User login
New approach to breast screening based on breast density at 40
The result would then be used to stratify further screening, with annual screening starting at age 40 for average-risk women who have dense breasts, and screening every 2 years starting at age 50 for women without dense breasts.
Such an approach would be cost effective and offers a more targeted risk-based strategy for the early detection of breast cancer when compared with current practices, say the authors, led by Tina Shih, PhD, University of Texas MD Anderson Cancer Center, Houston.
Their modeling study was published online in the Annals of Internal Medicine.
However, experts writing in an accompanying editorial are not persuaded. Karla Kerlikowske, MD, and Kirsten Bibbins-Domingo, MD, PhD, both from the University of California, San Francisco, point out that not all women with dense breasts are at increased risk for breast cancer. They caution against relying on breast density alone when determining screening strategies, and say age and other risk factors also need to be considered.
New approach proposed
Current recommendations from the United States Preventive Services Task Force suggest that women in their 40s can choose to undergo screening mammography based on their own personal preference, Dr. Shih explained in an interview.
However, these recommendations do not take into consideration the additional risk that breast density confers on breast cancer risk – and the only way women can know their breast density is to have a mammogram. “If you follow [current] guidelines, you would not know about your breast density until the age of 45 or 50,” she commented.
“But what if you knew about breast density earlier on and then acted on it –would that make a difference?” This was the question her team set out to explore.
For their study, the authors defined women with dense breasts as those with the Breast Imaging Reporting and Data System (BI-RADS) category C (heterogeneously dense breasts) and category D (extremely dense breasts).
The team used a computer model to compare seven different breast screening strategies:
- No screening.
- Triennial mammography from age 50 to 75 years (T50).
- Biennial mammography from age 50 to 75 years (B50).
- Stratified annual mammography from age 50 to 75 for women with dense breasts at age 50, and triennial. screening from age 50 to 75 for women without dense breasts at the age of 50 (SA50T50).
- Stratified annual mammography from age 50 to 75 for women with dense breasts at age 50, and biennial screening from age 50 to 75 for those without dense breast at age 50 (SA50B50).
- Stratified annual mammography from age 40 to 75 for women with dense breasts at age 49, and triennial screening from age 50 to 75 for those without dense breasts at age 40 (SA40T50).
- Stratified annual mammography from age 40 to 75 for women with dense breasts at age 40, and biennial mammography for women from age 50 to 75 without dense breasts at age 40 (SA40B50).
Compared with a no-screening strategy, the average number of mammography sessions through a woman’s lifetime would increase from seven mammograms per lifetime for the least frequent screening (T50) to 22 mammograms per lifetime for the most intensive screening schedule, the team reports.
Compared with no screening, screening would reduce breast cancer deaths by 8.6 per 1,000 women (T50)–13.2 per 1,000 women (SA40B50).
A cost-effectiveness analysis showed that the proposed new approach (SA40B50) yielded an incremental cost-effectiveness ratio of $36,200 per quality-adjusted life-year (QALY), compared with the currently recommended biennial screening strategy. This is well within the willingness-to-pay threshold of $100,000 per QALY that is generally accepted by society, the authors point out.
On the other hand, false-positive results and overdiagnosis would increase, the authors note.
The average number of false positives would increase from 141.2 per 1,000 women who underwent the least frequent triennial mammography screening schedule (T50) to 567.3 per 1,000 women with the new approach (SA40B50).
Rates of overdiagnosis would also increase from a low of 12.5% to a high of 18.6%, they add.
“With this study, we are not saying that everybody should start screening at the age of 40. We’re just saying, do a baseline mammography at 40, know your breast density status, and then we can try to modify the screening schedule based on individual risk,” Dr. Shih emphasized.
“Compared with other screening strategies examined in our study, this strategy is associated with the greatest reduction in breast cancer mortality and is cost effective, [although it] involves the most screening mammograms in a woman’s lifetime and higher rates of false-positive results and overdiagnosis,” the authors conclude.
Fundamental problem with this approach
The fundamental problem with this approach of stratifying risk on measurement of breast density – and on the basis of a single reading – is that not every woman with dense breasts is at increased risk for breast cancer, the editorialists comment.
Dr. Kerlikowske and Dr. Bibbins-Domingo point out that, in fact, only about one-quarter of women with dense breasts are at high risk for a missed invasive cancer within 1 year of a negative mammogram, and these women can be identified by using the Breast Cancer Surveillance Consortium risk model.
“This observation means that most women with dense breasts can undergo biennial screening and need not consider annual screening or supplemental imaging,” the editorialists write.
“Thus, we caution against using breast density alone to determine if a woman is at elevated risk for breast cancer,” they emphasize.
An alternative option is to focus on overall risk to select screening strategies, they suggest. For example, most guidelines recommend screening from age 50 to 74, so identifying women in their 40s who have the same risk of a woman aged 50-59 is one way to determine who may benefit from earlier initiation of screening, the editorialists observe.
“Thus, women who have a first-degree relative with breast cancer or a history of breast biopsy could be offered screening in their 40s, and, if mammography shows dense breasts, they could continue biennial screening through their 40s,” the editorialists observe. “Such women with nondense breasts could resume biennial screening at age 50 years.”
Dr. Shih told this news organization that she did not disagree with the editorialists’ suggestion that physicians could focus on overall breast cancer risk to select an appropriate screening strategy for individual patients.
“What we are suggesting is, ‘Let’s just do a baseline assessment at the age of 40 so women know their breast density instead of waiting until they are older,’ “ she said.
“But what the editorialists are suggesting is a strategy that could be even more cost effective,” she acknowledged. Dr. Shih also said that Dr. Kerlikowske and Dr. Bibbins-Domingo’s estimate that only one-quarter of women with dense breasts are actually at high risk for breast cancer likely reflects their limitation of breast density to only those women with BI-RADs category “D” – extremely dense breasts.
Yet as Dr. Shih notes, women with category C and category D breast densities are both at higher risk for breast cancer, so ignoring women with lesser degrees of breast density still doesn’t address the fact that they have a higher-than-average risk for breast cancer.
“It’s getting harder to make universal screening strategies work as we are learning more and more about breast cancer, so people are starting to talk about screening strategies based on a patient’s risk classification,” Dr. Shih noted.
“It’ll be harder to implement these kinds of strategies, but it seems like the right way to go,” she added.
The study was funded by the National Cancer Institute. Dr. Shih reports grants from the National Cancer Institute during the conduct of the study and personal fees from Pfizer and AstraZeneca outside the submitted work. Dr. Kerlikowske is an unpaid consultant for GRAIL for the STRIVE study. Dr. Bibbins-Domingo has disclosed no relevant financial relationships.
A version of this article first appeared on Medscape.com.
The result would then be used to stratify further screening, with annual screening starting at age 40 for average-risk women who have dense breasts, and screening every 2 years starting at age 50 for women without dense breasts.
Such an approach would be cost effective and offers a more targeted risk-based strategy for the early detection of breast cancer when compared with current practices, say the authors, led by Tina Shih, PhD, University of Texas MD Anderson Cancer Center, Houston.
Their modeling study was published online in the Annals of Internal Medicine.
However, experts writing in an accompanying editorial are not persuaded. Karla Kerlikowske, MD, and Kirsten Bibbins-Domingo, MD, PhD, both from the University of California, San Francisco, point out that not all women with dense breasts are at increased risk for breast cancer. They caution against relying on breast density alone when determining screening strategies, and say age and other risk factors also need to be considered.
New approach proposed
Current recommendations from the United States Preventive Services Task Force suggest that women in their 40s can choose to undergo screening mammography based on their own personal preference, Dr. Shih explained in an interview.
However, these recommendations do not take into consideration the additional risk that breast density confers on breast cancer risk – and the only way women can know their breast density is to have a mammogram. “If you follow [current] guidelines, you would not know about your breast density until the age of 45 or 50,” she commented.
“But what if you knew about breast density earlier on and then acted on it –would that make a difference?” This was the question her team set out to explore.
For their study, the authors defined women with dense breasts as those with the Breast Imaging Reporting and Data System (BI-RADS) category C (heterogeneously dense breasts) and category D (extremely dense breasts).
The team used a computer model to compare seven different breast screening strategies:
- No screening.
- Triennial mammography from age 50 to 75 years (T50).
- Biennial mammography from age 50 to 75 years (B50).
- Stratified annual mammography from age 50 to 75 for women with dense breasts at age 50, and triennial. screening from age 50 to 75 for women without dense breasts at the age of 50 (SA50T50).
- Stratified annual mammography from age 50 to 75 for women with dense breasts at age 50, and biennial screening from age 50 to 75 for those without dense breast at age 50 (SA50B50).
- Stratified annual mammography from age 40 to 75 for women with dense breasts at age 49, and triennial screening from age 50 to 75 for those without dense breasts at age 40 (SA40T50).
- Stratified annual mammography from age 40 to 75 for women with dense breasts at age 40, and biennial mammography for women from age 50 to 75 without dense breasts at age 40 (SA40B50).
Compared with a no-screening strategy, the average number of mammography sessions through a woman’s lifetime would increase from seven mammograms per lifetime for the least frequent screening (T50) to 22 mammograms per lifetime for the most intensive screening schedule, the team reports.
Compared with no screening, screening would reduce breast cancer deaths by 8.6 per 1,000 women (T50)–13.2 per 1,000 women (SA40B50).
A cost-effectiveness analysis showed that the proposed new approach (SA40B50) yielded an incremental cost-effectiveness ratio of $36,200 per quality-adjusted life-year (QALY), compared with the currently recommended biennial screening strategy. This is well within the willingness-to-pay threshold of $100,000 per QALY that is generally accepted by society, the authors point out.
On the other hand, false-positive results and overdiagnosis would increase, the authors note.
The average number of false positives would increase from 141.2 per 1,000 women who underwent the least frequent triennial mammography screening schedule (T50) to 567.3 per 1,000 women with the new approach (SA40B50).
Rates of overdiagnosis would also increase from a low of 12.5% to a high of 18.6%, they add.
“With this study, we are not saying that everybody should start screening at the age of 40. We’re just saying, do a baseline mammography at 40, know your breast density status, and then we can try to modify the screening schedule based on individual risk,” Dr. Shih emphasized.
“Compared with other screening strategies examined in our study, this strategy is associated with the greatest reduction in breast cancer mortality and is cost effective, [although it] involves the most screening mammograms in a woman’s lifetime and higher rates of false-positive results and overdiagnosis,” the authors conclude.
Fundamental problem with this approach
The fundamental problem with this approach of stratifying risk on measurement of breast density – and on the basis of a single reading – is that not every woman with dense breasts is at increased risk for breast cancer, the editorialists comment.
Dr. Kerlikowske and Dr. Bibbins-Domingo point out that, in fact, only about one-quarter of women with dense breasts are at high risk for a missed invasive cancer within 1 year of a negative mammogram, and these women can be identified by using the Breast Cancer Surveillance Consortium risk model.
“This observation means that most women with dense breasts can undergo biennial screening and need not consider annual screening or supplemental imaging,” the editorialists write.
“Thus, we caution against using breast density alone to determine if a woman is at elevated risk for breast cancer,” they emphasize.
An alternative option is to focus on overall risk to select screening strategies, they suggest. For example, most guidelines recommend screening from age 50 to 74, so identifying women in their 40s who have the same risk of a woman aged 50-59 is one way to determine who may benefit from earlier initiation of screening, the editorialists observe.
“Thus, women who have a first-degree relative with breast cancer or a history of breast biopsy could be offered screening in their 40s, and, if mammography shows dense breasts, they could continue biennial screening through their 40s,” the editorialists observe. “Such women with nondense breasts could resume biennial screening at age 50 years.”
Dr. Shih told this news organization that she did not disagree with the editorialists’ suggestion that physicians could focus on overall breast cancer risk to select an appropriate screening strategy for individual patients.
“What we are suggesting is, ‘Let’s just do a baseline assessment at the age of 40 so women know their breast density instead of waiting until they are older,’ “ she said.
“But what the editorialists are suggesting is a strategy that could be even more cost effective,” she acknowledged. Dr. Shih also said that Dr. Kerlikowske and Dr. Bibbins-Domingo’s estimate that only one-quarter of women with dense breasts are actually at high risk for breast cancer likely reflects their limitation of breast density to only those women with BI-RADs category “D” – extremely dense breasts.
Yet as Dr. Shih notes, women with category C and category D breast densities are both at higher risk for breast cancer, so ignoring women with lesser degrees of breast density still doesn’t address the fact that they have a higher-than-average risk for breast cancer.
“It’s getting harder to make universal screening strategies work as we are learning more and more about breast cancer, so people are starting to talk about screening strategies based on a patient’s risk classification,” Dr. Shih noted.
“It’ll be harder to implement these kinds of strategies, but it seems like the right way to go,” she added.
The study was funded by the National Cancer Institute. Dr. Shih reports grants from the National Cancer Institute during the conduct of the study and personal fees from Pfizer and AstraZeneca outside the submitted work. Dr. Kerlikowske is an unpaid consultant for GRAIL for the STRIVE study. Dr. Bibbins-Domingo has disclosed no relevant financial relationships.
A version of this article first appeared on Medscape.com.
The result would then be used to stratify further screening, with annual screening starting at age 40 for average-risk women who have dense breasts, and screening every 2 years starting at age 50 for women without dense breasts.
Such an approach would be cost effective and offers a more targeted risk-based strategy for the early detection of breast cancer when compared with current practices, say the authors, led by Tina Shih, PhD, University of Texas MD Anderson Cancer Center, Houston.
Their modeling study was published online in the Annals of Internal Medicine.
However, experts writing in an accompanying editorial are not persuaded. Karla Kerlikowske, MD, and Kirsten Bibbins-Domingo, MD, PhD, both from the University of California, San Francisco, point out that not all women with dense breasts are at increased risk for breast cancer. They caution against relying on breast density alone when determining screening strategies, and say age and other risk factors also need to be considered.
New approach proposed
Current recommendations from the United States Preventive Services Task Force suggest that women in their 40s can choose to undergo screening mammography based on their own personal preference, Dr. Shih explained in an interview.
However, these recommendations do not take into consideration the additional risk that breast density confers on breast cancer risk – and the only way women can know their breast density is to have a mammogram. “If you follow [current] guidelines, you would not know about your breast density until the age of 45 or 50,” she commented.
“But what if you knew about breast density earlier on and then acted on it –would that make a difference?” This was the question her team set out to explore.
For their study, the authors defined women with dense breasts as those with the Breast Imaging Reporting and Data System (BI-RADS) category C (heterogeneously dense breasts) and category D (extremely dense breasts).
The team used a computer model to compare seven different breast screening strategies:
- No screening.
- Triennial mammography from age 50 to 75 years (T50).
- Biennial mammography from age 50 to 75 years (B50).
- Stratified annual mammography from age 50 to 75 for women with dense breasts at age 50, and triennial. screening from age 50 to 75 for women without dense breasts at the age of 50 (SA50T50).
- Stratified annual mammography from age 50 to 75 for women with dense breasts at age 50, and biennial screening from age 50 to 75 for those without dense breast at age 50 (SA50B50).
- Stratified annual mammography from age 40 to 75 for women with dense breasts at age 49, and triennial screening from age 50 to 75 for those without dense breasts at age 40 (SA40T50).
- Stratified annual mammography from age 40 to 75 for women with dense breasts at age 40, and biennial mammography for women from age 50 to 75 without dense breasts at age 40 (SA40B50).
Compared with a no-screening strategy, the average number of mammography sessions through a woman’s lifetime would increase from seven mammograms per lifetime for the least frequent screening (T50) to 22 mammograms per lifetime for the most intensive screening schedule, the team reports.
Compared with no screening, screening would reduce breast cancer deaths by 8.6 per 1,000 women (T50)–13.2 per 1,000 women (SA40B50).
A cost-effectiveness analysis showed that the proposed new approach (SA40B50) yielded an incremental cost-effectiveness ratio of $36,200 per quality-adjusted life-year (QALY), compared with the currently recommended biennial screening strategy. This is well within the willingness-to-pay threshold of $100,000 per QALY that is generally accepted by society, the authors point out.
On the other hand, false-positive results and overdiagnosis would increase, the authors note.
The average number of false positives would increase from 141.2 per 1,000 women who underwent the least frequent triennial mammography screening schedule (T50) to 567.3 per 1,000 women with the new approach (SA40B50).
Rates of overdiagnosis would also increase from a low of 12.5% to a high of 18.6%, they add.
“With this study, we are not saying that everybody should start screening at the age of 40. We’re just saying, do a baseline mammography at 40, know your breast density status, and then we can try to modify the screening schedule based on individual risk,” Dr. Shih emphasized.
“Compared with other screening strategies examined in our study, this strategy is associated with the greatest reduction in breast cancer mortality and is cost effective, [although it] involves the most screening mammograms in a woman’s lifetime and higher rates of false-positive results and overdiagnosis,” the authors conclude.
Fundamental problem with this approach
The fundamental problem with this approach of stratifying risk on measurement of breast density – and on the basis of a single reading – is that not every woman with dense breasts is at increased risk for breast cancer, the editorialists comment.
Dr. Kerlikowske and Dr. Bibbins-Domingo point out that, in fact, only about one-quarter of women with dense breasts are at high risk for a missed invasive cancer within 1 year of a negative mammogram, and these women can be identified by using the Breast Cancer Surveillance Consortium risk model.
“This observation means that most women with dense breasts can undergo biennial screening and need not consider annual screening or supplemental imaging,” the editorialists write.
“Thus, we caution against using breast density alone to determine if a woman is at elevated risk for breast cancer,” they emphasize.
An alternative option is to focus on overall risk to select screening strategies, they suggest. For example, most guidelines recommend screening from age 50 to 74, so identifying women in their 40s who have the same risk of a woman aged 50-59 is one way to determine who may benefit from earlier initiation of screening, the editorialists observe.
“Thus, women who have a first-degree relative with breast cancer or a history of breast biopsy could be offered screening in their 40s, and, if mammography shows dense breasts, they could continue biennial screening through their 40s,” the editorialists observe. “Such women with nondense breasts could resume biennial screening at age 50 years.”
Dr. Shih told this news organization that she did not disagree with the editorialists’ suggestion that physicians could focus on overall breast cancer risk to select an appropriate screening strategy for individual patients.
“What we are suggesting is, ‘Let’s just do a baseline assessment at the age of 40 so women know their breast density instead of waiting until they are older,’ “ she said.
“But what the editorialists are suggesting is a strategy that could be even more cost effective,” she acknowledged. Dr. Shih also said that Dr. Kerlikowske and Dr. Bibbins-Domingo’s estimate that only one-quarter of women with dense breasts are actually at high risk for breast cancer likely reflects their limitation of breast density to only those women with BI-RADs category “D” – extremely dense breasts.
Yet as Dr. Shih notes, women with category C and category D breast densities are both at higher risk for breast cancer, so ignoring women with lesser degrees of breast density still doesn’t address the fact that they have a higher-than-average risk for breast cancer.
“It’s getting harder to make universal screening strategies work as we are learning more and more about breast cancer, so people are starting to talk about screening strategies based on a patient’s risk classification,” Dr. Shih noted.
“It’ll be harder to implement these kinds of strategies, but it seems like the right way to go,” she added.
The study was funded by the National Cancer Institute. Dr. Shih reports grants from the National Cancer Institute during the conduct of the study and personal fees from Pfizer and AstraZeneca outside the submitted work. Dr. Kerlikowske is an unpaid consultant for GRAIL for the STRIVE study. Dr. Bibbins-Domingo has disclosed no relevant financial relationships.
A version of this article first appeared on Medscape.com.
CXR-Net: An AI-based diagnostic tool for COVID-19
The system, called CXR-Net, was trained to differentiate SARS-CoV-2 chest x-rays (CXRs) from CXRs that are either normal or non–COVID-19 lung pathologies, explained Abdulah Haikal, an MD candidate at Wayne State University, Detroit.
Mr. Haikal described CXR-Net at the AACR Virtual Meeting: COVID-19 and Cancer (Abstract S11-04).
CXR-Net is a two-module pipeline, Mr. Haikal explained. Module I is based on Res-CR-Net, a type of neural network originally designed for the semantic segmentation of microscopy images, with the ability to retain the original resolution of the input images in the feature maps of all layers and in the final output.
Module II is a hybrid convolutional neural network in which the first convolutional layer with learned coefficients is replaced by a layer with fixed coefficients provided by the Wavelet Scattering Transform. Module II inputs patients’ CXRs and corresponding lung masks quantified by Module I, and generates as outputs a class assignment (COVID-19 or non–COVID-19) and high-resolution heat maps that detect the severe acute respiratory syndrome–-associated lung regions.
“The system is trained to differentiate COVID and non-COVID pathologies and produces a highly discriminative heat map to point to lung regions where COVID is suspected,” Mr. Haikal said. “The Wavelet Scattering Transform allows for fast determination of COVID versus non-COVID CXRs.”
Preliminary results and implications
CXR-Net was piloted on a small dataset of CXRs from non–COVID-19 and polymerase chain reaction–confirmed COVID-19 patients acquired at a single center in Detroit.
Upon fivefold cross validation of the training set with 2,265 images, 90% accuracy was observed when the training set was tested against the validation set. However, once 1,532 new images were introduced, a 76% accuracy rate was observed.
The F1 scores were 0.81 and 0.70 for the training and test sets, respectively.
“I’m really excited about this new approach, and I think AI will allow us to do more with less, which is exciting,” said Ross L. Levine, MD, of Memorial Sloan Kettering Cancer Center in New York, who led a discussion session with Mr. Haikal about CXR-Net.
One question raised during the discussion was whether the technology will help health care providers be more thoughtful about when and how they image COVID-19 patients.
“The more data you feed into the system, the stronger and more accurate it becomes,” Mr. Haikal said. “However, until we have data sharing from multiple centers, we won’t see improved accuracy results.”
Another question was whether this technology could be integrated with more clinical parameters.
“Some individuals are afraid that AI will replace the job of a professional, but it will only make it better for us,” Mr. Haikal said. “We don’t rely on current imaging techniques to make a definitive diagnosis, but rather have a specificity and sensitivity to establish a diagnosis, and AI can be used in the same way as a diagnostic tool.”
Mr. Haikal and Dr. Levine disclosed no conflicts of interest. No funding sources were reported in the presentation.
The system, called CXR-Net, was trained to differentiate SARS-CoV-2 chest x-rays (CXRs) from CXRs that are either normal or non–COVID-19 lung pathologies, explained Abdulah Haikal, an MD candidate at Wayne State University, Detroit.
Mr. Haikal described CXR-Net at the AACR Virtual Meeting: COVID-19 and Cancer (Abstract S11-04).
CXR-Net is a two-module pipeline, Mr. Haikal explained. Module I is based on Res-CR-Net, a type of neural network originally designed for the semantic segmentation of microscopy images, with the ability to retain the original resolution of the input images in the feature maps of all layers and in the final output.
Module II is a hybrid convolutional neural network in which the first convolutional layer with learned coefficients is replaced by a layer with fixed coefficients provided by the Wavelet Scattering Transform. Module II inputs patients’ CXRs and corresponding lung masks quantified by Module I, and generates as outputs a class assignment (COVID-19 or non–COVID-19) and high-resolution heat maps that detect the severe acute respiratory syndrome–-associated lung regions.
“The system is trained to differentiate COVID and non-COVID pathologies and produces a highly discriminative heat map to point to lung regions where COVID is suspected,” Mr. Haikal said. “The Wavelet Scattering Transform allows for fast determination of COVID versus non-COVID CXRs.”
Preliminary results and implications
CXR-Net was piloted on a small dataset of CXRs from non–COVID-19 and polymerase chain reaction–confirmed COVID-19 patients acquired at a single center in Detroit.
Upon fivefold cross validation of the training set with 2,265 images, 90% accuracy was observed when the training set was tested against the validation set. However, once 1,532 new images were introduced, a 76% accuracy rate was observed.
The F1 scores were 0.81 and 0.70 for the training and test sets, respectively.
“I’m really excited about this new approach, and I think AI will allow us to do more with less, which is exciting,” said Ross L. Levine, MD, of Memorial Sloan Kettering Cancer Center in New York, who led a discussion session with Mr. Haikal about CXR-Net.
One question raised during the discussion was whether the technology will help health care providers be more thoughtful about when and how they image COVID-19 patients.
“The more data you feed into the system, the stronger and more accurate it becomes,” Mr. Haikal said. “However, until we have data sharing from multiple centers, we won’t see improved accuracy results.”
Another question was whether this technology could be integrated with more clinical parameters.
“Some individuals are afraid that AI will replace the job of a professional, but it will only make it better for us,” Mr. Haikal said. “We don’t rely on current imaging techniques to make a definitive diagnosis, but rather have a specificity and sensitivity to establish a diagnosis, and AI can be used in the same way as a diagnostic tool.”
Mr. Haikal and Dr. Levine disclosed no conflicts of interest. No funding sources were reported in the presentation.
The system, called CXR-Net, was trained to differentiate SARS-CoV-2 chest x-rays (CXRs) from CXRs that are either normal or non–COVID-19 lung pathologies, explained Abdulah Haikal, an MD candidate at Wayne State University, Detroit.
Mr. Haikal described CXR-Net at the AACR Virtual Meeting: COVID-19 and Cancer (Abstract S11-04).
CXR-Net is a two-module pipeline, Mr. Haikal explained. Module I is based on Res-CR-Net, a type of neural network originally designed for the semantic segmentation of microscopy images, with the ability to retain the original resolution of the input images in the feature maps of all layers and in the final output.
Module II is a hybrid convolutional neural network in which the first convolutional layer with learned coefficients is replaced by a layer with fixed coefficients provided by the Wavelet Scattering Transform. Module II inputs patients’ CXRs and corresponding lung masks quantified by Module I, and generates as outputs a class assignment (COVID-19 or non–COVID-19) and high-resolution heat maps that detect the severe acute respiratory syndrome–-associated lung regions.
“The system is trained to differentiate COVID and non-COVID pathologies and produces a highly discriminative heat map to point to lung regions where COVID is suspected,” Mr. Haikal said. “The Wavelet Scattering Transform allows for fast determination of COVID versus non-COVID CXRs.”
Preliminary results and implications
CXR-Net was piloted on a small dataset of CXRs from non–COVID-19 and polymerase chain reaction–confirmed COVID-19 patients acquired at a single center in Detroit.
Upon fivefold cross validation of the training set with 2,265 images, 90% accuracy was observed when the training set was tested against the validation set. However, once 1,532 new images were introduced, a 76% accuracy rate was observed.
The F1 scores were 0.81 and 0.70 for the training and test sets, respectively.
“I’m really excited about this new approach, and I think AI will allow us to do more with less, which is exciting,” said Ross L. Levine, MD, of Memorial Sloan Kettering Cancer Center in New York, who led a discussion session with Mr. Haikal about CXR-Net.
One question raised during the discussion was whether the technology will help health care providers be more thoughtful about when and how they image COVID-19 patients.
“The more data you feed into the system, the stronger and more accurate it becomes,” Mr. Haikal said. “However, until we have data sharing from multiple centers, we won’t see improved accuracy results.”
Another question was whether this technology could be integrated with more clinical parameters.
“Some individuals are afraid that AI will replace the job of a professional, but it will only make it better for us,” Mr. Haikal said. “We don’t rely on current imaging techniques to make a definitive diagnosis, but rather have a specificity and sensitivity to establish a diagnosis, and AI can be used in the same way as a diagnostic tool.”
Mr. Haikal and Dr. Levine disclosed no conflicts of interest. No funding sources were reported in the presentation.
FROM AACR: COVID-19 AND CANCER 2021
Asymptomatic screening for COVID-19 in cancer patients still debated
Of more than 2,000 patients, less than 1% were found to be COVID-19 positive on asymptomatic screening, an investigator reported at the AACR Virtual Meeting: COVID-19 and Cancer (Abstract S09-04).
While several models have been proposed to screen for COVID-19 among cancer patients, the optimal strategy remains unknown, said investigator Justin A. Shaya, MD, of the University of California, San Diego.
The most commonly used approach is symptom/exposure-based screening and testing. However, other models have combined this method with polymerase chain reaction (PCR) testing for asymptomatic high-risk patients (such as those undergoing bone marrow transplant, receiving chemotherapy, or with hematologic malignancies) or with PCR testing for all asymptomatic cancer patients.
Dr. Shaya’s institution implemented a novel COVID-19 screening protocol for cancer patients receiving infusional therapy in May 2020.
The protocol required SARS-CoV-2 PCR testing for asymptomatic patients 24-96 hours prior to infusion. However, testing was only required before the administration of anticancer therapy. Infusion visits for supportive care interventions did not require previsit testing.
The researchers retrospectively analyzed data from patients with active cancer receiving infusional anticancer therapy who had at least one asymptomatic SARS-CoV-2 PCR test between June 1 and Dec. 1, 2020. The primary outcome was the rate of COVID-19 positivity among asymptomatic patients.
Results
Among 2,202 patients identified, 21 (0.95%) were found to be COVID-19 positive on asymptomatic screening. Most of these patients (90.5%) had solid tumors, but two (9.5%) had hematologic malignancies.
With respect to treatment, 16 patients (76.2%) received cytotoxic chemotherapy, 2 (9.5%) received targeted therapy, 1 (4.7%) received immunotherapy, and 2 (9.5%) were on a clinical trial.
At a median follow-up of 174 days from a positive PCR test (range, 55-223 days), only two patients (9.5%) developed COVID-related symptoms. Both patients had acute leukemia, and one required hospitalization for COVID-related complications.
In the COVID-19–positive cohort, 20 (95.2%) patients had their anticancer therapy delayed or deferred, with a median delay of 21 days (range, 7-77 days).
In the overall cohort, an additional 26 patients (1.2%) developed symptomatic COVID-19 during the study period.
“These results are particularly interesting because they come from a high-quality center that sees a large number of patients,” said Solange Peters, MD, PhD, of the University of Lausanne (Switzerland), who was not involved in this study.
“As they suggest, it is still a debate on how efficient routine screening is, asking the question whether we’re really detecting COVID-19 infection in our patients. Of course, it depends on the time and environment,” Dr. Peters added.
Dr. Shaya acknowledged that the small sample size was a key limitation of the study. Thus, the results may not be generalizable to other regions.
“One of the most striking things is that asymptomatic patients suffer very few consequences of COVID-19 infection, except for patients with hematologic malignancies,” Dr. Shaya said during a live discussion. “The majority of our patients had solid tumors and failed to develop any signs/symptoms of COVID infection.
“Routine screening provides a lot of security, and our institution is big enough to allow for it, and it seems our teams enjoy the fact of knowing the COVID status for each patient,” he continued.
Dr. Shaya and Dr. Peters disclosed no conflicts of interest. No funding sources were reported in the presentation.
Of more than 2,000 patients, less than 1% were found to be COVID-19 positive on asymptomatic screening, an investigator reported at the AACR Virtual Meeting: COVID-19 and Cancer (Abstract S09-04).
While several models have been proposed to screen for COVID-19 among cancer patients, the optimal strategy remains unknown, said investigator Justin A. Shaya, MD, of the University of California, San Diego.
The most commonly used approach is symptom/exposure-based screening and testing. However, other models have combined this method with polymerase chain reaction (PCR) testing for asymptomatic high-risk patients (such as those undergoing bone marrow transplant, receiving chemotherapy, or with hematologic malignancies) or with PCR testing for all asymptomatic cancer patients.
Dr. Shaya’s institution implemented a novel COVID-19 screening protocol for cancer patients receiving infusional therapy in May 2020.
The protocol required SARS-CoV-2 PCR testing for asymptomatic patients 24-96 hours prior to infusion. However, testing was only required before the administration of anticancer therapy. Infusion visits for supportive care interventions did not require previsit testing.
The researchers retrospectively analyzed data from patients with active cancer receiving infusional anticancer therapy who had at least one asymptomatic SARS-CoV-2 PCR test between June 1 and Dec. 1, 2020. The primary outcome was the rate of COVID-19 positivity among asymptomatic patients.
Results
Among 2,202 patients identified, 21 (0.95%) were found to be COVID-19 positive on asymptomatic screening. Most of these patients (90.5%) had solid tumors, but two (9.5%) had hematologic malignancies.
With respect to treatment, 16 patients (76.2%) received cytotoxic chemotherapy, 2 (9.5%) received targeted therapy, 1 (4.7%) received immunotherapy, and 2 (9.5%) were on a clinical trial.
At a median follow-up of 174 days from a positive PCR test (range, 55-223 days), only two patients (9.5%) developed COVID-related symptoms. Both patients had acute leukemia, and one required hospitalization for COVID-related complications.
In the COVID-19–positive cohort, 20 (95.2%) patients had their anticancer therapy delayed or deferred, with a median delay of 21 days (range, 7-77 days).
In the overall cohort, an additional 26 patients (1.2%) developed symptomatic COVID-19 during the study period.
“These results are particularly interesting because they come from a high-quality center that sees a large number of patients,” said Solange Peters, MD, PhD, of the University of Lausanne (Switzerland), who was not involved in this study.
“As they suggest, it is still a debate on how efficient routine screening is, asking the question whether we’re really detecting COVID-19 infection in our patients. Of course, it depends on the time and environment,” Dr. Peters added.
Dr. Shaya acknowledged that the small sample size was a key limitation of the study. Thus, the results may not be generalizable to other regions.
“One of the most striking things is that asymptomatic patients suffer very few consequences of COVID-19 infection, except for patients with hematologic malignancies,” Dr. Shaya said during a live discussion. “The majority of our patients had solid tumors and failed to develop any signs/symptoms of COVID infection.
“Routine screening provides a lot of security, and our institution is big enough to allow for it, and it seems our teams enjoy the fact of knowing the COVID status for each patient,” he continued.
Dr. Shaya and Dr. Peters disclosed no conflicts of interest. No funding sources were reported in the presentation.
Of more than 2,000 patients, less than 1% were found to be COVID-19 positive on asymptomatic screening, an investigator reported at the AACR Virtual Meeting: COVID-19 and Cancer (Abstract S09-04).
While several models have been proposed to screen for COVID-19 among cancer patients, the optimal strategy remains unknown, said investigator Justin A. Shaya, MD, of the University of California, San Diego.
The most commonly used approach is symptom/exposure-based screening and testing. However, other models have combined this method with polymerase chain reaction (PCR) testing for asymptomatic high-risk patients (such as those undergoing bone marrow transplant, receiving chemotherapy, or with hematologic malignancies) or with PCR testing for all asymptomatic cancer patients.
Dr. Shaya’s institution implemented a novel COVID-19 screening protocol for cancer patients receiving infusional therapy in May 2020.
The protocol required SARS-CoV-2 PCR testing for asymptomatic patients 24-96 hours prior to infusion. However, testing was only required before the administration of anticancer therapy. Infusion visits for supportive care interventions did not require previsit testing.
The researchers retrospectively analyzed data from patients with active cancer receiving infusional anticancer therapy who had at least one asymptomatic SARS-CoV-2 PCR test between June 1 and Dec. 1, 2020. The primary outcome was the rate of COVID-19 positivity among asymptomatic patients.
Results
Among 2,202 patients identified, 21 (0.95%) were found to be COVID-19 positive on asymptomatic screening. Most of these patients (90.5%) had solid tumors, but two (9.5%) had hematologic malignancies.
With respect to treatment, 16 patients (76.2%) received cytotoxic chemotherapy, 2 (9.5%) received targeted therapy, 1 (4.7%) received immunotherapy, and 2 (9.5%) were on a clinical trial.
At a median follow-up of 174 days from a positive PCR test (range, 55-223 days), only two patients (9.5%) developed COVID-related symptoms. Both patients had acute leukemia, and one required hospitalization for COVID-related complications.
In the COVID-19–positive cohort, 20 (95.2%) patients had their anticancer therapy delayed or deferred, with a median delay of 21 days (range, 7-77 days).
In the overall cohort, an additional 26 patients (1.2%) developed symptomatic COVID-19 during the study period.
“These results are particularly interesting because they come from a high-quality center that sees a large number of patients,” said Solange Peters, MD, PhD, of the University of Lausanne (Switzerland), who was not involved in this study.
“As they suggest, it is still a debate on how efficient routine screening is, asking the question whether we’re really detecting COVID-19 infection in our patients. Of course, it depends on the time and environment,” Dr. Peters added.
Dr. Shaya acknowledged that the small sample size was a key limitation of the study. Thus, the results may not be generalizable to other regions.
“One of the most striking things is that asymptomatic patients suffer very few consequences of COVID-19 infection, except for patients with hematologic malignancies,” Dr. Shaya said during a live discussion. “The majority of our patients had solid tumors and failed to develop any signs/symptoms of COVID infection.
“Routine screening provides a lot of security, and our institution is big enough to allow for it, and it seems our teams enjoy the fact of knowing the COVID status for each patient,” he continued.
Dr. Shaya and Dr. Peters disclosed no conflicts of interest. No funding sources were reported in the presentation.
FROM AACR: COVID-19 AND CANCER 2021
Managing cancer outpatients during the pandemic: Tips from MSKCC
“We’ve tried a lot of new things to ensure optimal care for our patients,” said Tiffany A. Traina, MD, of Memorial Sloan Kettering Cancer Center (MSKCC) in New York. “We need to effectively utilize all resources at our disposal to keep in touch with our patients during this time.”
Dr. Traina described the approach to outpatient management used at MSKCC during a presentation at the AACR Virtual Meeting: COVID-19 and Cancer.
Four guiding principles
MSKCC has established four guiding principles on how to manage cancer patients during the pandemic: openness, safety, technology, and staffing.
Openness ensures that decisions are guided by clinical priorities to provide optimal patient care and allow for prioritization of clinical research and education, Dr. Traina said.
The safety of patients and staff is of the utmost importance, she added. To ensure safety in the context of outpatient care, several operational levers were developed, including COVID surge planning, universal masking and personal protective equipment guidelines, remote work, clinical levers, and new dashboards and communications.
Dr. Traina said data analytics and dashboards have been key technological tools used to support evidence-based decision-making and deliver care remotely for patients during the pandemic.
Staffing resources have also shifted to support demand at different health system locations.
Screening, cohorting, and telemedicine
One measure MSKCC adopted is the MSK Engage Questionnaire, a COVID-19 screening questionnaire assigned to every patient with a scheduled outpatient visit. After completing the questionnaire, patients receive a response denoting whether they need to come into the outpatient setting.
On the staffing side, clinic coordinators prepare appointments accordingly, based on the risk level for each patient.
“We also try to cohort COVID-positive patients into particular areas within the outpatient setting,” Dr. Traina explained. “In addition, we control flow through ambulatory care locations by having separate patient entrances and use other tools to make flow as efficient as possible.”
On the technology side, interactive dashboards are being used to model traffic through different buildings.
“These data and analytics are useful for operational engineering, answering questions such as (1) Are there backups in chemotherapy? and (2) Are patients seeing one particular physician?” Dr. Traina explained. “One important key takeaway is the importance of frequently communicating simple messages through multiple mechanisms, including signage, websites, and dedicated resources.”
Other key technological measures are leveraging telemedicine to convert inpatient appointments to a virtual setting, as well as developing and deploying a system for centralized outpatient follow-up of COVID-19-positive patients.
“We saw a 3,000% increase in telemedicine utilization from February 2020 to June 2020,” Dr. Traina reported. “In a given month, we have approximately 230,000 outpatient visits, and a substantial proportion of these are now done via telemedicine.”
Dr. Traina also noted that multiple organizations have released guidelines addressing when to resume anticancer therapy in patients who have been COVID-19 positive. Adherence is important, as unnecessary COVID-19 testing may delay cancer therapy and is not recommended.
During a live discussion, Louis P. Voigt, MD, of MSKCC, said Dr. Traina’s presentation provided “a lot of good ideas for other institutions who may be facing similar challenges.”
Dr. Traina and Dr. Voigt disclosed no conflicts of interest. No funding sources were reported.
“We’ve tried a lot of new things to ensure optimal care for our patients,” said Tiffany A. Traina, MD, of Memorial Sloan Kettering Cancer Center (MSKCC) in New York. “We need to effectively utilize all resources at our disposal to keep in touch with our patients during this time.”
Dr. Traina described the approach to outpatient management used at MSKCC during a presentation at the AACR Virtual Meeting: COVID-19 and Cancer.
Four guiding principles
MSKCC has established four guiding principles on how to manage cancer patients during the pandemic: openness, safety, technology, and staffing.
Openness ensures that decisions are guided by clinical priorities to provide optimal patient care and allow for prioritization of clinical research and education, Dr. Traina said.
The safety of patients and staff is of the utmost importance, she added. To ensure safety in the context of outpatient care, several operational levers were developed, including COVID surge planning, universal masking and personal protective equipment guidelines, remote work, clinical levers, and new dashboards and communications.
Dr. Traina said data analytics and dashboards have been key technological tools used to support evidence-based decision-making and deliver care remotely for patients during the pandemic.
Staffing resources have also shifted to support demand at different health system locations.
Screening, cohorting, and telemedicine
One measure MSKCC adopted is the MSK Engage Questionnaire, a COVID-19 screening questionnaire assigned to every patient with a scheduled outpatient visit. After completing the questionnaire, patients receive a response denoting whether they need to come into the outpatient setting.
On the staffing side, clinic coordinators prepare appointments accordingly, based on the risk level for each patient.
“We also try to cohort COVID-positive patients into particular areas within the outpatient setting,” Dr. Traina explained. “In addition, we control flow through ambulatory care locations by having separate patient entrances and use other tools to make flow as efficient as possible.”
On the technology side, interactive dashboards are being used to model traffic through different buildings.
“These data and analytics are useful for operational engineering, answering questions such as (1) Are there backups in chemotherapy? and (2) Are patients seeing one particular physician?” Dr. Traina explained. “One important key takeaway is the importance of frequently communicating simple messages through multiple mechanisms, including signage, websites, and dedicated resources.”
Other key technological measures are leveraging telemedicine to convert inpatient appointments to a virtual setting, as well as developing and deploying a system for centralized outpatient follow-up of COVID-19-positive patients.
“We saw a 3,000% increase in telemedicine utilization from February 2020 to June 2020,” Dr. Traina reported. “In a given month, we have approximately 230,000 outpatient visits, and a substantial proportion of these are now done via telemedicine.”
Dr. Traina also noted that multiple organizations have released guidelines addressing when to resume anticancer therapy in patients who have been COVID-19 positive. Adherence is important, as unnecessary COVID-19 testing may delay cancer therapy and is not recommended.
During a live discussion, Louis P. Voigt, MD, of MSKCC, said Dr. Traina’s presentation provided “a lot of good ideas for other institutions who may be facing similar challenges.”
Dr. Traina and Dr. Voigt disclosed no conflicts of interest. No funding sources were reported.
“We’ve tried a lot of new things to ensure optimal care for our patients,” said Tiffany A. Traina, MD, of Memorial Sloan Kettering Cancer Center (MSKCC) in New York. “We need to effectively utilize all resources at our disposal to keep in touch with our patients during this time.”
Dr. Traina described the approach to outpatient management used at MSKCC during a presentation at the AACR Virtual Meeting: COVID-19 and Cancer.
Four guiding principles
MSKCC has established four guiding principles on how to manage cancer patients during the pandemic: openness, safety, technology, and staffing.
Openness ensures that decisions are guided by clinical priorities to provide optimal patient care and allow for prioritization of clinical research and education, Dr. Traina said.
The safety of patients and staff is of the utmost importance, she added. To ensure safety in the context of outpatient care, several operational levers were developed, including COVID surge planning, universal masking and personal protective equipment guidelines, remote work, clinical levers, and new dashboards and communications.
Dr. Traina said data analytics and dashboards have been key technological tools used to support evidence-based decision-making and deliver care remotely for patients during the pandemic.
Staffing resources have also shifted to support demand at different health system locations.
Screening, cohorting, and telemedicine
One measure MSKCC adopted is the MSK Engage Questionnaire, a COVID-19 screening questionnaire assigned to every patient with a scheduled outpatient visit. After completing the questionnaire, patients receive a response denoting whether they need to come into the outpatient setting.
On the staffing side, clinic coordinators prepare appointments accordingly, based on the risk level for each patient.
“We also try to cohort COVID-positive patients into particular areas within the outpatient setting,” Dr. Traina explained. “In addition, we control flow through ambulatory care locations by having separate patient entrances and use other tools to make flow as efficient as possible.”
On the technology side, interactive dashboards are being used to model traffic through different buildings.
“These data and analytics are useful for operational engineering, answering questions such as (1) Are there backups in chemotherapy? and (2) Are patients seeing one particular physician?” Dr. Traina explained. “One important key takeaway is the importance of frequently communicating simple messages through multiple mechanisms, including signage, websites, and dedicated resources.”
Other key technological measures are leveraging telemedicine to convert inpatient appointments to a virtual setting, as well as developing and deploying a system for centralized outpatient follow-up of COVID-19-positive patients.
“We saw a 3,000% increase in telemedicine utilization from February 2020 to June 2020,” Dr. Traina reported. “In a given month, we have approximately 230,000 outpatient visits, and a substantial proportion of these are now done via telemedicine.”
Dr. Traina also noted that multiple organizations have released guidelines addressing when to resume anticancer therapy in patients who have been COVID-19 positive. Adherence is important, as unnecessary COVID-19 testing may delay cancer therapy and is not recommended.
During a live discussion, Louis P. Voigt, MD, of MSKCC, said Dr. Traina’s presentation provided “a lot of good ideas for other institutions who may be facing similar challenges.”
Dr. Traina and Dr. Voigt disclosed no conflicts of interest. No funding sources were reported.
FROM AACR: COVID-19 AND CANCER 2021
Long-term metformin use linked to fewer ER+ breast cancers
.
Conversely, the results also showed higher rates of ER-negative and triple-negative breast cancer among women with type 2 diabetes who received metformin, although case numbers were small.
“Our conclusion that having type 2 diabetes increases the risk of developing breast cancer but taking metformin may protect against developing ER-positive breast cancer – but not other types of breast cancer – is biologically plausible and supported by our results, even though some [endpoints] are not statistically significant,” senior author Dale P. Sandler, PhD, chief of the epidemiology branch, National Institute of Environmental Health Sciences, Research Triangle Park, N.C., said in an interview.
“Among our findings that are not statistically significant are several that helped us get a better picture of the relationships between type 2 diabetes, metformin treatment, and breast cancer risk,” Dr. Sandler added.
The results were published online Jan. 28 in Annals of Oncology by Yong-Moon Mark Park, MD, PhD, now an epidemiologist at the University of Arkansas for Medical Sciences in Little Rock, and colleagues.
Sara P. Cate, MD, a breast cancer surgeon at Mount Sinai Medical Center in New York, who was not involved with the study, said: “Certainly, metformin helps with weight loss, which is linked with estrogen-driven breast cancers, so this may explain why fewer patients on metformin got this type of breast cancer.”
A tangled web ... with no clear conclusions yet
But in an accompanying editorial, Ana E. Lohmann, MD, PhD, and Pamela J. Goodwin, MD, say that, while this is “a large, well-designed prospective cohort study,” it tells a complicated story.
“The report by Park adds to the growing evidence linking type 2 diabetes and its treatment to breast cancer risk, but definitive conclusions regarding these associations are not yet possible,” they observe.
The “largely negative” results of the new study perhaps in part occurred because the cohort included only 277 women with type 2 diabetes diagnosed with incident breast cancer, note Dr. Lohmann, of London Health Sciences Centre, University of Western Ontario, and Dr. Goodwin, of Mount Sinai Hospital, Toronto.
“Clearly, this is an important area, and additional research is needed to untangle the web of inter-related associations of type 2 diabetes, its treatment, and breast cancer risk,” they write.
Examination of the effects of metformin in studies such as the Canadian Cancer Trial Group MA.32, a phase 3 trial of over 3,500 women with hormone receptor–positive early-stage breast cancer who are being randomized to metformin or placebo for up to 5 years in addition to standard adjuvant therapy, will provide further insights, they observe. The trial is slated to be completed in February 2022.
Study followed women whose sisters had breast cancer
The new data come from the Sister Study, which followed more than 50,000 women without a history of breast cancer who had sisters or half-sisters with a breast cancer diagnosis. The study, run by the NIEHS, enrolled women 35-74 years old from all 50 U.S. states and Puerto Rico in 2003-2009.
The current analysis excluded women with a history of any other type of cancer, missing data about diabetes, or an uncertain breast cancer diagnosis during the study, which left 44,541 available for study. At entry, 7% of the women had type 2 diabetes, and another 5% developed new-onset type 2 diabetes during follow-up.
Among those with diabetes, 61% received treatment with metformin either alone or with other antidiabetic drugs.
During a median follow-up of 8.6 years, 2,678 women received a diagnosis of primary breast cancer, either invasive or ductal carcinoma in situ.
In a series of multivariate analyses that adjusted for numerous potential confounders, the authors found that, overall, no association existed between diabetes and breast cancer incidence, with a hazard ratio of 0.99, compared with women without diabetes.
But, said Dr. Sandler, “there is a strong biological rationale to hypothesize that type 2 diabetes increases the risk for breast cancer, and results from earlier studies support this.”
Association of metformin and breast cancer
Women with type 2 diabetes who received metformin had a 14% lower rate of ER-positive breast cancer, compared with women with diabetes not taking metformin, a nonsignificant association.
Among women taking metformin for at least 10 years, the associated reduction in ER-positive breast cancer, compared with those who did not take it, was 38%, a difference that just missed significance, with a 95% confidence interval of 0.38-1.01.
In contrast, cases of ER-negative and triple-negative breast cancers increased in the women with diabetes taking metformin. The hazard ratio for ER-negative tumors showed a nonsignificant 25% relative increase in women taking metformin and a significant 74% increase in triple-negative cancers.
The editorialists note, however, that “the number of patients who were found to have triple-negative breast cancer was small [so] we cannot draw any practice-changing conclusions from it.”
In conclusion, Dr. Park and colleagues reiterate: “Our analysis is consistent with a potential protective effect of metformin and suggests that long-term use of metformin may reduce breast cancer risk associated with type 2 diabetes.”
The study received no commercial funding. Dr. Sandler, Dr. Park, Dr. Lohmann, Dr. Goodwin, and Dr. Cate have reported no relevant financial relationships.
A version of this article first appeared on Medscape.com.
.
Conversely, the results also showed higher rates of ER-negative and triple-negative breast cancer among women with type 2 diabetes who received metformin, although case numbers were small.
“Our conclusion that having type 2 diabetes increases the risk of developing breast cancer but taking metformin may protect against developing ER-positive breast cancer – but not other types of breast cancer – is biologically plausible and supported by our results, even though some [endpoints] are not statistically significant,” senior author Dale P. Sandler, PhD, chief of the epidemiology branch, National Institute of Environmental Health Sciences, Research Triangle Park, N.C., said in an interview.
“Among our findings that are not statistically significant are several that helped us get a better picture of the relationships between type 2 diabetes, metformin treatment, and breast cancer risk,” Dr. Sandler added.
The results were published online Jan. 28 in Annals of Oncology by Yong-Moon Mark Park, MD, PhD, now an epidemiologist at the University of Arkansas for Medical Sciences in Little Rock, and colleagues.
Sara P. Cate, MD, a breast cancer surgeon at Mount Sinai Medical Center in New York, who was not involved with the study, said: “Certainly, metformin helps with weight loss, which is linked with estrogen-driven breast cancers, so this may explain why fewer patients on metformin got this type of breast cancer.”
A tangled web ... with no clear conclusions yet
But in an accompanying editorial, Ana E. Lohmann, MD, PhD, and Pamela J. Goodwin, MD, say that, while this is “a large, well-designed prospective cohort study,” it tells a complicated story.
“The report by Park adds to the growing evidence linking type 2 diabetes and its treatment to breast cancer risk, but definitive conclusions regarding these associations are not yet possible,” they observe.
The “largely negative” results of the new study perhaps in part occurred because the cohort included only 277 women with type 2 diabetes diagnosed with incident breast cancer, note Dr. Lohmann, of London Health Sciences Centre, University of Western Ontario, and Dr. Goodwin, of Mount Sinai Hospital, Toronto.
“Clearly, this is an important area, and additional research is needed to untangle the web of inter-related associations of type 2 diabetes, its treatment, and breast cancer risk,” they write.
Examination of the effects of metformin in studies such as the Canadian Cancer Trial Group MA.32, a phase 3 trial of over 3,500 women with hormone receptor–positive early-stage breast cancer who are being randomized to metformin or placebo for up to 5 years in addition to standard adjuvant therapy, will provide further insights, they observe. The trial is slated to be completed in February 2022.
Study followed women whose sisters had breast cancer
The new data come from the Sister Study, which followed more than 50,000 women without a history of breast cancer who had sisters or half-sisters with a breast cancer diagnosis. The study, run by the NIEHS, enrolled women 35-74 years old from all 50 U.S. states and Puerto Rico in 2003-2009.
The current analysis excluded women with a history of any other type of cancer, missing data about diabetes, or an uncertain breast cancer diagnosis during the study, which left 44,541 available for study. At entry, 7% of the women had type 2 diabetes, and another 5% developed new-onset type 2 diabetes during follow-up.
Among those with diabetes, 61% received treatment with metformin either alone or with other antidiabetic drugs.
During a median follow-up of 8.6 years, 2,678 women received a diagnosis of primary breast cancer, either invasive or ductal carcinoma in situ.
In a series of multivariate analyses that adjusted for numerous potential confounders, the authors found that, overall, no association existed between diabetes and breast cancer incidence, with a hazard ratio of 0.99, compared with women without diabetes.
But, said Dr. Sandler, “there is a strong biological rationale to hypothesize that type 2 diabetes increases the risk for breast cancer, and results from earlier studies support this.”
Association of metformin and breast cancer
Women with type 2 diabetes who received metformin had a 14% lower rate of ER-positive breast cancer, compared with women with diabetes not taking metformin, a nonsignificant association.
Among women taking metformin for at least 10 years, the associated reduction in ER-positive breast cancer, compared with those who did not take it, was 38%, a difference that just missed significance, with a 95% confidence interval of 0.38-1.01.
In contrast, cases of ER-negative and triple-negative breast cancers increased in the women with diabetes taking metformin. The hazard ratio for ER-negative tumors showed a nonsignificant 25% relative increase in women taking metformin and a significant 74% increase in triple-negative cancers.
The editorialists note, however, that “the number of patients who were found to have triple-negative breast cancer was small [so] we cannot draw any practice-changing conclusions from it.”
In conclusion, Dr. Park and colleagues reiterate: “Our analysis is consistent with a potential protective effect of metformin and suggests that long-term use of metformin may reduce breast cancer risk associated with type 2 diabetes.”
The study received no commercial funding. Dr. Sandler, Dr. Park, Dr. Lohmann, Dr. Goodwin, and Dr. Cate have reported no relevant financial relationships.
A version of this article first appeared on Medscape.com.
.
Conversely, the results also showed higher rates of ER-negative and triple-negative breast cancer among women with type 2 diabetes who received metformin, although case numbers were small.
“Our conclusion that having type 2 diabetes increases the risk of developing breast cancer but taking metformin may protect against developing ER-positive breast cancer – but not other types of breast cancer – is biologically plausible and supported by our results, even though some [endpoints] are not statistically significant,” senior author Dale P. Sandler, PhD, chief of the epidemiology branch, National Institute of Environmental Health Sciences, Research Triangle Park, N.C., said in an interview.
“Among our findings that are not statistically significant are several that helped us get a better picture of the relationships between type 2 diabetes, metformin treatment, and breast cancer risk,” Dr. Sandler added.
The results were published online Jan. 28 in Annals of Oncology by Yong-Moon Mark Park, MD, PhD, now an epidemiologist at the University of Arkansas for Medical Sciences in Little Rock, and colleagues.
Sara P. Cate, MD, a breast cancer surgeon at Mount Sinai Medical Center in New York, who was not involved with the study, said: “Certainly, metformin helps with weight loss, which is linked with estrogen-driven breast cancers, so this may explain why fewer patients on metformin got this type of breast cancer.”
A tangled web ... with no clear conclusions yet
But in an accompanying editorial, Ana E. Lohmann, MD, PhD, and Pamela J. Goodwin, MD, say that, while this is “a large, well-designed prospective cohort study,” it tells a complicated story.
“The report by Park adds to the growing evidence linking type 2 diabetes and its treatment to breast cancer risk, but definitive conclusions regarding these associations are not yet possible,” they observe.
The “largely negative” results of the new study perhaps in part occurred because the cohort included only 277 women with type 2 diabetes diagnosed with incident breast cancer, note Dr. Lohmann, of London Health Sciences Centre, University of Western Ontario, and Dr. Goodwin, of Mount Sinai Hospital, Toronto.
“Clearly, this is an important area, and additional research is needed to untangle the web of inter-related associations of type 2 diabetes, its treatment, and breast cancer risk,” they write.
Examination of the effects of metformin in studies such as the Canadian Cancer Trial Group MA.32, a phase 3 trial of over 3,500 women with hormone receptor–positive early-stage breast cancer who are being randomized to metformin or placebo for up to 5 years in addition to standard adjuvant therapy, will provide further insights, they observe. The trial is slated to be completed in February 2022.
Study followed women whose sisters had breast cancer
The new data come from the Sister Study, which followed more than 50,000 women without a history of breast cancer who had sisters or half-sisters with a breast cancer diagnosis. The study, run by the NIEHS, enrolled women 35-74 years old from all 50 U.S. states and Puerto Rico in 2003-2009.
The current analysis excluded women with a history of any other type of cancer, missing data about diabetes, or an uncertain breast cancer diagnosis during the study, which left 44,541 available for study. At entry, 7% of the women had type 2 diabetes, and another 5% developed new-onset type 2 diabetes during follow-up.
Among those with diabetes, 61% received treatment with metformin either alone or with other antidiabetic drugs.
During a median follow-up of 8.6 years, 2,678 women received a diagnosis of primary breast cancer, either invasive or ductal carcinoma in situ.
In a series of multivariate analyses that adjusted for numerous potential confounders, the authors found that, overall, no association existed between diabetes and breast cancer incidence, with a hazard ratio of 0.99, compared with women without diabetes.
But, said Dr. Sandler, “there is a strong biological rationale to hypothesize that type 2 diabetes increases the risk for breast cancer, and results from earlier studies support this.”
Association of metformin and breast cancer
Women with type 2 diabetes who received metformin had a 14% lower rate of ER-positive breast cancer, compared with women with diabetes not taking metformin, a nonsignificant association.
Among women taking metformin for at least 10 years, the associated reduction in ER-positive breast cancer, compared with those who did not take it, was 38%, a difference that just missed significance, with a 95% confidence interval of 0.38-1.01.
In contrast, cases of ER-negative and triple-negative breast cancers increased in the women with diabetes taking metformin. The hazard ratio for ER-negative tumors showed a nonsignificant 25% relative increase in women taking metformin and a significant 74% increase in triple-negative cancers.
The editorialists note, however, that “the number of patients who were found to have triple-negative breast cancer was small [so] we cannot draw any practice-changing conclusions from it.”
In conclusion, Dr. Park and colleagues reiterate: “Our analysis is consistent with a potential protective effect of metformin and suggests that long-term use of metformin may reduce breast cancer risk associated with type 2 diabetes.”
The study received no commercial funding. Dr. Sandler, Dr. Park, Dr. Lohmann, Dr. Goodwin, and Dr. Cate have reported no relevant financial relationships.
A version of this article first appeared on Medscape.com.
Early breast cancer: Real-world recurrence with IORT higher than previously reported
Key clinical point: Rates of ipsilateral breast tumor recurrence (IBTR) in patients with early breast cancer treated with lumpectomy and intraoperative radiation therapy (IORT) are higher than that reported in TARGIT-A trial and with traditional whole-breast radiation therapy or other forms of partial breast irradiation.
Major finding: At 5 years, the absolute IBTR rate was 6.6% for the entire IORT-treated cohort. IBTR rate was 8% and 1.2% for patients who received primary IORT and unintentional IORT boost treatment, respectively. No recurrences were observed in the delayed IORT or intentional-boost IORT cohorts.
Study details: Findings from an updated analysis of TARGIT-R with a 5-year follow-up assessment in 667 patients with early-stage breast cancer who underwent lumpectomy and IORT.
Disclosures: The study did not receive any funding. The lead author did not report any conflicts of interest, but some co-investigators reported relationships with various pharmaceutical companies.
Source: Valente SA et al. Ann Surg Oncol. 2021 Jan 12. doi: 10.1245/s10434-020-09432-3.
Key clinical point: Rates of ipsilateral breast tumor recurrence (IBTR) in patients with early breast cancer treated with lumpectomy and intraoperative radiation therapy (IORT) are higher than that reported in TARGIT-A trial and with traditional whole-breast radiation therapy or other forms of partial breast irradiation.
Major finding: At 5 years, the absolute IBTR rate was 6.6% for the entire IORT-treated cohort. IBTR rate was 8% and 1.2% for patients who received primary IORT and unintentional IORT boost treatment, respectively. No recurrences were observed in the delayed IORT or intentional-boost IORT cohorts.
Study details: Findings from an updated analysis of TARGIT-R with a 5-year follow-up assessment in 667 patients with early-stage breast cancer who underwent lumpectomy and IORT.
Disclosures: The study did not receive any funding. The lead author did not report any conflicts of interest, but some co-investigators reported relationships with various pharmaceutical companies.
Source: Valente SA et al. Ann Surg Oncol. 2021 Jan 12. doi: 10.1245/s10434-020-09432-3.
Key clinical point: Rates of ipsilateral breast tumor recurrence (IBTR) in patients with early breast cancer treated with lumpectomy and intraoperative radiation therapy (IORT) are higher than that reported in TARGIT-A trial and with traditional whole-breast radiation therapy or other forms of partial breast irradiation.
Major finding: At 5 years, the absolute IBTR rate was 6.6% for the entire IORT-treated cohort. IBTR rate was 8% and 1.2% for patients who received primary IORT and unintentional IORT boost treatment, respectively. No recurrences were observed in the delayed IORT or intentional-boost IORT cohorts.
Study details: Findings from an updated analysis of TARGIT-R with a 5-year follow-up assessment in 667 patients with early-stage breast cancer who underwent lumpectomy and IORT.
Disclosures: The study did not receive any funding. The lead author did not report any conflicts of interest, but some co-investigators reported relationships with various pharmaceutical companies.
Source: Valente SA et al. Ann Surg Oncol. 2021 Jan 12. doi: 10.1245/s10434-020-09432-3.
TNBC: Capecitabine maintenance improves DFS but not OS
Key clinical point: Low-dose capecitabine maintenance therapy for 1 year after standard adjuvant chemotherapy resulted in significantly better disease-free survival (DFS) but not overall survival (OS) in women with early triple-negative breast cancer (TNBC).
Major finding: Capecitabine vs. observation group had significantly higher estimated 5-year DFS (82.8% vs. 73%; hazard ratio [HR], 0.64; P = .03) and distant DFS (85.8% vs. 75.8%; HR, 0.60; P = .02) but not OS (85.5% vs. 81.3%; HR, 0.75; P = .22). Hand-foot syndrome (45.2%) was the most common adverse event in the capecitabine group, with 7.7% of patients experiencing grade 3 event.
Study details: Phase 3 SYSUCC-001 trial randomly allocated 434 women with early TNBC to receive either low-dose capecitabine maintenance (n=221) or undergo observation (n=213) within 4 weeks after completion of standard adjuvant chemotherapy.
Disclosures: This study was funded by Sun Yat-sen University, the National Natural Science Foundation of China, Natural Science Foundation of Guangdong Province, and F. Hoffmann-La Roche Ltd. The study investigators did not report any conflict of interest.
Source: Wang X et al. JAMA. 2021 Jan 5. doi: 10.1001/jama.2020.23370.
Key clinical point: Low-dose capecitabine maintenance therapy for 1 year after standard adjuvant chemotherapy resulted in significantly better disease-free survival (DFS) but not overall survival (OS) in women with early triple-negative breast cancer (TNBC).
Major finding: Capecitabine vs. observation group had significantly higher estimated 5-year DFS (82.8% vs. 73%; hazard ratio [HR], 0.64; P = .03) and distant DFS (85.8% vs. 75.8%; HR, 0.60; P = .02) but not OS (85.5% vs. 81.3%; HR, 0.75; P = .22). Hand-foot syndrome (45.2%) was the most common adverse event in the capecitabine group, with 7.7% of patients experiencing grade 3 event.
Study details: Phase 3 SYSUCC-001 trial randomly allocated 434 women with early TNBC to receive either low-dose capecitabine maintenance (n=221) or undergo observation (n=213) within 4 weeks after completion of standard adjuvant chemotherapy.
Disclosures: This study was funded by Sun Yat-sen University, the National Natural Science Foundation of China, Natural Science Foundation of Guangdong Province, and F. Hoffmann-La Roche Ltd. The study investigators did not report any conflict of interest.
Source: Wang X et al. JAMA. 2021 Jan 5. doi: 10.1001/jama.2020.23370.
Key clinical point: Low-dose capecitabine maintenance therapy for 1 year after standard adjuvant chemotherapy resulted in significantly better disease-free survival (DFS) but not overall survival (OS) in women with early triple-negative breast cancer (TNBC).
Major finding: Capecitabine vs. observation group had significantly higher estimated 5-year DFS (82.8% vs. 73%; hazard ratio [HR], 0.64; P = .03) and distant DFS (85.8% vs. 75.8%; HR, 0.60; P = .02) but not OS (85.5% vs. 81.3%; HR, 0.75; P = .22). Hand-foot syndrome (45.2%) was the most common adverse event in the capecitabine group, with 7.7% of patients experiencing grade 3 event.
Study details: Phase 3 SYSUCC-001 trial randomly allocated 434 women with early TNBC to receive either low-dose capecitabine maintenance (n=221) or undergo observation (n=213) within 4 weeks after completion of standard adjuvant chemotherapy.
Disclosures: This study was funded by Sun Yat-sen University, the National Natural Science Foundation of China, Natural Science Foundation of Guangdong Province, and F. Hoffmann-La Roche Ltd. The study investigators did not report any conflict of interest.
Source: Wang X et al. JAMA. 2021 Jan 5. doi: 10.1001/jama.2020.23370.
MBC: Pertuzumab-associated rash and diarrhea predict survival outcomes
Key clinical point: In patients with human epidermal growth factor receptor 2 (HER2)-positive metastatic breast cancer (MBC) treated with pertuzumab, trastuzumab, and docetaxel, rash during treatment and diarrhea after docetaxel discontinuation are predictors of survival outcomes.
Major finding: Development of rash during docetaxel administration predicted progression-free survival (PFS; adjusted hazard ratio [aHR], 0.71; P = .006) and overall survival (OS; aHR, 0.66; P = .01). Development of rash after docetaxel interruption also predicted PFS (aHR, 0.55; P = .002) and OS (aHR, 0.52; P = .018). Diarrhea was prognostic only for PFS (aHR, 0.65; P = .011) after docetaxel discontinuation.
Study details: The data come from a retrospective analysis of CLEOPATRA trial involving 777 patients with de novo or recurrent advanced HER2-positive MBC treated with docetaxel plus trastuzumab with or without pertuzumab.
Disclosures: No specific funding source was identified. Some authors reported receiving travel grants, consultation fees, and honoraria from various pharmaceutical companies.
Source: Ferreira AR et al. Eur J Cancer. 2020 Dec 31. doi: 10.1016/j.ejca.2020.11.023.
Key clinical point: In patients with human epidermal growth factor receptor 2 (HER2)-positive metastatic breast cancer (MBC) treated with pertuzumab, trastuzumab, and docetaxel, rash during treatment and diarrhea after docetaxel discontinuation are predictors of survival outcomes.
Major finding: Development of rash during docetaxel administration predicted progression-free survival (PFS; adjusted hazard ratio [aHR], 0.71; P = .006) and overall survival (OS; aHR, 0.66; P = .01). Development of rash after docetaxel interruption also predicted PFS (aHR, 0.55; P = .002) and OS (aHR, 0.52; P = .018). Diarrhea was prognostic only for PFS (aHR, 0.65; P = .011) after docetaxel discontinuation.
Study details: The data come from a retrospective analysis of CLEOPATRA trial involving 777 patients with de novo or recurrent advanced HER2-positive MBC treated with docetaxel plus trastuzumab with or without pertuzumab.
Disclosures: No specific funding source was identified. Some authors reported receiving travel grants, consultation fees, and honoraria from various pharmaceutical companies.
Source: Ferreira AR et al. Eur J Cancer. 2020 Dec 31. doi: 10.1016/j.ejca.2020.11.023.
Key clinical point: In patients with human epidermal growth factor receptor 2 (HER2)-positive metastatic breast cancer (MBC) treated with pertuzumab, trastuzumab, and docetaxel, rash during treatment and diarrhea after docetaxel discontinuation are predictors of survival outcomes.
Major finding: Development of rash during docetaxel administration predicted progression-free survival (PFS; adjusted hazard ratio [aHR], 0.71; P = .006) and overall survival (OS; aHR, 0.66; P = .01). Development of rash after docetaxel interruption also predicted PFS (aHR, 0.55; P = .002) and OS (aHR, 0.52; P = .018). Diarrhea was prognostic only for PFS (aHR, 0.65; P = .011) after docetaxel discontinuation.
Study details: The data come from a retrospective analysis of CLEOPATRA trial involving 777 patients with de novo or recurrent advanced HER2-positive MBC treated with docetaxel plus trastuzumab with or without pertuzumab.
Disclosures: No specific funding source was identified. Some authors reported receiving travel grants, consultation fees, and honoraria from various pharmaceutical companies.
Source: Ferreira AR et al. Eur J Cancer. 2020 Dec 31. doi: 10.1016/j.ejca.2020.11.023.
Heterogeneity in risk factors for symptom- vs. screen-detected breast cancer
Key clinical point: Hormone therapy (HT) use and benign breast disease (BBD) history are more strongly associated with a higher risk for symptom-detected breast cancer (sym-BC), whereas alcohol intake and obesity are associated with an increased screen-detected BC (scrn-BC) risk.
Major finding: Factors more strongly associated with higher sym-BC vs. scrn-BC risk were estrogen HT use (adjusted hazard ratio [aHR], 1.40; 95% confidence interval [CI], 1.15-1.71 vs. aHR, 0.95; 95% CI, 0.83-1.09), combined HT use (aHR, 2.07; 95% CI, 1.72-2.48 vs. aHR, 1.45; 95% CI, 1.27-1.65), and BBD history (aHR, 95% CI, 1.85; 1.64-2.08 vs. aHR, 1.43; 95% CI, 1.33-1.55). Factors more strongly associated with scrn-BC vs. sym-BC risk were alcohol intake (per drink aHR, 1.28; 95% CI, 1.18-1.39 vs. aHR, 1.07; 95% CI, 0.94-1.22) and body mass index ³30 kg/m2 (aHR, 1.22; 95% CI, 1.01-1.48 vs. aHR, 0.76; 95% CI, 0.56-1.01).
Study details: The data come from an analysis of 77,206 women followed-up for a median of 14.8 years. BC was detected through screening or by symptoms in 2,711 and 1,281 women, respectively.
Disclosures: The study was supported by the American Cancer Society. The authors declared no conflicts of interest.
Source: Gaudet MM et al. Breast Cancer Res Treat. 2021 Jan 4. doi: 10.1007/s10549-020-06025-2.
Key clinical point: Hormone therapy (HT) use and benign breast disease (BBD) history are more strongly associated with a higher risk for symptom-detected breast cancer (sym-BC), whereas alcohol intake and obesity are associated with an increased screen-detected BC (scrn-BC) risk.
Major finding: Factors more strongly associated with higher sym-BC vs. scrn-BC risk were estrogen HT use (adjusted hazard ratio [aHR], 1.40; 95% confidence interval [CI], 1.15-1.71 vs. aHR, 0.95; 95% CI, 0.83-1.09), combined HT use (aHR, 2.07; 95% CI, 1.72-2.48 vs. aHR, 1.45; 95% CI, 1.27-1.65), and BBD history (aHR, 95% CI, 1.85; 1.64-2.08 vs. aHR, 1.43; 95% CI, 1.33-1.55). Factors more strongly associated with scrn-BC vs. sym-BC risk were alcohol intake (per drink aHR, 1.28; 95% CI, 1.18-1.39 vs. aHR, 1.07; 95% CI, 0.94-1.22) and body mass index ³30 kg/m2 (aHR, 1.22; 95% CI, 1.01-1.48 vs. aHR, 0.76; 95% CI, 0.56-1.01).
Study details: The data come from an analysis of 77,206 women followed-up for a median of 14.8 years. BC was detected through screening or by symptoms in 2,711 and 1,281 women, respectively.
Disclosures: The study was supported by the American Cancer Society. The authors declared no conflicts of interest.
Source: Gaudet MM et al. Breast Cancer Res Treat. 2021 Jan 4. doi: 10.1007/s10549-020-06025-2.
Key clinical point: Hormone therapy (HT) use and benign breast disease (BBD) history are more strongly associated with a higher risk for symptom-detected breast cancer (sym-BC), whereas alcohol intake and obesity are associated with an increased screen-detected BC (scrn-BC) risk.
Major finding: Factors more strongly associated with higher sym-BC vs. scrn-BC risk were estrogen HT use (adjusted hazard ratio [aHR], 1.40; 95% confidence interval [CI], 1.15-1.71 vs. aHR, 0.95; 95% CI, 0.83-1.09), combined HT use (aHR, 2.07; 95% CI, 1.72-2.48 vs. aHR, 1.45; 95% CI, 1.27-1.65), and BBD history (aHR, 95% CI, 1.85; 1.64-2.08 vs. aHR, 1.43; 95% CI, 1.33-1.55). Factors more strongly associated with scrn-BC vs. sym-BC risk were alcohol intake (per drink aHR, 1.28; 95% CI, 1.18-1.39 vs. aHR, 1.07; 95% CI, 0.94-1.22) and body mass index ³30 kg/m2 (aHR, 1.22; 95% CI, 1.01-1.48 vs. aHR, 0.76; 95% CI, 0.56-1.01).
Study details: The data come from an analysis of 77,206 women followed-up for a median of 14.8 years. BC was detected through screening or by symptoms in 2,711 and 1,281 women, respectively.
Disclosures: The study was supported by the American Cancer Society. The authors declared no conflicts of interest.
Source: Gaudet MM et al. Breast Cancer Res Treat. 2021 Jan 4. doi: 10.1007/s10549-020-06025-2.
HER+ early breast cancer: Fixed-dose SC pertuzumab-trastuzumab noninferior to IV dosing
Key clinical point: Fixed-dose combination of pertuzumab and trastuzumab for subcutaneous (SC) injection was noninferior to intravenous (IV) dosing in patients with human epidermal growth factor receptor 2-positive (HER2+) early breast cancer.
Major finding: Geometric mean ratio of cycle 7 pertuzumab serum Ctrough of the SC group to the IV group was 1.22 (90% confidence interval, 1.14-1.31). Total pathologic complete response was achieved by 59.5% and 59.7% of patients in IV and SC groups, respectively. Common grade 3-4 adverse events were similar.
Study details: In the phase 3 FeDeriCa trial, patients with HER2+ early breast cancer were randomly assigned to receive either fixed-dose SC (n = 248) or IV (n = 252) pertuzumab and trastuzumab along with neoadjuvant chemotherapy.
Disclosures: This study was funded by F Hoffmann-La Roche and Genentech. The lead author AR Tan reported receving financial support from F Hoffmann-La Roche, Genentech, Pfizer, Merck, Tesaro, Novartis, Immunomedics, Celgene, and AbbVie. His coauthors also reported relationships with various pharmaceutical companies including F Hoffmann-La Roche and Genentech.
Source: Tan AR et al. Lancet Oncol. 2020 Dec 21. doi: 10.1016/S1470-2045(20)30536-2.
Key clinical point: Fixed-dose combination of pertuzumab and trastuzumab for subcutaneous (SC) injection was noninferior to intravenous (IV) dosing in patients with human epidermal growth factor receptor 2-positive (HER2+) early breast cancer.
Major finding: Geometric mean ratio of cycle 7 pertuzumab serum Ctrough of the SC group to the IV group was 1.22 (90% confidence interval, 1.14-1.31). Total pathologic complete response was achieved by 59.5% and 59.7% of patients in IV and SC groups, respectively. Common grade 3-4 adverse events were similar.
Study details: In the phase 3 FeDeriCa trial, patients with HER2+ early breast cancer were randomly assigned to receive either fixed-dose SC (n = 248) or IV (n = 252) pertuzumab and trastuzumab along with neoadjuvant chemotherapy.
Disclosures: This study was funded by F Hoffmann-La Roche and Genentech. The lead author AR Tan reported receving financial support from F Hoffmann-La Roche, Genentech, Pfizer, Merck, Tesaro, Novartis, Immunomedics, Celgene, and AbbVie. His coauthors also reported relationships with various pharmaceutical companies including F Hoffmann-La Roche and Genentech.
Source: Tan AR et al. Lancet Oncol. 2020 Dec 21. doi: 10.1016/S1470-2045(20)30536-2.
Key clinical point: Fixed-dose combination of pertuzumab and trastuzumab for subcutaneous (SC) injection was noninferior to intravenous (IV) dosing in patients with human epidermal growth factor receptor 2-positive (HER2+) early breast cancer.
Major finding: Geometric mean ratio of cycle 7 pertuzumab serum Ctrough of the SC group to the IV group was 1.22 (90% confidence interval, 1.14-1.31). Total pathologic complete response was achieved by 59.5% and 59.7% of patients in IV and SC groups, respectively. Common grade 3-4 adverse events were similar.
Study details: In the phase 3 FeDeriCa trial, patients with HER2+ early breast cancer were randomly assigned to receive either fixed-dose SC (n = 248) or IV (n = 252) pertuzumab and trastuzumab along with neoadjuvant chemotherapy.
Disclosures: This study was funded by F Hoffmann-La Roche and Genentech. The lead author AR Tan reported receving financial support from F Hoffmann-La Roche, Genentech, Pfizer, Merck, Tesaro, Novartis, Immunomedics, Celgene, and AbbVie. His coauthors also reported relationships with various pharmaceutical companies including F Hoffmann-La Roche and Genentech.
Source: Tan AR et al. Lancet Oncol. 2020 Dec 21. doi: 10.1016/S1470-2045(20)30536-2.