiple illnesses, and obviously, cancer is prominent among them.
Here’s the conclusion of the paper that I think is interesting. That doctor, whether it’s a primary care doctor, an oncologist, an ob/gyn, or a family doctor, is seeing Mr Smith or Mrs Jones in the office today, whether they know that patient well or not very well, and they’re still smoking. However, if the person we’re describing here quits smoking at these ages, how much life do they add back, compared with if they continued?
They may say: “Oh, I’ve been smoking all my life. What difference does it make? The die is cast.” Wrong! If you’ve been smoking your whole adult life — so let’s just say that you started at age 18, age 20, age 15, or even age 12 — but you quit smoking at the age of 35, you’re going to add 8 years of life on average. If you quit smoking when you’re 65, having smoked your whole adult life, you will add 1.7 years of life. That’s 1.7 years to be with your family, to be with your grandchildren, and enjoy life. If you ask, “Oh, what difference does it make?” It makes a big difference.
I’ll share another statistic and I’ll be done. I think this is really an interesting one. The chances of gaining at least a year of life among those who quit smoking at the age of 65 was 23.4%. There is a 1 out of 4 chance that you’re going to live an additional year if you stop at age 65. Even if you stop smoking at age 75, you have a 14% chance of living at least an additional year longer than you would have if you didn’t stop smoking.
There is much to think about here, much to consider, and much to discuss potentially with patients.
Dr. Markman is Professor of Medical Oncology and Therapeutics Research, City of Hope Comprehensive Cancer Center; President, Medicine & Science, City of Hope Atlanta, Chicago, Phoenix. He reported conflicts of interest with GlaxoSmithKline and AstraZeneca.
A version of this article first appeared on Medscape.com.
Why Insurers Keep Denying Claims (And What to Do)
This transcript has been edited for clarity.
Oh, insurance claim denials. When patient care or treatment is warranted by a specific diagnosis, I wish insurers would just reimburse it without any hassle. That’s not reality. Let’s talk about insurance claim denials, how they’re rising and harming patient care, and what we can do about it. That’s kind of complicated.
Rising Trend in Claim Denials and Financial Impact
First, denials are increasing. Experian Health surveyed provider revenue cycle leaders— that’s a fancy term for people who manage billing and insurance claims — and 75% said that denials are increasing. This is up from 42% a few years ago. Those surveyed also said that reimbursement times and errors in claims are also increasing, and changes in policy are happening more frequently. This all adds to the problem.
Aside from being time-consuming and annoying, claim denials take a toll on hospitals and patients. One analysis, which made headlines everywhere, showed that hospitals and health systems spent nearly $20 billion in 2022 trying to repeal overturned claims. This analysis was done by Premier, a health insurance performance company.
Breakdown of Denial Rates and Costs
Let’s do some quick whiteboard math. Health insurance companies get about 3 billion claims per year. According to surveys, about 15% of those claims are denied, so that leaves us with 450 million denied claims. Hospitals spend, on average, $43.84 per denied claim in administrative fees trying to get them overturned.
That’s about $19.7 billion spent on claim denials. Here’s the gut punch: Around 54% of those claims are ultimately paid, so that leaves us with $10.7 billion that we definitely should have saved.
Common Reasons for Denials
Let’s take a look at major causes and what’s going on.
Insurance denial rates are all over the place. It depends on state and plan. According to one analysis, the average for in-network claim denials across some states was 4% to 5%. It was 40% in Mississippi. According to HealthCare.gov, in 2021, around 17% of in-network claims were denied.
The most common reasons were excluded services, a lack of referral or preauthorization, or a medical treatment not being deemed necessary. Then there’s the black box of “other,” just some arbitrary reason to make a claim denial.
Many times, these denials are done by an algorithm, not by individual people.
What’s more, a Kaiser Family Foundation analysis found that private insurers, including Medicare Advantage plans, were more likely to deny claims than public options.
When broken down, the problem was higher among employer-sponsored and marketplace insurance, and less so with Medicare and Medicaid.
Impact on Patient Care
Many consumers don’t truly understand what their health insurance covers and what’s going to be out of pocket, and many people don’t know that they have appeal rights. They don’t know who to call for help either.
The ACA set up Consumer Assistance Programs (CAPs), which are designed to help people navigate health insurance problems. By law, private insurers have to share data with CAPs. Yet, only 3% of people who had trouble with health insurance claims called a CAP for help.
We all know some of the downstream effects of this problem. Patients may skip or delay treatments if they can’t get insurance to cover it or it’s too expensive. When post-acute care, such as transfer to a skilled nursing facility or rehab center, isn’t covered and we’re trying to discharge patients from the hospital, hospital stays become lengthened, which means they’re more expensive, and this comes with its own set of complications.
How Can We Address This?
I’m genuinely curious about what you all have done to efficiently address this problem. I’m looking at this publication from the American Health Information Management Association about major reasons for denial. We’ve already talked about a lack of preauthorization or procedures not being covered, but there are also reasons such as missing or incorrect information, duplicate claims, and not filing within the appropriate time.
Also, if treatments or procedures are bundled, they can’t be filed separately.
Preventing all of this would take a large effort. Healthcare systems would have to have a dedicated team, who would understand all the major reasons for denials, identify common patterns, and then fill everything out with accurate information, with referrals, with preauthorizations, high-specificity codes, and the correct modifiers — and do all of this within the filing deadline every time.
You would need physicians on board, but also people from IT, finance, compliance, case management, registration, and probably a bunch of other people who are already stretched too thin.
Perhaps our government can do more to hold insurers accountable and make sure plans, such as Medicare Advantage, are holding up their end of the public health bargain.
It’s an uphill $20 billion battle, but I’m optimistic. What about you? What’s your unfiltered take on claim denials? What more can we be doing?
Dr. Patel is a clinical instructor, Department of Pediatrics, Columbia University College of Physicians and Surgeons; pediatric hospitalist, Morgan Stanley Children’s Hospital of NewYork-Presbyterian, New York City, and Benioff Children’s Hospital, University of California, San Francisco. He reported a conflict of interest with Medumo.
A version of this article first appeared on Medscape.com.
This transcript has been edited for clarity.
Oh, insurance claim denials. When patient care or treatment is warranted by a specific diagnosis, I wish insurers would just reimburse it without any hassle. That’s not reality. Let’s talk about insurance claim denials, how they’re rising and harming patient care, and what we can do about it. That’s kind of complicated.
Rising Trend in Claim Denials and Financial Impact
First, denials are increasing. Experian Health surveyed provider revenue cycle leaders— that’s a fancy term for people who manage billing and insurance claims — and 75% said that denials are increasing. This is up from 42% a few years ago. Those surveyed also said that reimbursement times and errors in claims are also increasing, and changes in policy are happening more frequently. This all adds to the problem.
Aside from being time-consuming and annoying, claim denials take a toll on hospitals and patients. One analysis, which made headlines everywhere, showed that hospitals and health systems spent nearly $20 billion in 2022 trying to repeal overturned claims. This analysis was done by Premier, a health insurance performance company.
Breakdown of Denial Rates and Costs
Let’s do some quick whiteboard math. Health insurance companies get about 3 billion claims per year. According to surveys, about 15% of those claims are denied, so that leaves us with 450 million denied claims. Hospitals spend, on average, $43.84 per denied claim in administrative fees trying to get them overturned.
That’s about $19.7 billion spent on claim denials. Here’s the gut punch: Around 54% of those claims are ultimately paid, so that leaves us with $10.7 billion that we definitely should have saved.
Common Reasons for Denials
Let’s take a look at major causes and what’s going on.
Insurance denial rates are all over the place. It depends on state and plan. According to one analysis, the average for in-network claim denials across some states was 4% to 5%. It was 40% in Mississippi. According to HealthCare.gov, in 2021, around 17% of in-network claims were denied.
The most common reasons were excluded services, a lack of referral or preauthorization, or a medical treatment not being deemed necessary. Then there’s the black box of “other,” just some arbitrary reason to make a claim denial.
Many times, these denials are done by an algorithm, not by individual people.
What’s more, a Kaiser Family Foundation analysis found that private insurers, including Medicare Advantage plans, were more likely to deny claims than public options.
When broken down, the problem was higher among employer-sponsored and marketplace insurance, and less so with Medicare and Medicaid.
Impact on Patient Care
Many consumers don’t truly understand what their health insurance covers and what’s going to be out of pocket, and many people don’t know that they have appeal rights. They don’t know who to call for help either.
The ACA set up Consumer Assistance Programs (CAPs), which are designed to help people navigate health insurance problems. By law, private insurers have to share data with CAPs. Yet, only 3% of people who had trouble with health insurance claims called a CAP for help.
We all know some of the downstream effects of this problem. Patients may skip or delay treatments if they can’t get insurance to cover it or it’s too expensive. When post-acute care, such as transfer to a skilled nursing facility or rehab center, isn’t covered and we’re trying to discharge patients from the hospital, hospital stays become lengthened, which means they’re more expensive, and this comes with its own set of complications.
How Can We Address This?
I’m genuinely curious about what you all have done to efficiently address this problem. I’m looking at this publication from the American Health Information Management Association about major reasons for denial. We’ve already talked about a lack of preauthorization or procedures not being covered, but there are also reasons such as missing or incorrect information, duplicate claims, and not filing within the appropriate time.
Also, if treatments or procedures are bundled, they can’t be filed separately.
Preventing all of this would take a large effort. Healthcare systems would have to have a dedicated team, who would understand all the major reasons for denials, identify common patterns, and then fill everything out with accurate information, with referrals, with preauthorizations, high-specificity codes, and the correct modifiers — and do all of this within the filing deadline every time.
You would need physicians on board, but also people from IT, finance, compliance, case management, registration, and probably a bunch of other people who are already stretched too thin.
Perhaps our government can do more to hold insurers accountable and make sure plans, such as Medicare Advantage, are holding up their end of the public health bargain.
It’s an uphill $20 billion battle, but I’m optimistic. What about you? What’s your unfiltered take on claim denials? What more can we be doing?
Dr. Patel is a clinical instructor, Department of Pediatrics, Columbia University College of Physicians and Surgeons; pediatric hospitalist, Morgan Stanley Children’s Hospital of NewYork-Presbyterian, New York City, and Benioff Children’s Hospital, University of California, San Francisco. He reported a conflict of interest with Medumo.
A version of this article first appeared on Medscape.com.
This transcript has been edited for clarity.
Oh, insurance claim denials. When patient care or treatment is warranted by a specific diagnosis, I wish insurers would just reimburse it without any hassle. That’s not reality. Let’s talk about insurance claim denials, how they’re rising and harming patient care, and what we can do about it. That’s kind of complicated.
Rising Trend in Claim Denials and Financial Impact
First, denials are increasing. Experian Health surveyed provider revenue cycle leaders— that’s a fancy term for people who manage billing and insurance claims — and 75% said that denials are increasing. This is up from 42% a few years ago. Those surveyed also said that reimbursement times and errors in claims are also increasing, and changes in policy are happening more frequently. This all adds to the problem.
Aside from being time-consuming and annoying, claim denials take a toll on hospitals and patients. One analysis, which made headlines everywhere, showed that hospitals and health systems spent nearly $20 billion in 2022 trying to repeal overturned claims. This analysis was done by Premier, a health insurance performance company.
Breakdown of Denial Rates and Costs
Let’s do some quick whiteboard math. Health insurance companies get about 3 billion claims per year. According to surveys, about 15% of those claims are denied, so that leaves us with 450 million denied claims. Hospitals spend, on average, $43.84 per denied claim in administrative fees trying to get them overturned.
That’s about $19.7 billion spent on claim denials. Here’s the gut punch: Around 54% of those claims are ultimately paid, so that leaves us with $10.7 billion that we definitely should have saved.
Common Reasons for Denials
Let’s take a look at major causes and what’s going on.
Insurance denial rates are all over the place. It depends on state and plan. According to one analysis, the average for in-network claim denials across some states was 4% to 5%. It was 40% in Mississippi. According to HealthCare.gov, in 2021, around 17% of in-network claims were denied.
The most common reasons were excluded services, a lack of referral or preauthorization, or a medical treatment not being deemed necessary. Then there’s the black box of “other,” just some arbitrary reason to make a claim denial.
Many times, these denials are done by an algorithm, not by individual people.
What’s more, a Kaiser Family Foundation analysis found that private insurers, including Medicare Advantage plans, were more likely to deny claims than public options.
When broken down, the problem was higher among employer-sponsored and marketplace insurance, and less so with Medicare and Medicaid.
Impact on Patient Care
Many consumers don’t truly understand what their health insurance covers and what’s going to be out of pocket, and many people don’t know that they have appeal rights. They don’t know who to call for help either.
The ACA set up Consumer Assistance Programs (CAPs), which are designed to help people navigate health insurance problems. By law, private insurers have to share data with CAPs. Yet, only 3% of people who had trouble with health insurance claims called a CAP for help.
We all know some of the downstream effects of this problem. Patients may skip or delay treatments if they can’t get insurance to cover it or it’s too expensive. When post-acute care, such as transfer to a skilled nursing facility or rehab center, isn’t covered and we’re trying to discharge patients from the hospital, hospital stays become lengthened, which means they’re more expensive, and this comes with its own set of complications.
How Can We Address This?
I’m genuinely curious about what you all have done to efficiently address this problem. I’m looking at this publication from the American Health Information Management Association about major reasons for denial. We’ve already talked about a lack of preauthorization or procedures not being covered, but there are also reasons such as missing or incorrect information, duplicate claims, and not filing within the appropriate time.
Also, if treatments or procedures are bundled, they can’t be filed separately.
Preventing all of this would take a large effort. Healthcare systems would have to have a dedicated team, who would understand all the major reasons for denials, identify common patterns, and then fill everything out with accurate information, with referrals, with preauthorizations, high-specificity codes, and the correct modifiers — and do all of this within the filing deadline every time.
You would need physicians on board, but also people from IT, finance, compliance, case management, registration, and probably a bunch of other people who are already stretched too thin.
Perhaps our government can do more to hold insurers accountable and make sure plans, such as Medicare Advantage, are holding up their end of the public health bargain.
It’s an uphill $20 billion battle, but I’m optimistic. What about you? What’s your unfiltered take on claim denials? What more can we be doing?
Dr. Patel is a clinical instructor, Department of Pediatrics, Columbia University College of Physicians and Surgeons; pediatric hospitalist, Morgan Stanley Children’s Hospital of NewYork-Presbyterian, New York City, and Benioff Children’s Hospital, University of California, San Francisco. He reported a conflict of interest with Medumo.
A version of this article first appeared on Medscape.com.
Eye Toxicities Are a Growing Concern With Certain ADCs
Such experts called for greater collaboration between oncologists and ophthalmologists, in interviews with Medscape Medical News.
ADCs combine a monoclonal antibody targeted at an antigen overexpressed on cancer cells with a toxic chemotherapy payload — the aim being to maximize the effectiveness of the drug against the tumor while minimizing the damage to healthy tissues and reducing systemic toxicity.
Yet trastuzumab duocarmazine (T-Duo), a third-generation human epidermal growth factor receptor 2 (HER2)–targeted ADC designed to treat HER2-positive breast cancer, was recently found to have a notable adverse effect in the TULIP trial of 437 patients.
As reported by Medscape Medical News, the drug was associated with a significant increase in progression-free survival over physician’s choice of therapy. However, 78% of patients in the ADC group experienced at least one treatment-emergent ocular toxicity adverse event vs 29.2% of those in the control group.
Moreover, grade 3 or high ocular toxicity events were reported by 21% of patients in the experimental group compared with none of those who received physician’s choice.
Ocular Toxicities Seen on Ocular Surface
Ocular toxicities with these drugs are “not necessarily a new thing,” said Joann J. Kang, MD, director, Cornea and Refractive Surgery, and associate professor of ophthalmology at Albert Einstein College of Medicine, Montefiore Medical Center, Bronx, New York.
“But what we’re seeing with certain ADCs is a lot of ocular toxicity, especially on the ocular surface,” with the degree toxicity varying depending on the ADC in question. “It’s definitely a real concern.”
Kang noted that separate from T-Duo, certain ADCs already come with black box warnings for ocular toxicity, including:
- Belantamab mafodotin (Blenrep) — approved for relapsed or refractory multiple myeloma and carries a warning specifically for keratopathy.
- Tisotumab vedotin (Tivdak) — indicated for recurrent or metastatic cervical cancer and can cause changes in the corneal epithelium and conjunctiva.
- Mirvetuximab soravtansine (Elahere) — used to treat folate receptor (FR) alpha–positive ovarian, fallopian tube, and peritoneal cancers and can lead to keratopathy, blurred vision, and dry eyes.
Indeed, the American Academy of Ophthalmology 2024 annual meeting saw research presented indicating that mirvetuximab was associated with moderate or severe corneal toxicity in 47% of patients treated for primary gynecologic malignancies.
As reported by Medscape Medical News, the study, by researchers at Byers Eye Institute of Stanford University in Stanford, California, was a retrospective analysis of 36 eyes of 18 women who received mirvetuximab for FR alpha–positive, platinum-resistant primary ovarian cancer.
What Are the Causes?
But why would a drug that is targeted specifically to a cancer tumor, thanks to the presence of a monoclonal antibody, cause off-target effects such as ocular toxicity?
Kathy D. Miller, MD, professor of oncology and medicine at Indiana University School of Medicine in Indianapolis, pointed out that they are targeted in a relative and not absolute sense, meaning that the antigen target may not be truly limited to the tumor cells.
There can also be “a lot of ways that you could get systemic toxicities,” she said.
For example, if the linker connecting the antibody and the chemotherapy payload breaks prematurely or is not stable, or if the drug leaches out into the tumor microenvironment and then is “picked up into the circulation, that can give you systemic toxicity,” she said.
In addition, the drug may, once it is in the tumor cells, be metabolized to an active metabolite that could, again, result in systemic exposure.
Side Effects Are Underappreciated and Distressing
Ocular toxicity remains underappreciated among oncologists prescribing these drugs. One reason is that it “did not get enough attention” in the initial clinical trial reports, Miller said she suspects.
Another potential reason for this is that “we’re not used to thinking about it because it’s not particularly common among the drugs that oncologists use frequently,” she added. Additionally, it tends to come up later during treatment, “so people have to be on therapy for some time before you start to see it.”
Nevertheless, Miller underlined that ocular toxicity “can be particularly distressing for patients, as it’s uncomfortable [and] can lead to scarring, so some of the vision issues can be permanent.”
“We often see in these situations that there are different types of ocular toxicities that present in different patients,” said Jane L. Meisel, MD, co-director, Breast Medical Oncology, Department of Hematology and Medical Oncology at Emory University School of Medicine in Atlanta.
“Corneal damage is pretty common, and patients can present with blurry vision, or dry eyes, or light sensitivity. And unlike some side effects, these are things that really impact people at every waking moment of their day.”
“So they’re pretty clinically significant side effects, even if they’re not life-threatening,” Meisel emphasized.
Miller suspects that more heavily pretreated patients may be more likely to experience ocular toxicity, as “there’s a much higher incidence of dry eyes in our patients than we recognize.”
She added: “We don’t usually ask about it, and we certainly don’t routinely do Schirmer’s tests,” which determine whether the eye produces enough tears to keep it moist.
Preventive Measures
For patients receiving tisotumab or mirvetuximab who experience ocular toxicity, Kang said the recommendation is to use steroid eye drops before, during, and after treatment with the ADC.
However, she noted that steroids have not been found to be useful in patients given belantamab, so clinicians have tried vasoconstrictor eye drops immediately prior to the infusion, as well as ocular cooling masks, which “are thought to help by reducing blood supply to the ocular areas.”
Other approaches to minimize ocular toxicity have included longer infusion times, so it’s “not so much of a hefty dose at one time,” Kang added.
She underlined that grade 2 and 3 ocular toxicities can lead to dose delays or dose modifications, and “usually by the time you get a grade 4 event, then you may need to discontinue the medication.”
This can have consequences for the patients because they are often “very sick, and this may be their third agent that they’re trying,” or it may be that their tumor is responding to a new treatment, but it has to be withheld because of an ocular toxicity.
“It can be incredibly frustrating for patients, and also for oncologists, and then for ophthalmologists,” Kang said.
Closer Collaboration Between Specialists Needed
What’s known about ocular side effects in patients taking ADCs underlines that there is a need for closer collaboration between oncologists and ophthalmologists.
“In oncology, especially as immunotherapies came to the forefront, our relationships with our endocrinology colleagues have become stronger because we’ve needed them to help us manage things like thyroid toxicity and pituitary issues related to immunotherapy,” Meisel said.
With toxicities that may be “very impactful for patient quality of life, like ocular toxicity, we will need to learn more about them and develop protocols for management, along with our ophthalmology colleagues, so that we can keep patients as comfortable as possible, while maximizing the efficacy of these drugs.”
Miller agreed, saying oncologists need to have “a conversation with a local ophthalmologist,” although she conceded that, in many areas, such specialists “are in short supply.”
The oncologist “not only needs to be aware” of and looking for ocular toxicity when using these ADCs but also needs to be thinking: “If I run into trouble here, who’s my ophthalmology backup? Are they familiar with this drug? And do we have a plan for the multispecialty management of patients who run into this toxicity?”
Setting Counts When Assessing Toxicities
But do all these considerations mean that ADCs’ potential ocular toxicity should give clinicians pause when considering whether to use these drugs?
“What my patients most want are drugs that work; that are effective in controlling their tumors,” Miller said.
“Every drug we use has potential toxicities, and which toxicities are most physically troublesome [or] are the greatest concern may vary from patient to patient, and it may vary a lot from patients with metastatic disease to those in the curative setting.”
She explained that “toxicities that might not be prohibitive at all in the metastatic setting [may] have to be a much bigger part of our considerations” when moving drugs into the adjuvant or neoadjuvant setting.
This, Miller underlined, is where the ocular toxicity with these ADCs “may be much more prohibitive.”
TULIP was funded by Byondis BV.
Turner declared relationships with Novartis, AstraZeneca, Pfizer, Merck Sharp & Dohme, Lilly, Repare Therapeutics, Roche, GlaxoSmithKline, Gilead Sciences, Inivata, Guardant Health, Exact Sciences, and Relay Therapeutics.
Meisel declared relationships with Novartis, AstraZeneca, Genentech, Seagen, Olema Oncology, GE Healthcare, Pfizer, Stemline, and Sermonix Pharmaceuticals.
A version of this article appeared on Medscape.com.
Such experts called for greater collaboration between oncologists and ophthalmologists, in interviews with Medscape Medical News.
ADCs combine a monoclonal antibody targeted at an antigen overexpressed on cancer cells with a toxic chemotherapy payload — the aim being to maximize the effectiveness of the drug against the tumor while minimizing the damage to healthy tissues and reducing systemic toxicity.
Yet trastuzumab duocarmazine (T-Duo), a third-generation human epidermal growth factor receptor 2 (HER2)–targeted ADC designed to treat HER2-positive breast cancer, was recently found to have a notable adverse effect in the TULIP trial of 437 patients.
As reported by Medscape Medical News, the drug was associated with a significant increase in progression-free survival over physician’s choice of therapy. However, 78% of patients in the ADC group experienced at least one treatment-emergent ocular toxicity adverse event vs 29.2% of those in the control group.
Moreover, grade 3 or high ocular toxicity events were reported by 21% of patients in the experimental group compared with none of those who received physician’s choice.
Ocular Toxicities Seen on Ocular Surface
Ocular toxicities with these drugs are “not necessarily a new thing,” said Joann J. Kang, MD, director, Cornea and Refractive Surgery, and associate professor of ophthalmology at Albert Einstein College of Medicine, Montefiore Medical Center, Bronx, New York.
“But what we’re seeing with certain ADCs is a lot of ocular toxicity, especially on the ocular surface,” with the degree toxicity varying depending on the ADC in question. “It’s definitely a real concern.”
Kang noted that separate from T-Duo, certain ADCs already come with black box warnings for ocular toxicity, including:
- Belantamab mafodotin (Blenrep) — approved for relapsed or refractory multiple myeloma and carries a warning specifically for keratopathy.
- Tisotumab vedotin (Tivdak) — indicated for recurrent or metastatic cervical cancer and can cause changes in the corneal epithelium and conjunctiva.
- Mirvetuximab soravtansine (Elahere) — used to treat folate receptor (FR) alpha–positive ovarian, fallopian tube, and peritoneal cancers and can lead to keratopathy, blurred vision, and dry eyes.
Indeed, the American Academy of Ophthalmology 2024 annual meeting saw research presented indicating that mirvetuximab was associated with moderate or severe corneal toxicity in 47% of patients treated for primary gynecologic malignancies.
As reported by Medscape Medical News, the study, by researchers at Byers Eye Institute of Stanford University in Stanford, California, was a retrospective analysis of 36 eyes of 18 women who received mirvetuximab for FR alpha–positive, platinum-resistant primary ovarian cancer.
What Are the Causes?
But why would a drug that is targeted specifically to a cancer tumor, thanks to the presence of a monoclonal antibody, cause off-target effects such as ocular toxicity?
Kathy D. Miller, MD, professor of oncology and medicine at Indiana University School of Medicine in Indianapolis, pointed out that they are targeted in a relative and not absolute sense, meaning that the antigen target may not be truly limited to the tumor cells.
There can also be “a lot of ways that you could get systemic toxicities,” she said.
For example, if the linker connecting the antibody and the chemotherapy payload breaks prematurely or is not stable, or if the drug leaches out into the tumor microenvironment and then is “picked up into the circulation, that can give you systemic toxicity,” she said.
In addition, the drug may, once it is in the tumor cells, be metabolized to an active metabolite that could, again, result in systemic exposure.
Side Effects Are Underappreciated and Distressing
Ocular toxicity remains underappreciated among oncologists prescribing these drugs. One reason is that it “did not get enough attention” in the initial clinical trial reports, Miller said she suspects.
Another potential reason for this is that “we’re not used to thinking about it because it’s not particularly common among the drugs that oncologists use frequently,” she added. Additionally, it tends to come up later during treatment, “so people have to be on therapy for some time before you start to see it.”
Nevertheless, Miller underlined that ocular toxicity “can be particularly distressing for patients, as it’s uncomfortable [and] can lead to scarring, so some of the vision issues can be permanent.”
“We often see in these situations that there are different types of ocular toxicities that present in different patients,” said Jane L. Meisel, MD, co-director, Breast Medical Oncology, Department of Hematology and Medical Oncology at Emory University School of Medicine in Atlanta.
“Corneal damage is pretty common, and patients can present with blurry vision, or dry eyes, or light sensitivity. And unlike some side effects, these are things that really impact people at every waking moment of their day.”
“So they’re pretty clinically significant side effects, even if they’re not life-threatening,” Meisel emphasized.
Miller suspects that more heavily pretreated patients may be more likely to experience ocular toxicity, as “there’s a much higher incidence of dry eyes in our patients than we recognize.”
She added: “We don’t usually ask about it, and we certainly don’t routinely do Schirmer’s tests,” which determine whether the eye produces enough tears to keep it moist.
Preventive Measures
For patients receiving tisotumab or mirvetuximab who experience ocular toxicity, Kang said the recommendation is to use steroid eye drops before, during, and after treatment with the ADC.
However, she noted that steroids have not been found to be useful in patients given belantamab, so clinicians have tried vasoconstrictor eye drops immediately prior to the infusion, as well as ocular cooling masks, which “are thought to help by reducing blood supply to the ocular areas.”
Other approaches to minimize ocular toxicity have included longer infusion times, so it’s “not so much of a hefty dose at one time,” Kang added.
She underlined that grade 2 and 3 ocular toxicities can lead to dose delays or dose modifications, and “usually by the time you get a grade 4 event, then you may need to discontinue the medication.”
This can have consequences for the patients because they are often “very sick, and this may be their third agent that they’re trying,” or it may be that their tumor is responding to a new treatment, but it has to be withheld because of an ocular toxicity.
“It can be incredibly frustrating for patients, and also for oncologists, and then for ophthalmologists,” Kang said.
Closer Collaboration Between Specialists Needed
What’s known about ocular side effects in patients taking ADCs underlines that there is a need for closer collaboration between oncologists and ophthalmologists.
“In oncology, especially as immunotherapies came to the forefront, our relationships with our endocrinology colleagues have become stronger because we’ve needed them to help us manage things like thyroid toxicity and pituitary issues related to immunotherapy,” Meisel said.
With toxicities that may be “very impactful for patient quality of life, like ocular toxicity, we will need to learn more about them and develop protocols for management, along with our ophthalmology colleagues, so that we can keep patients as comfortable as possible, while maximizing the efficacy of these drugs.”
Miller agreed, saying oncologists need to have “a conversation with a local ophthalmologist,” although she conceded that, in many areas, such specialists “are in short supply.”
The oncologist “not only needs to be aware” of and looking for ocular toxicity when using these ADCs but also needs to be thinking: “If I run into trouble here, who’s my ophthalmology backup? Are they familiar with this drug? And do we have a plan for the multispecialty management of patients who run into this toxicity?”
Setting Counts When Assessing Toxicities
But do all these considerations mean that ADCs’ potential ocular toxicity should give clinicians pause when considering whether to use these drugs?
“What my patients most want are drugs that work; that are effective in controlling their tumors,” Miller said.
“Every drug we use has potential toxicities, and which toxicities are most physically troublesome [or] are the greatest concern may vary from patient to patient, and it may vary a lot from patients with metastatic disease to those in the curative setting.”
She explained that “toxicities that might not be prohibitive at all in the metastatic setting [may] have to be a much bigger part of our considerations” when moving drugs into the adjuvant or neoadjuvant setting.
This, Miller underlined, is where the ocular toxicity with these ADCs “may be much more prohibitive.”
TULIP was funded by Byondis BV.
Turner declared relationships with Novartis, AstraZeneca, Pfizer, Merck Sharp & Dohme, Lilly, Repare Therapeutics, Roche, GlaxoSmithKline, Gilead Sciences, Inivata, Guardant Health, Exact Sciences, and Relay Therapeutics.
Meisel declared relationships with Novartis, AstraZeneca, Genentech, Seagen, Olema Oncology, GE Healthcare, Pfizer, Stemline, and Sermonix Pharmaceuticals.
A version of this article appeared on Medscape.com.
Such experts called for greater collaboration between oncologists and ophthalmologists, in interviews with Medscape Medical News.
ADCs combine a monoclonal antibody targeted at an antigen overexpressed on cancer cells with a toxic chemotherapy payload — the aim being to maximize the effectiveness of the drug against the tumor while minimizing the damage to healthy tissues and reducing systemic toxicity.
Yet trastuzumab duocarmazine (T-Duo), a third-generation human epidermal growth factor receptor 2 (HER2)–targeted ADC designed to treat HER2-positive breast cancer, was recently found to have a notable adverse effect in the TULIP trial of 437 patients.
As reported by Medscape Medical News, the drug was associated with a significant increase in progression-free survival over physician’s choice of therapy. However, 78% of patients in the ADC group experienced at least one treatment-emergent ocular toxicity adverse event vs 29.2% of those in the control group.
Moreover, grade 3 or high ocular toxicity events were reported by 21% of patients in the experimental group compared with none of those who received physician’s choice.
Ocular Toxicities Seen on Ocular Surface
Ocular toxicities with these drugs are “not necessarily a new thing,” said Joann J. Kang, MD, director, Cornea and Refractive Surgery, and associate professor of ophthalmology at Albert Einstein College of Medicine, Montefiore Medical Center, Bronx, New York.
“But what we’re seeing with certain ADCs is a lot of ocular toxicity, especially on the ocular surface,” with the degree toxicity varying depending on the ADC in question. “It’s definitely a real concern.”
Kang noted that separate from T-Duo, certain ADCs already come with black box warnings for ocular toxicity, including:
- Belantamab mafodotin (Blenrep) — approved for relapsed or refractory multiple myeloma and carries a warning specifically for keratopathy.
- Tisotumab vedotin (Tivdak) — indicated for recurrent or metastatic cervical cancer and can cause changes in the corneal epithelium and conjunctiva.
- Mirvetuximab soravtansine (Elahere) — used to treat folate receptor (FR) alpha–positive ovarian, fallopian tube, and peritoneal cancers and can lead to keratopathy, blurred vision, and dry eyes.
Indeed, the American Academy of Ophthalmology 2024 annual meeting saw research presented indicating that mirvetuximab was associated with moderate or severe corneal toxicity in 47% of patients treated for primary gynecologic malignancies.
As reported by Medscape Medical News, the study, by researchers at Byers Eye Institute of Stanford University in Stanford, California, was a retrospective analysis of 36 eyes of 18 women who received mirvetuximab for FR alpha–positive, platinum-resistant primary ovarian cancer.
What Are the Causes?
But why would a drug that is targeted specifically to a cancer tumor, thanks to the presence of a monoclonal antibody, cause off-target effects such as ocular toxicity?
Kathy D. Miller, MD, professor of oncology and medicine at Indiana University School of Medicine in Indianapolis, pointed out that they are targeted in a relative and not absolute sense, meaning that the antigen target may not be truly limited to the tumor cells.
There can also be “a lot of ways that you could get systemic toxicities,” she said.
For example, if the linker connecting the antibody and the chemotherapy payload breaks prematurely or is not stable, or if the drug leaches out into the tumor microenvironment and then is “picked up into the circulation, that can give you systemic toxicity,” she said.
In addition, the drug may, once it is in the tumor cells, be metabolized to an active metabolite that could, again, result in systemic exposure.
Side Effects Are Underappreciated and Distressing
Ocular toxicity remains underappreciated among oncologists prescribing these drugs. One reason is that it “did not get enough attention” in the initial clinical trial reports, Miller said she suspects.
Another potential reason for this is that “we’re not used to thinking about it because it’s not particularly common among the drugs that oncologists use frequently,” she added. Additionally, it tends to come up later during treatment, “so people have to be on therapy for some time before you start to see it.”
Nevertheless, Miller underlined that ocular toxicity “can be particularly distressing for patients, as it’s uncomfortable [and] can lead to scarring, so some of the vision issues can be permanent.”
“We often see in these situations that there are different types of ocular toxicities that present in different patients,” said Jane L. Meisel, MD, co-director, Breast Medical Oncology, Department of Hematology and Medical Oncology at Emory University School of Medicine in Atlanta.
“Corneal damage is pretty common, and patients can present with blurry vision, or dry eyes, or light sensitivity. And unlike some side effects, these are things that really impact people at every waking moment of their day.”
“So they’re pretty clinically significant side effects, even if they’re not life-threatening,” Meisel emphasized.
Miller suspects that more heavily pretreated patients may be more likely to experience ocular toxicity, as “there’s a much higher incidence of dry eyes in our patients than we recognize.”
She added: “We don’t usually ask about it, and we certainly don’t routinely do Schirmer’s tests,” which determine whether the eye produces enough tears to keep it moist.
Preventive Measures
For patients receiving tisotumab or mirvetuximab who experience ocular toxicity, Kang said the recommendation is to use steroid eye drops before, during, and after treatment with the ADC.
However, she noted that steroids have not been found to be useful in patients given belantamab, so clinicians have tried vasoconstrictor eye drops immediately prior to the infusion, as well as ocular cooling masks, which “are thought to help by reducing blood supply to the ocular areas.”
Other approaches to minimize ocular toxicity have included longer infusion times, so it’s “not so much of a hefty dose at one time,” Kang added.
She underlined that grade 2 and 3 ocular toxicities can lead to dose delays or dose modifications, and “usually by the time you get a grade 4 event, then you may need to discontinue the medication.”
This can have consequences for the patients because they are often “very sick, and this may be their third agent that they’re trying,” or it may be that their tumor is responding to a new treatment, but it has to be withheld because of an ocular toxicity.
“It can be incredibly frustrating for patients, and also for oncologists, and then for ophthalmologists,” Kang said.
Closer Collaboration Between Specialists Needed
What’s known about ocular side effects in patients taking ADCs underlines that there is a need for closer collaboration between oncologists and ophthalmologists.
“In oncology, especially as immunotherapies came to the forefront, our relationships with our endocrinology colleagues have become stronger because we’ve needed them to help us manage things like thyroid toxicity and pituitary issues related to immunotherapy,” Meisel said.
With toxicities that may be “very impactful for patient quality of life, like ocular toxicity, we will need to learn more about them and develop protocols for management, along with our ophthalmology colleagues, so that we can keep patients as comfortable as possible, while maximizing the efficacy of these drugs.”
Miller agreed, saying oncologists need to have “a conversation with a local ophthalmologist,” although she conceded that, in many areas, such specialists “are in short supply.”
The oncologist “not only needs to be aware” of and looking for ocular toxicity when using these ADCs but also needs to be thinking: “If I run into trouble here, who’s my ophthalmology backup? Are they familiar with this drug? And do we have a plan for the multispecialty management of patients who run into this toxicity?”
Setting Counts When Assessing Toxicities
But do all these considerations mean that ADCs’ potential ocular toxicity should give clinicians pause when considering whether to use these drugs?
“What my patients most want are drugs that work; that are effective in controlling their tumors,” Miller said.
“Every drug we use has potential toxicities, and which toxicities are most physically troublesome [or] are the greatest concern may vary from patient to patient, and it may vary a lot from patients with metastatic disease to those in the curative setting.”
She explained that “toxicities that might not be prohibitive at all in the metastatic setting [may] have to be a much bigger part of our considerations” when moving drugs into the adjuvant or neoadjuvant setting.
This, Miller underlined, is where the ocular toxicity with these ADCs “may be much more prohibitive.”
TULIP was funded by Byondis BV.
Turner declared relationships with Novartis, AstraZeneca, Pfizer, Merck Sharp & Dohme, Lilly, Repare Therapeutics, Roche, GlaxoSmithKline, Gilead Sciences, Inivata, Guardant Health, Exact Sciences, and Relay Therapeutics.
Meisel declared relationships with Novartis, AstraZeneca, Genentech, Seagen, Olema Oncology, GE Healthcare, Pfizer, Stemline, and Sermonix Pharmaceuticals.
A version of this article appeared on Medscape.com.
Health Impacts of Micro- and Nanoplastics
In preparation for a future international treaty aimed at reducing plastic pollution, the French Parliamentary Office for the Evaluation of Scientific and Technological Choices presented the conclusions of a public hearing on the impact of plastics on various aspects of human health.
Increased Global Plastic Production
Philippe Bolo, a member of the French Democratic Party and the rapporteur for the public mission on the health impacts of plastics, spoke about the latest round of treaty negotiations, held from November 25 to December 1 in South Korea, attended by leading French and global experts about the impact of plastics on human health.
The hearing highlighted a sharp increase in plastic production. “It has doubled in the last 20 years and is expected to exceed 500 million tons in 2024,” Bolo said. This is about 60 kg per person. According to projections from the Organization for Economic Co-operation and Development, on its current trajectory, plastic production will reach 750 million tons by 2040 and surpass 1 billion tons before 2050, he said.
Minimal Plastic Waste Recycling
Around one third (32%) of plastics are used for packaging. “Therefore, most plastic production is still intended for single-use purposes,” he said. Plastic waste follows a similar growth trajectory, with volumes expected to rise from 360 million tons in 2020 to 617 million tons by 2040 unless action is taken. Very little of this waste is recycled, even in the most countries that are most advanced in terms of collection, sorting, and processing.
In France, for example, in 2018, only 0.6 million tons of the 3.6 million tons of plastic waste produced was truly recycled. This is less than one fifth (17%). Globally, less than 10% of plastic waste is recycled. In 2020, plastic waste that ended up in the environment represented 81 million tons, or 22% of the total. “Beyond waste, this leads to pollution by microplastics and nanoplastics, resulting from their fragmentation. All environments are affected: Seas, rivers, soils, air, and even living organisms,” Bolo said.
Methodological Challenges
However, measuring the impact of plastics on health faces methodological difficulties due to the wide variety of composition, size, and shape of plastics. Nevertheless, the French Standardization Association (Association Française de Normalisation) has conducted work to establish a characterization standard for microplastics in water, which serves as an international reference.
“It is also very difficult to know what we are ingesting,” Bolo said. “A study conducted in 2019 estimated that the average human absorbs 5 grams of plastics per week, the equivalent of a credit card.» Since then, other studies have revised this estimate downward, but no consensus has been reached.
A recent study across 109 countries, both industrialized and developing, found significant exposure, estimated at 500 mg/d, particularly in Southeast Asian countries, where it was due mainly to seafood consumption.
A study concluded that plastic water bottles contain 240,000 particles per liter, 90% of which are nanoplastics. These nanoparticles can pass through the intestinal barrier to enter the bloodstream and reach several organs including the heart, brain, and placenta, as well as the fetus.
Changes to the Microbiome
Microplastics also accumulate in organs. Thus, the amount of plastic in the lungs increases with age, suggesting that particles may persist in the body without being eliminated. The health consequences of this are still poorly understood, but exposure to plastics appears to cause changes in the composition of the intestinal microbiota. Pathobionts (commensal bacteria with harmful potential) have been found in both adults and children, which could contribute to dysbiosis of the gut microbiome. Furthermore, a decrease in butyrate, a short-chain fatty acid beneficial to health, has been observed in children’s intestines.
Inhaled nanoplastics may disrupt the mucociliary clearance mechanisms of the respiratory system. The toxicity of inhaled plastic particles was demonstrated as early as the 1970s among workers in the flocking industry. Some developed lung function impairments, shortness of breath, inflammation, fibrosis, and even lung cancer. Similar symptoms have been observed in workers in the textile and polyvinyl chloride industries.
A study published recently in The New England Journal of Medicine measured the amount of microplastics collected from carotid plaque of more than 300 patients who had undergone carotid endarterectomy for asymptomatic carotid artery disease. It found a 4.53 times higher risk for the primary endpoint, a composite of myocardial infarction, stroke, and all-cause mortality, among individuals with microplastics and nanoplastics in plaque compared with those without.
Health Affects High
The danger of plastics is also directly linked to the chemical substances they contain. A general scientific review looked at the health impacts of three chemicals used almost exclusively in plastics: Polybromodiphenyl ethers (PBDEs), used as flame retardants in textiles or electronics; bisphenol A (BPA), used in the lining of cans and bottles; and phthalates, particularly diethylhexyl phthalate (DEHP), used to make plastics more flexible.
The review highlighted strong epidemiological evidence linking fetal exposure to PBDEs during pregnancy to low birth weight and later exposure to delayed or impaired cognitive development in children and even a loss of IQ. Statistically significant evidence of disruption of thyroid function in adults was also found.
BPA is linked to genital malformations in female newborns exposed to BPA in utero, type 2 diabetes in adults, insulin resistance, and polycystic ovary syndrome in women. BPA exposure also increases the risk for obesity and hypertension in both children and adults, as well as the risk for cardiovascular disease in adults.
Finally, the review established links between exposure to DEHP and miscarriages, genital malformations in male newborns, delayed or impaired cognitive development in children, loss of IQ, delayed psychomotor development, early puberty in young girls, and endometriosis in young women. DEHP exposure also has multiple effects on cardiometabolic health, including insulin resistance, obesity, and elevated blood pressure.
The economic costs associated with the health impacts of these three substances have been estimated at $675 billion in the United States.
Bolo said that the solution to this plastic pollution is necessarily international. “We need an ambitious and legally binding treaty to reduce plastic production,” he said. “The damage is already done; we need to act to protect human health,” he concluded. The parliamentary office has made nine recommendations to the treaty negotiators.
This story was translated from Medscape’s French edition using several editorial tools, including AI, as part of the process. Human editors reviewed this content before publication. A version of this article appeared on Medscape.com.
In preparation for a future international treaty aimed at reducing plastic pollution, the French Parliamentary Office for the Evaluation of Scientific and Technological Choices presented the conclusions of a public hearing on the impact of plastics on various aspects of human health.
Increased Global Plastic Production
Philippe Bolo, a member of the French Democratic Party and the rapporteur for the public mission on the health impacts of plastics, spoke about the latest round of treaty negotiations, held from November 25 to December 1 in South Korea, attended by leading French and global experts about the impact of plastics on human health.
The hearing highlighted a sharp increase in plastic production. “It has doubled in the last 20 years and is expected to exceed 500 million tons in 2024,” Bolo said. This is about 60 kg per person. According to projections from the Organization for Economic Co-operation and Development, on its current trajectory, plastic production will reach 750 million tons by 2040 and surpass 1 billion tons before 2050, he said.
Minimal Plastic Waste Recycling
Around one third (32%) of plastics are used for packaging. “Therefore, most plastic production is still intended for single-use purposes,” he said. Plastic waste follows a similar growth trajectory, with volumes expected to rise from 360 million tons in 2020 to 617 million tons by 2040 unless action is taken. Very little of this waste is recycled, even in the most countries that are most advanced in terms of collection, sorting, and processing.
In France, for example, in 2018, only 0.6 million tons of the 3.6 million tons of plastic waste produced was truly recycled. This is less than one fifth (17%). Globally, less than 10% of plastic waste is recycled. In 2020, plastic waste that ended up in the environment represented 81 million tons, or 22% of the total. “Beyond waste, this leads to pollution by microplastics and nanoplastics, resulting from their fragmentation. All environments are affected: Seas, rivers, soils, air, and even living organisms,” Bolo said.
Methodological Challenges
However, measuring the impact of plastics on health faces methodological difficulties due to the wide variety of composition, size, and shape of plastics. Nevertheless, the French Standardization Association (Association Française de Normalisation) has conducted work to establish a characterization standard for microplastics in water, which serves as an international reference.
“It is also very difficult to know what we are ingesting,” Bolo said. “A study conducted in 2019 estimated that the average human absorbs 5 grams of plastics per week, the equivalent of a credit card.» Since then, other studies have revised this estimate downward, but no consensus has been reached.
A recent study across 109 countries, both industrialized and developing, found significant exposure, estimated at 500 mg/d, particularly in Southeast Asian countries, where it was due mainly to seafood consumption.
A study concluded that plastic water bottles contain 240,000 particles per liter, 90% of which are nanoplastics. These nanoparticles can pass through the intestinal barrier to enter the bloodstream and reach several organs including the heart, brain, and placenta, as well as the fetus.
Changes to the Microbiome
Microplastics also accumulate in organs. Thus, the amount of plastic in the lungs increases with age, suggesting that particles may persist in the body without being eliminated. The health consequences of this are still poorly understood, but exposure to plastics appears to cause changes in the composition of the intestinal microbiota. Pathobionts (commensal bacteria with harmful potential) have been found in both adults and children, which could contribute to dysbiosis of the gut microbiome. Furthermore, a decrease in butyrate, a short-chain fatty acid beneficial to health, has been observed in children’s intestines.
Inhaled nanoplastics may disrupt the mucociliary clearance mechanisms of the respiratory system. The toxicity of inhaled plastic particles was demonstrated as early as the 1970s among workers in the flocking industry. Some developed lung function impairments, shortness of breath, inflammation, fibrosis, and even lung cancer. Similar symptoms have been observed in workers in the textile and polyvinyl chloride industries.
A study published recently in The New England Journal of Medicine measured the amount of microplastics collected from carotid plaque of more than 300 patients who had undergone carotid endarterectomy for asymptomatic carotid artery disease. It found a 4.53 times higher risk for the primary endpoint, a composite of myocardial infarction, stroke, and all-cause mortality, among individuals with microplastics and nanoplastics in plaque compared with those without.
Health Affects High
The danger of plastics is also directly linked to the chemical substances they contain. A general scientific review looked at the health impacts of three chemicals used almost exclusively in plastics: Polybromodiphenyl ethers (PBDEs), used as flame retardants in textiles or electronics; bisphenol A (BPA), used in the lining of cans and bottles; and phthalates, particularly diethylhexyl phthalate (DEHP), used to make plastics more flexible.
The review highlighted strong epidemiological evidence linking fetal exposure to PBDEs during pregnancy to low birth weight and later exposure to delayed or impaired cognitive development in children and even a loss of IQ. Statistically significant evidence of disruption of thyroid function in adults was also found.
BPA is linked to genital malformations in female newborns exposed to BPA in utero, type 2 diabetes in adults, insulin resistance, and polycystic ovary syndrome in women. BPA exposure also increases the risk for obesity and hypertension in both children and adults, as well as the risk for cardiovascular disease in adults.
Finally, the review established links between exposure to DEHP and miscarriages, genital malformations in male newborns, delayed or impaired cognitive development in children, loss of IQ, delayed psychomotor development, early puberty in young girls, and endometriosis in young women. DEHP exposure also has multiple effects on cardiometabolic health, including insulin resistance, obesity, and elevated blood pressure.
The economic costs associated with the health impacts of these three substances have been estimated at $675 billion in the United States.
Bolo said that the solution to this plastic pollution is necessarily international. “We need an ambitious and legally binding treaty to reduce plastic production,” he said. “The damage is already done; we need to act to protect human health,” he concluded. The parliamentary office has made nine recommendations to the treaty negotiators.
This story was translated from Medscape’s French edition using several editorial tools, including AI, as part of the process. Human editors reviewed this content before publication. A version of this article appeared on Medscape.com.
In preparation for a future international treaty aimed at reducing plastic pollution, the French Parliamentary Office for the Evaluation of Scientific and Technological Choices presented the conclusions of a public hearing on the impact of plastics on various aspects of human health.
Increased Global Plastic Production
Philippe Bolo, a member of the French Democratic Party and the rapporteur for the public mission on the health impacts of plastics, spoke about the latest round of treaty negotiations, held from November 25 to December 1 in South Korea, attended by leading French and global experts about the impact of plastics on human health.
The hearing highlighted a sharp increase in plastic production. “It has doubled in the last 20 years and is expected to exceed 500 million tons in 2024,” Bolo said. This is about 60 kg per person. According to projections from the Organization for Economic Co-operation and Development, on its current trajectory, plastic production will reach 750 million tons by 2040 and surpass 1 billion tons before 2050, he said.
Minimal Plastic Waste Recycling
Around one third (32%) of plastics are used for packaging. “Therefore, most plastic production is still intended for single-use purposes,” he said. Plastic waste follows a similar growth trajectory, with volumes expected to rise from 360 million tons in 2020 to 617 million tons by 2040 unless action is taken. Very little of this waste is recycled, even in the most countries that are most advanced in terms of collection, sorting, and processing.
In France, for example, in 2018, only 0.6 million tons of the 3.6 million tons of plastic waste produced was truly recycled. This is less than one fifth (17%). Globally, less than 10% of plastic waste is recycled. In 2020, plastic waste that ended up in the environment represented 81 million tons, or 22% of the total. “Beyond waste, this leads to pollution by microplastics and nanoplastics, resulting from their fragmentation. All environments are affected: Seas, rivers, soils, air, and even living organisms,” Bolo said.
Methodological Challenges
However, measuring the impact of plastics on health faces methodological difficulties due to the wide variety of composition, size, and shape of plastics. Nevertheless, the French Standardization Association (Association Française de Normalisation) has conducted work to establish a characterization standard for microplastics in water, which serves as an international reference.
“It is also very difficult to know what we are ingesting,” Bolo said. “A study conducted in 2019 estimated that the average human absorbs 5 grams of plastics per week, the equivalent of a credit card.» Since then, other studies have revised this estimate downward, but no consensus has been reached.
A recent study across 109 countries, both industrialized and developing, found significant exposure, estimated at 500 mg/d, particularly in Southeast Asian countries, where it was due mainly to seafood consumption.
A study concluded that plastic water bottles contain 240,000 particles per liter, 90% of which are nanoplastics. These nanoparticles can pass through the intestinal barrier to enter the bloodstream and reach several organs including the heart, brain, and placenta, as well as the fetus.
Changes to the Microbiome
Microplastics also accumulate in organs. Thus, the amount of plastic in the lungs increases with age, suggesting that particles may persist in the body without being eliminated. The health consequences of this are still poorly understood, but exposure to plastics appears to cause changes in the composition of the intestinal microbiota. Pathobionts (commensal bacteria with harmful potential) have been found in both adults and children, which could contribute to dysbiosis of the gut microbiome. Furthermore, a decrease in butyrate, a short-chain fatty acid beneficial to health, has been observed in children’s intestines.
Inhaled nanoplastics may disrupt the mucociliary clearance mechanisms of the respiratory system. The toxicity of inhaled plastic particles was demonstrated as early as the 1970s among workers in the flocking industry. Some developed lung function impairments, shortness of breath, inflammation, fibrosis, and even lung cancer. Similar symptoms have been observed in workers in the textile and polyvinyl chloride industries.
A study published recently in The New England Journal of Medicine measured the amount of microplastics collected from carotid plaque of more than 300 patients who had undergone carotid endarterectomy for asymptomatic carotid artery disease. It found a 4.53 times higher risk for the primary endpoint, a composite of myocardial infarction, stroke, and all-cause mortality, among individuals with microplastics and nanoplastics in plaque compared with those without.
Health Affects High
The danger of plastics is also directly linked to the chemical substances they contain. A general scientific review looked at the health impacts of three chemicals used almost exclusively in plastics: Polybromodiphenyl ethers (PBDEs), used as flame retardants in textiles or electronics; bisphenol A (BPA), used in the lining of cans and bottles; and phthalates, particularly diethylhexyl phthalate (DEHP), used to make plastics more flexible.
The review highlighted strong epidemiological evidence linking fetal exposure to PBDEs during pregnancy to low birth weight and later exposure to delayed or impaired cognitive development in children and even a loss of IQ. Statistically significant evidence of disruption of thyroid function in adults was also found.
BPA is linked to genital malformations in female newborns exposed to BPA in utero, type 2 diabetes in adults, insulin resistance, and polycystic ovary syndrome in women. BPA exposure also increases the risk for obesity and hypertension in both children and adults, as well as the risk for cardiovascular disease in adults.
Finally, the review established links between exposure to DEHP and miscarriages, genital malformations in male newborns, delayed or impaired cognitive development in children, loss of IQ, delayed psychomotor development, early puberty in young girls, and endometriosis in young women. DEHP exposure also has multiple effects on cardiometabolic health, including insulin resistance, obesity, and elevated blood pressure.
The economic costs associated with the health impacts of these three substances have been estimated at $675 billion in the United States.
Bolo said that the solution to this plastic pollution is necessarily international. “We need an ambitious and legally binding treaty to reduce plastic production,” he said. “The damage is already done; we need to act to protect human health,” he concluded. The parliamentary office has made nine recommendations to the treaty negotiators.
This story was translated from Medscape’s French edition using several editorial tools, including AI, as part of the process. Human editors reviewed this content before publication. A version of this article appeared on Medscape.com.
Camrelizumab Plus Chemotherapy Boosts Response in Triple-Negative Breast Cancer
TOPLINE:
The combination shows consistent benefits across patient subgroups with a manageable safety profile.
METHODOLOGY:
- A randomized, double-blind, phase 3 trial enrolled 441 females (median age, 48 years) with early or locally advanced triple-negative breast cancer from 40 hospitals in China between November 2020 and May 2023.
- Participants were randomized 1:1 to receive either camrelizumab 200 mg (n = 222) or placebo (n = 219) combined with chemotherapy every 2 weeks, with median follow-up period of 14.4 months.
- Treatment included nab-paclitaxel (100 mg/m²) plus carboplatin (area under curve, 1.5) on days 1, 8, and 15 in 28-day cycles for 16 weeks, followed by epirubicin (90 mg/m²) and cyclophosphamide (500 mg/m²) every 2 weeks for 8 weeks.
- The primary endpoint was pathological complete response, defined as no invasive tumor in breast and lymph nodes.
TAKEAWAY:
- Pathological complete response was achieved in 56.8% (95% CI, 50.0%-63.4%) of patients in the camrelizumab-chemotherapy group vs 44.7% (95% CI, 38.0%-51.6%) in the placebo-chemotherapy group (rate difference, 12.2%; 95% CI, 3.3%-21.2%; P = .004).
- Grade 3 or higher adverse events occurred in 89.2% of camrelizumab-chemotherapy group vs 83.1% in placebo-chemotherapy group, with serious adverse events in 34.7% vs 22.8%, respectively.
- Event-free survival rate at 18 months was 86.6% (95% CI, 79.9%-91.1%) with camrelizumab-chemotherapy vs 83.6% (95% CI, 76.2%-88.9%) with placebo-chemotherapy (hazard ratio [HR], 0.80; 95% CI, 0.46-1.42).
- Disease-free survival rate at 12 months reached 91.9% (95% CI, 85.5%-95.5%) with camrelizumab-chemotherapy compared with 87.8% (95% CI, 80.3%-92.6%) with placebo-chemotherapy (HR, 0.58; 95% CI, 0.27-1.24).
IN PRACTICE:
“The addition of camrelizumab to neoadjuvant chemotherapy significantly improved pathological complete response... The benefits of camrelizumab-chemotherapy with respect to pCR were generally consistent across subgroups,” wrote the authors of the study.
SOURCE:
The study was led by Zhi-Ming Shao, MD, Fudan University Shanghai Cancer Center in Shanghai, China. It was published online on December 13 in JAMA.
LIMITATIONS:
According to the authors, the study’s limitations include short follow-up duration preventing assessment of mature survival data and long-term safety profile, uncertainty about optimal duration of adjuvant camrelizumab treatment, small sample sizes in some subgroups warranting cautious interpretation, and potential limited generalizability as the study was conducted only in Chinese patients with triple-negative breast cancer.
DISCLOSURES:
The study was supported by Jiangsu Hengrui Pharmaceuticals. The authors and funder were involved in data collection, analysis, and interpretation and guaranteed the accuracy, completeness of the data, writing of the report, and the decision to submit the manuscript for publication.
This article was created using several editorial tools, including AI, as part of the process. Human editors reviewed this content before publication. A version of this article first appeared on Medscape.com.
TOPLINE:
The combination shows consistent benefits across patient subgroups with a manageable safety profile.
METHODOLOGY:
- A randomized, double-blind, phase 3 trial enrolled 441 females (median age, 48 years) with early or locally advanced triple-negative breast cancer from 40 hospitals in China between November 2020 and May 2023.
- Participants were randomized 1:1 to receive either camrelizumab 200 mg (n = 222) or placebo (n = 219) combined with chemotherapy every 2 weeks, with median follow-up period of 14.4 months.
- Treatment included nab-paclitaxel (100 mg/m²) plus carboplatin (area under curve, 1.5) on days 1, 8, and 15 in 28-day cycles for 16 weeks, followed by epirubicin (90 mg/m²) and cyclophosphamide (500 mg/m²) every 2 weeks for 8 weeks.
- The primary endpoint was pathological complete response, defined as no invasive tumor in breast and lymph nodes.
TAKEAWAY:
- Pathological complete response was achieved in 56.8% (95% CI, 50.0%-63.4%) of patients in the camrelizumab-chemotherapy group vs 44.7% (95% CI, 38.0%-51.6%) in the placebo-chemotherapy group (rate difference, 12.2%; 95% CI, 3.3%-21.2%; P = .004).
- Grade 3 or higher adverse events occurred in 89.2% of camrelizumab-chemotherapy group vs 83.1% in placebo-chemotherapy group, with serious adverse events in 34.7% vs 22.8%, respectively.
- Event-free survival rate at 18 months was 86.6% (95% CI, 79.9%-91.1%) with camrelizumab-chemotherapy vs 83.6% (95% CI, 76.2%-88.9%) with placebo-chemotherapy (hazard ratio [HR], 0.80; 95% CI, 0.46-1.42).
- Disease-free survival rate at 12 months reached 91.9% (95% CI, 85.5%-95.5%) with camrelizumab-chemotherapy compared with 87.8% (95% CI, 80.3%-92.6%) with placebo-chemotherapy (HR, 0.58; 95% CI, 0.27-1.24).
IN PRACTICE:
“The addition of camrelizumab to neoadjuvant chemotherapy significantly improved pathological complete response... The benefits of camrelizumab-chemotherapy with respect to pCR were generally consistent across subgroups,” wrote the authors of the study.
SOURCE:
The study was led by Zhi-Ming Shao, MD, Fudan University Shanghai Cancer Center in Shanghai, China. It was published online on December 13 in JAMA.
LIMITATIONS:
According to the authors, the study’s limitations include short follow-up duration preventing assessment of mature survival data and long-term safety profile, uncertainty about optimal duration of adjuvant camrelizumab treatment, small sample sizes in some subgroups warranting cautious interpretation, and potential limited generalizability as the study was conducted only in Chinese patients with triple-negative breast cancer.
DISCLOSURES:
The study was supported by Jiangsu Hengrui Pharmaceuticals. The authors and funder were involved in data collection, analysis, and interpretation and guaranteed the accuracy, completeness of the data, writing of the report, and the decision to submit the manuscript for publication.
This article was created using several editorial tools, including AI, as part of the process. Human editors reviewed this content before publication. A version of this article first appeared on Medscape.com.
TOPLINE:
The combination shows consistent benefits across patient subgroups with a manageable safety profile.
METHODOLOGY:
- A randomized, double-blind, phase 3 trial enrolled 441 females (median age, 48 years) with early or locally advanced triple-negative breast cancer from 40 hospitals in China between November 2020 and May 2023.
- Participants were randomized 1:1 to receive either camrelizumab 200 mg (n = 222) or placebo (n = 219) combined with chemotherapy every 2 weeks, with median follow-up period of 14.4 months.
- Treatment included nab-paclitaxel (100 mg/m²) plus carboplatin (area under curve, 1.5) on days 1, 8, and 15 in 28-day cycles for 16 weeks, followed by epirubicin (90 mg/m²) and cyclophosphamide (500 mg/m²) every 2 weeks for 8 weeks.
- The primary endpoint was pathological complete response, defined as no invasive tumor in breast and lymph nodes.
TAKEAWAY:
- Pathological complete response was achieved in 56.8% (95% CI, 50.0%-63.4%) of patients in the camrelizumab-chemotherapy group vs 44.7% (95% CI, 38.0%-51.6%) in the placebo-chemotherapy group (rate difference, 12.2%; 95% CI, 3.3%-21.2%; P = .004).
- Grade 3 or higher adverse events occurred in 89.2% of camrelizumab-chemotherapy group vs 83.1% in placebo-chemotherapy group, with serious adverse events in 34.7% vs 22.8%, respectively.
- Event-free survival rate at 18 months was 86.6% (95% CI, 79.9%-91.1%) with camrelizumab-chemotherapy vs 83.6% (95% CI, 76.2%-88.9%) with placebo-chemotherapy (hazard ratio [HR], 0.80; 95% CI, 0.46-1.42).
- Disease-free survival rate at 12 months reached 91.9% (95% CI, 85.5%-95.5%) with camrelizumab-chemotherapy compared with 87.8% (95% CI, 80.3%-92.6%) with placebo-chemotherapy (HR, 0.58; 95% CI, 0.27-1.24).
IN PRACTICE:
“The addition of camrelizumab to neoadjuvant chemotherapy significantly improved pathological complete response... The benefits of camrelizumab-chemotherapy with respect to pCR were generally consistent across subgroups,” wrote the authors of the study.
SOURCE:
The study was led by Zhi-Ming Shao, MD, Fudan University Shanghai Cancer Center in Shanghai, China. It was published online on December 13 in JAMA.
LIMITATIONS:
According to the authors, the study’s limitations include short follow-up duration preventing assessment of mature survival data and long-term safety profile, uncertainty about optimal duration of adjuvant camrelizumab treatment, small sample sizes in some subgroups warranting cautious interpretation, and potential limited generalizability as the study was conducted only in Chinese patients with triple-negative breast cancer.
DISCLOSURES:
The study was supported by Jiangsu Hengrui Pharmaceuticals. The authors and funder were involved in data collection, analysis, and interpretation and guaranteed the accuracy, completeness of the data, writing of the report, and the decision to submit the manuscript for publication.
This article was created using several editorial tools, including AI, as part of the process. Human editors reviewed this content before publication. A version of this article first appeared on Medscape.com.