Breast Cancer

In this Practical AI column, we’ve explored everything from large language models to the nuances of trial matching, but one of the most immediate and impactful applications of AI is unfolding right now in breast imaging. For oncologists, this isn’t an abstract future — with new screening guidelines, dense-breast mandates, and a shrinking radiology workforce, it’s the imaging reports and patient questions landing in your clinic today.

Here is what oncologists need to know, and how to put it to work for their patients.

 

Why AI in Mammography Matters

More than 200 million women undergo breast cancer screening each year. In the US alone, 10% of the 40 million women screened annually require additional diagnostic imaging, and 4%–5% of these women are eventually diagnosed with breast cancer.

Two major shifts are redefining breast cancer screening in the US: The US Preventive Services Task Force (USPSTF) now recommends biennial screening from age 40 to 74 years, and notifying patients of breast density is a federal requirement as of September 10, 2024. That means more mammograms, more patient questions, and more downstream oncology decisions. Patients will increasingly ask about “dense” breast results and what to do next. Add a national radiologist shortage into the mix, and the pressure on timely callbacks, biopsies, and treatment planning will only grow.

 

Can AI Help Without Compromising Care?

The short answer is yes. With AI, we may be able to transform these rate-limiting steps into opportunities for earlier detection, decentralized screening, and smarter triage and save hundreds of thousands of women from an unnecessary diagnostic procedure, if implemented deliberately.

Don’t Confuse Today’s AI With Yesterday’s CAD 

Think of older computer-aided detection (CAD) like a 1990s chemotherapy drug: It sometimes helped, but it came with significant toxicity and rarely delivered consistent survival benefits. Today’s deep-learning AI is closer to targeted therapy — trained on millions of “trial participants” (mammograms), more precise, and applied in specific contexts where it adds value. If you once dismissed CAD as noise, it’s time to revisit what AI can now offer.

The role of AI is broader than drawing boxes. It provides second readings, worklist triage, risk prediction, density assessment, and decision support. FDA has cleared several AI tools for both 2D and digital breast tomosynthesis (DBT), which include iCAD ProFound (DBT), ScreenPoint Transpara (2D/DBT), and Lunit INSIGHT DBT. 

Some of the strongest evidence for AI in mammography is as a second reader during screening. Large trials show that AI plus one radiologist can match reading from two radiologists, cutting workload by about 40%. For example, the MASAI randomized trial showed that AI-supported screening achieved similar cancer detection but cut human screen-reading workload about 44% vs standard double reading (39,996 vs 40,024 participants). The primary interval cancer outcomes are maturing, but the safety analysis is reassuring.

Reducing second reads and arbitration time are important for clinicians because it frees capacity for callbacks and diagnostic workups. This will be especially key given that screening now starts at age 40. That will mean about 21 to 22 million more women are newly eligible, translating to about 10 to 11 million additional mammograms each year under biennial screening.

Another important area where AI can make its mark in mammography is triage and time to diagnosis. The results from a randomized implementation study showed that AI-prioritized worklists accelerated time to additional imaging and biopsy diagnosis without harming efficiency for others — exactly the kind of outcome patients feel.

Multiple studies have demonstrated improved diagnostic performance and shorter reading times when AI supports DBT interpretation, which is important because DBT can otherwise be time intensive.

We are also seeing rapid advancement in risk-based screening, moving beyond a single dense vs not dense approach. Deep-learning risk models, such as Mirai, predict 1- to 5-year breast cancer risk directly from the mammogram, and these tools are now being assessed prospectively to guide supplemental MRI. Cost-effectiveness modeling supports risk-stratified intervals vs one-size-fits-all schedules.

Finally, automated density tools, such as Transpara Density and Volpara, offer objective, reproducible volumetric measures that map to the Breast Imaging-Reporting and Data System, which is useful for Mammography Quality Standards Act-required reporting and as inputs to risk calculators.

While early evidence suggests AI may help surface future or interval cancers earlier, including more invasive tumors, the definitive impacts on interval cancer rates and mortality require longitudinal follow-up, which is now in progress.

 

Pitfalls to Watch For

Bias is real. Studies show false-positive differences by race, age, and density. AI can even infer racial identity from images, potentially amplifying disparities. Performance can also shift by vendor, demographics, and prevalence.

A Radiology study of 4855 DBT exams showed that an algorithm produced more false-positive case scores in Black patients and older patients (aged 71-80 years) patients and in women with extremely dense breasts. This can happen because AI can infer proxies for race directly from images, even when humans cannot, and this can propagate disparities if not addressed. External validations and reviews emphasize that performance can shift with device manufacturer, demographics, and prevalence, which is why all tools need to undergo local validation and calibration. 

Here’s a pragmatic adoption checklist before going live with an AI tool.

• Confirm FDA clearance: Verify the name and version of the algorithm, imaging modes (2D vs DBT), and operating points. Confirm 510(k) numbers.
• Local validation: Test on your patient mix and vendor stack (Hologic, GE, Siemens, Fuji). Compare this to your baseline recall rate, positive predictive value of recall (PPV1), cancer detection rate, and reading time. Commit to recalibration if drift occurs.
• Equity plan: Monitor false-positive and negative false-rates by age, race/ethnicity, and density; document corrective actions if disparities emerge. (This isn’t optional.)
• Workflow clarity: Is AI a second reader, an additional reader, or a triage tool? Who arbitrates discordance? What’s the escalation path for high-risk or interval cancer-like patterns?
• Regulatory strategy: Confirm whether the vendor has (or will file) a Predetermined Change Control Plan so models can be updated safely without repeated submissions. Also confirm how you’ll be notified about performance-relevant changes.
• Data governance: Audit logs of AI outputs, retention, protected health information handling, and the patient communication policy for AI-assisted reads.

After going live, set up a quarterly dashboard. It should include cancer detection rate per 1000 patients, recall rate, PPV1, interval cancer rate (as it matures), reading time, and turnaround time to diagnostic imaging or biopsy — all stratified by age, race/ethnicity, and density.

Here, I dissect what this discussion means through the lens of Moravec’s paradox (machines excel at what clinicians find hard, and vice versa) and offer a possible playbook for putting these tools to work.

 

What to Tell Patients

When speaking with patients, emphasize that a radiologist still reads their mammogram. AI helps with consistency and efficiency; it doesn’t replace human oversight. Patients with dense breasts should still expect a standard notice; discussion of individualized risk factors, such as family history, genetics, and prior biopsies; and consideration of supplemental imaging if risk warrants. But it’s also important to tell these patients that while dense breasts are common, they do not automatically mean high cancer risk.

As for screening schedules, remind patients that screening is at least biennial from 40 to 74 years of age per the USPSTF guidelines; however, specialty groups may recommend starting on an annual schedule at 40.

 

What You Can Implement Now

There are multiple practical use cases you can introduce now. One is to use AI as a second reader or an additional reader safety net to preserve detection while reducing human workload. This helps your breast center absorb screening expansion to age 40 without diluting quality. Another is to turn on AI triage to shorten the time to callback and biopsy for the few who need it most — patients notice and appreciate faster answers. You can also begin adopting automated density plus risk models to move beyond “dense/not dense.” For selected patients, AI-informed risk can justify MRI or tailored intervals. 

Here’s a quick cheat sheet (for your next leadership or tumor-board meeting).

 

Do:

• Use AI as a second or additional reader or triage tool, not as a black box.
• Track cancer detection rate, recall, PPV1, interval cancers, and reading time, stratified by age, race, and breast density.
• Pair automated density with AI risk to personalize screening and supplemental imaging.
• Enroll patients in future clinical trials, such as PRISM, the first large-scale randomized controlled trial of AI for screening mammography. This US-based, $16 million, seven-site study is funded by the Patient-Centered Outcomes Research Institute.

Don’t:

• Assume “AI = CAD.” The 2015 CAD story is over; modern deep learning systems are different and require different oversight.
• Go live without a local validation and equity plan or without clarity on software updates.
• Forget to remind patients that screening starts at age 40, and dense breast notifications are now universal. Use the visit to discuss risk, supplemental imaging, and why a human still directs their care.

The Bottom Line

AI won’t replace radiologists or read mammograms for us — just as PET scans didn’t replace oncologists and stethoscopes didn’t make cardiologists obsolete. What it will do is catch what the tired human eye might miss, shave days off anxious waiting, and turn breast density into data instead of doubt. For oncologists, that means staging sooner, enrolling smarter, and spending more time talking with patients instead of chasing callbacks.

In short, AI may not take the picture, but it helps us frame the story, making it sharper, faster, and with fewer blind spots. By pairing this powerful technology with rigorous, equity-focused local validation and transparent governance under the FDA’s emerging Predetermined Change Control Plan framework, we can realize the tangible benefits of practical AI for our patients without widening disparities. 

Now, during Breast Cancer Awareness Month, how about we add on AI to that pink ribbon — how cool would that be?

Thoughts? Drop me a line at [email protected]. Let’s keep the conversation — and pink ribbons — going.

Arturo Loaiza-Bonilla, MD, MSEd, is the co-founder and chief medical AI officer at Massive Bio, a company connecting patients to clinical trials using artificial intelligence. His research and professional interests focus on precision medicine, clinical trial design, digital health, entrepreneurship, and patient advocacy. Dr Loaiza-Bonilla serves as Systemwide Chief of Hematology and Oncology at St. Luke’s University Health Network, where he maintains a connection to patient care by attending to patients 2 days a week.

A version of this article first appeared on Medscape.com.

In this Practical AI column, we’ve explored everything from large language models to the nuances of trial matching, but one of the most immediate and impactful applications of AI is unfolding right now in breast imaging. For oncologists, this isn’t an abstract future — with new screening guidelines, dense-breast mandates, and a shrinking radiology workforce, it’s the imaging reports and patient questions landing in your clinic today.

Here is what oncologists need to know, and how to put it to work for their patients.

 

Why AI in Mammography Matters

More than 200 million women undergo breast cancer screening each year. In the US alone, 10% of the 40 million women screened annually require additional diagnostic imaging, and 4%–5% of these women are eventually diagnosed with breast cancer.

Two major shifts are redefining breast cancer screening in the US: The US Preventive Services Task Force (USPSTF) now recommends biennial screening from age 40 to 74 years, and notifying patients of breast density is a federal requirement as of September 10, 2024. That means more mammograms, more patient questions, and more downstream oncology decisions. Patients will increasingly ask about “dense” breast results and what to do next. Add a national radiologist shortage into the mix, and the pressure on timely callbacks, biopsies, and treatment planning will only grow.

 

Can AI Help Without Compromising Care?

The short answer is yes. With AI, we may be able to transform these rate-limiting steps into opportunities for earlier detection, decentralized screening, and smarter triage and save hundreds of thousands of women from an unnecessary diagnostic procedure, if implemented deliberately.

Don’t Confuse Today’s AI With Yesterday’s CAD 

Think of older computer-aided detection (CAD) like a 1990s chemotherapy drug: It sometimes helped, but it came with significant toxicity and rarely delivered consistent survival benefits. Today’s deep-learning AI is closer to targeted therapy — trained on millions of “trial participants” (mammograms), more precise, and applied in specific contexts where it adds value. If you once dismissed CAD as noise, it’s time to revisit what AI can now offer.

The role of AI is broader than drawing boxes. It provides second readings, worklist triage, risk prediction, density assessment, and decision support. FDA has cleared several AI tools for both 2D and digital breast tomosynthesis (DBT), which include iCAD ProFound (DBT), ScreenPoint Transpara (2D/DBT), and Lunit INSIGHT DBT. 

Some of the strongest evidence for AI in mammography is as a second reader during screening. Large trials show that AI plus one radiologist can match reading from two radiologists, cutting workload by about 40%. For example, the MASAI randomized trial showed that AI-supported screening achieved similar cancer detection but cut human screen-reading workload about 44% vs standard double reading (39,996 vs 40,024 participants). The primary interval cancer outcomes are maturing, but the safety analysis is reassuring.

Reducing second reads and arbitration time are important for clinicians because it frees capacity for callbacks and diagnostic workups. This will be especially key given that screening now starts at age 40. That will mean about 21 to 22 million more women are newly eligible, translating to about 10 to 11 million additional mammograms each year under biennial screening.

Another important area where AI can make its mark in mammography is triage and time to diagnosis. The results from a randomized implementation study showed that AI-prioritized worklists accelerated time to additional imaging and biopsy diagnosis without harming efficiency for others — exactly the kind of outcome patients feel.

Multiple studies have demonstrated improved diagnostic performance and shorter reading times when AI supports DBT interpretation, which is important because DBT can otherwise be time intensive.

We are also seeing rapid advancement in risk-based screening, moving beyond a single dense vs not dense approach. Deep-learning risk models, such as Mirai, predict 1- to 5-year breast cancer risk directly from the mammogram, and these tools are now being assessed prospectively to guide supplemental MRI. Cost-effectiveness modeling supports risk-stratified intervals vs one-size-fits-all schedules.

Finally, automated density tools, such as Transpara Density and Volpara, offer objective, reproducible volumetric measures that map to the Breast Imaging-Reporting and Data System, which is useful for Mammography Quality Standards Act-required reporting and as inputs to risk calculators.

While early evidence suggests AI may help surface future or interval cancers earlier, including more invasive tumors, the definitive impacts on interval cancer rates and mortality require longitudinal follow-up, which is now in progress.

 

Pitfalls to Watch For

Bias is real. Studies show false-positive differences by race, age, and density. AI can even infer racial identity from images, potentially amplifying disparities. Performance can also shift by vendor, demographics, and prevalence.

A Radiology study of 4855 DBT exams showed that an algorithm produced more false-positive case scores in Black patients and older patients (aged 71-80 years) patients and in women with extremely dense breasts. This can happen because AI can infer proxies for race directly from images, even when humans cannot, and this can propagate disparities if not addressed. External validations and reviews emphasize that performance can shift with device manufacturer, demographics, and prevalence, which is why all tools need to undergo local validation and calibration. 

Here’s a pragmatic adoption checklist before going live with an AI tool.

• Confirm FDA clearance: Verify the name and version of the algorithm, imaging modes (2D vs DBT), and operating points. Confirm 510(k) numbers.
• Local validation: Test on your patient mix and vendor stack (Hologic, GE, Siemens, Fuji). Compare this to your baseline recall rate, positive predictive value of recall (PPV1), cancer detection rate, and reading time. Commit to recalibration if drift occurs.
• Equity plan: Monitor false-positive and negative false-rates by age, race/ethnicity, and density; document corrective actions if disparities emerge. (This isn’t optional.)
• Workflow clarity: Is AI a second reader, an additional reader, or a triage tool? Who arbitrates discordance? What’s the escalation path for high-risk or interval cancer-like patterns?
• Regulatory strategy: Confirm whether the vendor has (or will file) a Predetermined Change Control Plan so models can be updated safely without repeated submissions. Also confirm how you’ll be notified about performance-relevant changes.
• Data governance: Audit logs of AI outputs, retention, protected health information handling, and the patient communication policy for AI-assisted reads.

After going live, set up a quarterly dashboard. It should include cancer detection rate per 1000 patients, recall rate, PPV1, interval cancer rate (as it matures), reading time, and turnaround time to diagnostic imaging or biopsy — all stratified by age, race/ethnicity, and density.

Here, I dissect what this discussion means through the lens of Moravec’s paradox (machines excel at what clinicians find hard, and vice versa) and offer a possible playbook for putting these tools to work.

 

What to Tell Patients

When speaking with patients, emphasize that a radiologist still reads their mammogram. AI helps with consistency and efficiency; it doesn’t replace human oversight. Patients with dense breasts should still expect a standard notice; discussion of individualized risk factors, such as family history, genetics, and prior biopsies; and consideration of supplemental imaging if risk warrants. But it’s also important to tell these patients that while dense breasts are common, they do not automatically mean high cancer risk.

As for screening schedules, remind patients that screening is at least biennial from 40 to 74 years of age per the USPSTF guidelines; however, specialty groups may recommend starting on an annual schedule at 40.

 

What You Can Implement Now

There are multiple practical use cases you can introduce now. One is to use AI as a second reader or an additional reader safety net to preserve detection while reducing human workload. This helps your breast center absorb screening expansion to age 40 without diluting quality. Another is to turn on AI triage to shorten the time to callback and biopsy for the few who need it most — patients notice and appreciate faster answers. You can also begin adopting automated density plus risk models to move beyond “dense/not dense.” For selected patients, AI-informed risk can justify MRI or tailored intervals. 

Here’s a quick cheat sheet (for your next leadership or tumor-board meeting).

 

Do:

• Use AI as a second or additional reader or triage tool, not as a black box.
• Track cancer detection rate, recall, PPV1, interval cancers, and reading time, stratified by age, race, and breast density.
• Pair automated density with AI risk to personalize screening and supplemental imaging.
• Enroll patients in future clinical trials, such as PRISM, the first large-scale randomized controlled trial of AI for screening mammography. This US-based, $16 million, seven-site study is funded by the Patient-Centered Outcomes Research Institute.

Don’t:

• Assume “AI = CAD.” The 2015 CAD story is over; modern deep learning systems are different and require different oversight.
• Go live without a local validation and equity plan or without clarity on software updates.
• Forget to remind patients that screening starts at age 40, and dense breast notifications are now universal. Use the visit to discuss risk, supplemental imaging, and why a human still directs their care.

The Bottom Line

AI won’t replace radiologists or read mammograms for us — just as PET scans didn’t replace oncologists and stethoscopes didn’t make cardiologists obsolete. What it will do is catch what the tired human eye might miss, shave days off anxious waiting, and turn breast density into data instead of doubt. For oncologists, that means staging sooner, enrolling smarter, and spending more time talking with patients instead of chasing callbacks.

In short, AI may not take the picture, but it helps us frame the story, making it sharper, faster, and with fewer blind spots. By pairing this powerful technology with rigorous, equity-focused local validation and transparent governance under the FDA’s emerging Predetermined Change Control Plan framework, we can realize the tangible benefits of practical AI for our patients without widening disparities. 

Now, during Breast Cancer Awareness Month, how about we add on AI to that pink ribbon — how cool would that be?

Thoughts? Drop me a line at [email protected]. Let’s keep the conversation — and pink ribbons — going.

Arturo Loaiza-Bonilla, MD, MSEd, is the co-founder and chief medical AI officer at Massive Bio, a company connecting patients to clinical trials using artificial intelligence. His research and professional interests focus on precision medicine, clinical trial design, digital health, entrepreneurship, and patient advocacy. Dr Loaiza-Bonilla serves as Systemwide Chief of Hematology and Oncology at St. Luke’s University Health Network, where he maintains a connection to patient care by attending to patients 2 days a week.

A version of this article first appeared on Medscape.com.

In this Practical AI column, we’ve explored everything from large language models to the nuances of trial matching, but one of the most immediate and impactful applications of AI is unfolding right now in breast imaging. For oncologists, this isn’t an abstract future — with new screening guidelines, dense-breast mandates, and a shrinking radiology workforce, it’s the imaging reports and patient questions landing in your clinic today.

Here is what oncologists need to know, and how to put it to work for their patients.

 

Why AI in Mammography Matters

More than 200 million women undergo breast cancer screening each year. In the US alone, 10% of the 40 million women screened annually require additional diagnostic imaging, and 4%–5% of these women are eventually diagnosed with breast cancer.

Two major shifts are redefining breast cancer screening in the US: The US Preventive Services Task Force (USPSTF) now recommends biennial screening from age 40 to 74 years, and notifying patients of breast density is a federal requirement as of September 10, 2024. That means more mammograms, more patient questions, and more downstream oncology decisions. Patients will increasingly ask about “dense” breast results and what to do next. Add a national radiologist shortage into the mix, and the pressure on timely callbacks, biopsies, and treatment planning will only grow.

 

Can AI Help Without Compromising Care?

The short answer is yes. With AI, we may be able to transform these rate-limiting steps into opportunities for earlier detection, decentralized screening, and smarter triage and save hundreds of thousands of women from an unnecessary diagnostic procedure, if implemented deliberately.

Don’t Confuse Today’s AI With Yesterday’s CAD 

Think of older computer-aided detection (CAD) like a 1990s chemotherapy drug: It sometimes helped, but it came with significant toxicity and rarely delivered consistent survival benefits. Today’s deep-learning AI is closer to targeted therapy — trained on millions of “trial participants” (mammograms), more precise, and applied in specific contexts where it adds value. If you once dismissed CAD as noise, it’s time to revisit what AI can now offer.

The role of AI is broader than drawing boxes. It provides second readings, worklist triage, risk prediction, density assessment, and decision support. FDA has cleared several AI tools for both 2D and digital breast tomosynthesis (DBT), which include iCAD ProFound (DBT), ScreenPoint Transpara (2D/DBT), and Lunit INSIGHT DBT. 

Some of the strongest evidence for AI in mammography is as a second reader during screening. Large trials show that AI plus one radiologist can match reading from two radiologists, cutting workload by about 40%. For example, the MASAI randomized trial showed that AI-supported screening achieved similar cancer detection but cut human screen-reading workload about 44% vs standard double reading (39,996 vs 40,024 participants). The primary interval cancer outcomes are maturing, but the safety analysis is reassuring.

Reducing second reads and arbitration time are important for clinicians because it frees capacity for callbacks and diagnostic workups. This will be especially key given that screening now starts at age 40. That will mean about 21 to 22 million more women are newly eligible, translating to about 10 to 11 million additional mammograms each year under biennial screening.

Another important area where AI can make its mark in mammography is triage and time to diagnosis. The results from a randomized implementation study showed that AI-prioritized worklists accelerated time to additional imaging and biopsy diagnosis without harming efficiency for others — exactly the kind of outcome patients feel.

Multiple studies have demonstrated improved diagnostic performance and shorter reading times when AI supports DBT interpretation, which is important because DBT can otherwise be time intensive.

We are also seeing rapid advancement in risk-based screening, moving beyond a single dense vs not dense approach. Deep-learning risk models, such as Mirai, predict 1- to 5-year breast cancer risk directly from the mammogram, and these tools are now being assessed prospectively to guide supplemental MRI. Cost-effectiveness modeling supports risk-stratified intervals vs one-size-fits-all schedules.

Finally, automated density tools, such as Transpara Density and Volpara, offer objective, reproducible volumetric measures that map to the Breast Imaging-Reporting and Data System, which is useful for Mammography Quality Standards Act-required reporting and as inputs to risk calculators.

While early evidence suggests AI may help surface future or interval cancers earlier, including more invasive tumors, the definitive impacts on interval cancer rates and mortality require longitudinal follow-up, which is now in progress.

 

Pitfalls to Watch For

Bias is real. Studies show false-positive differences by race, age, and density. AI can even infer racial identity from images, potentially amplifying disparities. Performance can also shift by vendor, demographics, and prevalence.

A Radiology study of 4855 DBT exams showed that an algorithm produced more false-positive case scores in Black patients and older patients (aged 71-80 years) patients and in women with extremely dense breasts. This can happen because AI can infer proxies for race directly from images, even when humans cannot, and this can propagate disparities if not addressed. External validations and reviews emphasize that performance can shift with device manufacturer, demographics, and prevalence, which is why all tools need to undergo local validation and calibration. 

Here’s a pragmatic adoption checklist before going live with an AI tool.

• Confirm FDA clearance: Verify the name and version of the algorithm, imaging modes (2D vs DBT), and operating points. Confirm 510(k) numbers.
• Local validation: Test on your patient mix and vendor stack (Hologic, GE, Siemens, Fuji). Compare this to your baseline recall rate, positive predictive value of recall (PPV1), cancer detection rate, and reading time. Commit to recalibration if drift occurs.
• Equity plan: Monitor false-positive and negative false-rates by age, race/ethnicity, and density; document corrective actions if disparities emerge. (This isn’t optional.)
• Workflow clarity: Is AI a second reader, an additional reader, or a triage tool? Who arbitrates discordance? What’s the escalation path for high-risk or interval cancer-like patterns?
• Regulatory strategy: Confirm whether the vendor has (or will file) a Predetermined Change Control Plan so models can be updated safely without repeated submissions. Also confirm how you’ll be notified about performance-relevant changes.
• Data governance: Audit logs of AI outputs, retention, protected health information handling, and the patient communication policy for AI-assisted reads.

After going live, set up a quarterly dashboard. It should include cancer detection rate per 1000 patients, recall rate, PPV1, interval cancer rate (as it matures), reading time, and turnaround time to diagnostic imaging or biopsy — all stratified by age, race/ethnicity, and density.

Here, I dissect what this discussion means through the lens of Moravec’s paradox (machines excel at what clinicians find hard, and vice versa) and offer a possible playbook for putting these tools to work.

 

What to Tell Patients

When speaking with patients, emphasize that a radiologist still reads their mammogram. AI helps with consistency and efficiency; it doesn’t replace human oversight. Patients with dense breasts should still expect a standard notice; discussion of individualized risk factors, such as family history, genetics, and prior biopsies; and consideration of supplemental imaging if risk warrants. But it’s also important to tell these patients that while dense breasts are common, they do not automatically mean high cancer risk.

As for screening schedules, remind patients that screening is at least biennial from 40 to 74 years of age per the USPSTF guidelines; however, specialty groups may recommend starting on an annual schedule at 40.

 

What You Can Implement Now

There are multiple practical use cases you can introduce now. One is to use AI as a second reader or an additional reader safety net to preserve detection while reducing human workload. This helps your breast center absorb screening expansion to age 40 without diluting quality. Another is to turn on AI triage to shorten the time to callback and biopsy for the few who need it most — patients notice and appreciate faster answers. You can also begin adopting automated density plus risk models to move beyond “dense/not dense.” For selected patients, AI-informed risk can justify MRI or tailored intervals. 

Here’s a quick cheat sheet (for your next leadership or tumor-board meeting).

 

Do:

• Use AI as a second or additional reader or triage tool, not as a black box.
• Track cancer detection rate, recall, PPV1, interval cancers, and reading time, stratified by age, race, and breast density.
• Pair automated density with AI risk to personalize screening and supplemental imaging.
• Enroll patients in future clinical trials, such as PRISM, the first large-scale randomized controlled trial of AI for screening mammography. This US-based, $16 million, seven-site study is funded by the Patient-Centered Outcomes Research Institute.

Don’t:

• Assume “AI = CAD.” The 2015 CAD story is over; modern deep learning systems are different and require different oversight.
• Go live without a local validation and equity plan or without clarity on software updates.
• Forget to remind patients that screening starts at age 40, and dense breast notifications are now universal. Use the visit to discuss risk, supplemental imaging, and why a human still directs their care.

The Bottom Line

AI won’t replace radiologists or read mammograms for us — just as PET scans didn’t replace oncologists and stethoscopes didn’t make cardiologists obsolete. What it will do is catch what the tired human eye might miss, shave days off anxious waiting, and turn breast density into data instead of doubt. For oncologists, that means staging sooner, enrolling smarter, and spending more time talking with patients instead of chasing callbacks.

In short, AI may not take the picture, but it helps us frame the story, making it sharper, faster, and with fewer blind spots. By pairing this powerful technology with rigorous, equity-focused local validation and transparent governance under the FDA’s emerging Predetermined Change Control Plan framework, we can realize the tangible benefits of practical AI for our patients without widening disparities. 

Now, during Breast Cancer Awareness Month, how about we add on AI to that pink ribbon — how cool would that be?

Thoughts? Drop me a line at [email protected]. Let’s keep the conversation — and pink ribbons — going.

Arturo Loaiza-Bonilla, MD, MSEd, is the co-founder and chief medical AI officer at Massive Bio, a company connecting patients to clinical trials using artificial intelligence. His research and professional interests focus on precision medicine, clinical trial design, digital health, entrepreneurship, and patient advocacy. Dr Loaiza-Bonilla serves as Systemwide Chief of Hematology and Oncology at St. Luke’s University Health Network, where he maintains a connection to patient care by attending to patients 2 days a week.

A version of this article first appeared on Medscape.com.

Patients with breast cancer who undergo chemotherapy may face an increased risk for brain atrophy and cognitive decline, new findings from a pilot study suggest.

Memory problems in patients with cancer may not stem solely from stress or anxiety related to their diagnosis but could reflect underlying changes in brain structure, study investigator Paul Edison, PhD, MPhil, professor of neuroscience and clinical professor of neurology at Imperial College London, England, told this news organization.

While the findings suggest that chemotherapy may contribute to neuronal damage, the researchers noted that many aspects of the relationship between treatment and brain changes remain unclear.

Edison highlighted three key areas that require further investigation — uncovering the mechanisms driving brain atrophy, determining the proportion of patients affected, and identifying effective prevention strategies.

Another investigator on the study, Laura Kenny, MD, PhD, associate professor and consultant medical oncologist at Imperial College London, noted that the issue has received limited attention to date but expressed hope that the findings will raise awareness and encourage further research, given its clinical importance.

The findings were presented on July 29 at the Alzheimer’s Association International Conference (AAIC) 2025.

 

Investigating Cognitive Impact

Advances in chemotherapeutic agents have improved survival rates in patients with cancer. However, challenges persist regarding the long-term impact of these drugs.

Chemotherapy-associated cognitive impairment, often referred to as “brain fog” or “chemobrain,” affects approximately one third of patients with breast cancer following treatment.

While cognitive decline resolves within 12 months for some patients, others experience persistent effects that may elevate the risk for neurodegenerative conditions, Edison explained.

To evaluate the impact of chemotherapy on the brain, investigators studied 328 women with nonmetastatic breast cancer who had undergone chemotherapy within the past 12 months.

Patients received either anthracycline — a drug derived from the Streptomyces peucetius bacterium — or taxanes such as docetaxel and paclitaxel, both commonly used in breast cancer treatment, or a combination of these agents. In addition, some patients may also have had hormone therapy at some point during treatment, said Kenny.

Participants completed neurocognitive prescreening tests every 3 months using a specialized artificial intelligence–driven platform, allowing them to take detailed memory assessments online from home.

Among those prescreened, 18 individuals with lower neurocognitive scores (mean age, 55 years) and 19 cognitively normal control individuals without breast cancer (mean age, 67 years) underwent comprehensive, in-person, neurocognitive evaluations and MRI scans.

Researchers analyzed the scans using region of interest (ROI) and voxel-based morphometry (VBM), which uses sophisticated computer software, to assess gray matter volumes and surface areas.

The ROI analysis revealed significant reductions in gray matter volume (measured in mm³) and surface area (measured in mm²) among patients experiencing chemobrain, particularly affecting the isthmus cingulate and pars opercularis, with changes extending into the orbitofrontal and temporal regions.

 

Significant Atrophy

The VBM analysis confirmed significant atrophy in the frontal, parietal, and cingulate regions of patients with chemobrain compared with control individuals (P < .05). Edison noted that this pattern overlaps with brain changes typically observed in Alzheimer’s disease and vascular cognitive impairment.

For both analyses, “we demonstrated there is some amount of shrinkage in the brain among patients with chemobrain,” he said. “The fact that controls are older means the results are even more significant as there’s more brain atrophy as people age.”

Some of the affected brain regions may be linked to impaired memory, a hallmark of Alzheimer’s disease, but Edison cautioned that given the small sample size this finding should be interpreted with caution.

While the analysis demonstrated overall lower brain volumes in patients with “chemobrain” compared with controls, Edison emphasized that this finding reflects a single time point and does not indicate brain shrinkage over time.

Other events, including stroke — can also cause brain changes.

Edison highlighted the importance of determining the significance of these brain changes, how they affect patients and whether they can be prevented.

In-person neurocognitive testing revealed significantly reduced semantic and verbal fluency, as well as lower Mini-Mental State Examination scores in patients with chemobrain. Edison noted that these results support the MRI findings.

The team plans to follow patients to track brain changes and memory recovery, Kenny said. While patients with breast cancer are a common focus, the researchers intend to expand the study to other cancers in both men and women, said Kenny. 

Based on discussions with her oncology colleagues, Kenny noted that many patients anecdotally report experiencing memory problems during chemotherapy.

 

More Research Needed

Commenting for this news organization, Rebecca M. Edelmayer, PhD, vice president, scientific engagement, at the Alzheimer’s Association, said the research may help shed light on why women are more likely to develop dementia than men.

For years now, experts have been trying to figure out what puts women at higher risk for AD and other dementias, said Edelmayer.

“We still don’t understand whether this involves biologically driven risk factors or socially driven risk factors.”

Research linking treatments for other health conditions to increased memory problems may offer some clues, she noted, suggesting a potential avenue for further investigation into the intersection of chemotherapy and neurodegenerative diseases such as Alzheimer’s.

However, Edelmayer emphasized that this line of research is still in its infancy. Much more work is needed to determine whether there is a direct cause-and-effect relationship with specific chemotherapy drugs, and whether some patients may already be predisposed or at higher risk for cognitive decline, she said.

Also commenting for this news organization, Eric Brown, MD, associate scientist and associate chief of geriatric psychiatry at the Centre for Addiction and Mental Health in Toronto, raised concerns about the study’s design.

One issue, he noted, is that the researchers did not image all patients who received chemotherapy but instead selected those with the most significant cognitive impairment. As a result, the findings may not have reflected outcomes in the average post-chemotherapy patients but rather represent the most severely affected subgroup.

Brown pointed out that the study did not clarify whether this subgroup had comorbid conditions. It’s possible, he said, that some individuals may have had Alzheimer’s disease or other forms of dementia unrelated to chemotherapy.

He agreed that tracking longitudinal changes in both cognitive scores and neuroimaging — comparing patients who receive chemotherapy with those who do not — would be a valuable next step.

The investigators, Edelmayer, and Brown reported no relevant conflicts of interest. A version of this article first appeared on Medscape.com.

Patients with breast cancer who undergo chemotherapy may face an increased risk for brain atrophy and cognitive decline, new findings from a pilot study suggest.

Memory problems in patients with cancer may not stem solely from stress or anxiety related to their diagnosis but could reflect underlying changes in brain structure, study investigator Paul Edison, PhD, MPhil, professor of neuroscience and clinical professor of neurology at Imperial College London, England, told this news organization.

While the findings suggest that chemotherapy may contribute to neuronal damage, the researchers noted that many aspects of the relationship between treatment and brain changes remain unclear.

Edison highlighted three key areas that require further investigation — uncovering the mechanisms driving brain atrophy, determining the proportion of patients affected, and identifying effective prevention strategies.

Another investigator on the study, Laura Kenny, MD, PhD, associate professor and consultant medical oncologist at Imperial College London, noted that the issue has received limited attention to date but expressed hope that the findings will raise awareness and encourage further research, given its clinical importance.

The findings were presented on July 29 at the Alzheimer’s Association International Conference (AAIC) 2025.

 

Investigating Cognitive Impact

Advances in chemotherapeutic agents have improved survival rates in patients with cancer. However, challenges persist regarding the long-term impact of these drugs.

Chemotherapy-associated cognitive impairment, often referred to as “brain fog” or “chemobrain,” affects approximately one third of patients with breast cancer following treatment.

While cognitive decline resolves within 12 months for some patients, others experience persistent effects that may elevate the risk for neurodegenerative conditions, Edison explained.

To evaluate the impact of chemotherapy on the brain, investigators studied 328 women with nonmetastatic breast cancer who had undergone chemotherapy within the past 12 months.

Patients received either anthracycline — a drug derived from the Streptomyces peucetius bacterium — or taxanes such as docetaxel and paclitaxel, both commonly used in breast cancer treatment, or a combination of these agents. In addition, some patients may also have had hormone therapy at some point during treatment, said Kenny.

Participants completed neurocognitive prescreening tests every 3 months using a specialized artificial intelligence–driven platform, allowing them to take detailed memory assessments online from home.

Among those prescreened, 18 individuals with lower neurocognitive scores (mean age, 55 years) and 19 cognitively normal control individuals without breast cancer (mean age, 67 years) underwent comprehensive, in-person, neurocognitive evaluations and MRI scans.

Researchers analyzed the scans using region of interest (ROI) and voxel-based morphometry (VBM), which uses sophisticated computer software, to assess gray matter volumes and surface areas.

The ROI analysis revealed significant reductions in gray matter volume (measured in mm³) and surface area (measured in mm²) among patients experiencing chemobrain, particularly affecting the isthmus cingulate and pars opercularis, with changes extending into the orbitofrontal and temporal regions.

 

Significant Atrophy

The VBM analysis confirmed significant atrophy in the frontal, parietal, and cingulate regions of patients with chemobrain compared with control individuals (P < .05). Edison noted that this pattern overlaps with brain changes typically observed in Alzheimer’s disease and vascular cognitive impairment.

For both analyses, “we demonstrated there is some amount of shrinkage in the brain among patients with chemobrain,” he said. “The fact that controls are older means the results are even more significant as there’s more brain atrophy as people age.”

Some of the affected brain regions may be linked to impaired memory, a hallmark of Alzheimer’s disease, but Edison cautioned that given the small sample size this finding should be interpreted with caution.

While the analysis demonstrated overall lower brain volumes in patients with “chemobrain” compared with controls, Edison emphasized that this finding reflects a single time point and does not indicate brain shrinkage over time.

Other events, including stroke — can also cause brain changes.

Edison highlighted the importance of determining the significance of these brain changes, how they affect patients and whether they can be prevented.

In-person neurocognitive testing revealed significantly reduced semantic and verbal fluency, as well as lower Mini-Mental State Examination scores in patients with chemobrain. Edison noted that these results support the MRI findings.

The team plans to follow patients to track brain changes and memory recovery, Kenny said. While patients with breast cancer are a common focus, the researchers intend to expand the study to other cancers in both men and women, said Kenny. 

Based on discussions with her oncology colleagues, Kenny noted that many patients anecdotally report experiencing memory problems during chemotherapy.

 

More Research Needed

Commenting for this news organization, Rebecca M. Edelmayer, PhD, vice president, scientific engagement, at the Alzheimer’s Association, said the research may help shed light on why women are more likely to develop dementia than men.

For years now, experts have been trying to figure out what puts women at higher risk for AD and other dementias, said Edelmayer.

“We still don’t understand whether this involves biologically driven risk factors or socially driven risk factors.”

Research linking treatments for other health conditions to increased memory problems may offer some clues, she noted, suggesting a potential avenue for further investigation into the intersection of chemotherapy and neurodegenerative diseases such as Alzheimer’s.

However, Edelmayer emphasized that this line of research is still in its infancy. Much more work is needed to determine whether there is a direct cause-and-effect relationship with specific chemotherapy drugs, and whether some patients may already be predisposed or at higher risk for cognitive decline, she said.

Also commenting for this news organization, Eric Brown, MD, associate scientist and associate chief of geriatric psychiatry at the Centre for Addiction and Mental Health in Toronto, raised concerns about the study’s design.

One issue, he noted, is that the researchers did not image all patients who received chemotherapy but instead selected those with the most significant cognitive impairment. As a result, the findings may not have reflected outcomes in the average post-chemotherapy patients but rather represent the most severely affected subgroup.

Brown pointed out that the study did not clarify whether this subgroup had comorbid conditions. It’s possible, he said, that some individuals may have had Alzheimer’s disease or other forms of dementia unrelated to chemotherapy.

He agreed that tracking longitudinal changes in both cognitive scores and neuroimaging — comparing patients who receive chemotherapy with those who do not — would be a valuable next step.

The investigators, Edelmayer, and Brown reported no relevant conflicts of interest. A version of this article first appeared on Medscape.com.

Patients with breast cancer who undergo chemotherapy may face an increased risk for brain atrophy and cognitive decline, new findings from a pilot study suggest.

Memory problems in patients with cancer may not stem solely from stress or anxiety related to their diagnosis but could reflect underlying changes in brain structure, study investigator Paul Edison, PhD, MPhil, professor of neuroscience and clinical professor of neurology at Imperial College London, England, told this news organization.

While the findings suggest that chemotherapy may contribute to neuronal damage, the researchers noted that many aspects of the relationship between treatment and brain changes remain unclear.

Edison highlighted three key areas that require further investigation — uncovering the mechanisms driving brain atrophy, determining the proportion of patients affected, and identifying effective prevention strategies.

Another investigator on the study, Laura Kenny, MD, PhD, associate professor and consultant medical oncologist at Imperial College London, noted that the issue has received limited attention to date but expressed hope that the findings will raise awareness and encourage further research, given its clinical importance.

The findings were presented on July 29 at the Alzheimer’s Association International Conference (AAIC) 2025.

 

Investigating Cognitive Impact

Advances in chemotherapeutic agents have improved survival rates in patients with cancer. However, challenges persist regarding the long-term impact of these drugs.

Chemotherapy-associated cognitive impairment, often referred to as “brain fog” or “chemobrain,” affects approximately one third of patients with breast cancer following treatment.

While cognitive decline resolves within 12 months for some patients, others experience persistent effects that may elevate the risk for neurodegenerative conditions, Edison explained.

To evaluate the impact of chemotherapy on the brain, investigators studied 328 women with nonmetastatic breast cancer who had undergone chemotherapy within the past 12 months.

Patients received either anthracycline — a drug derived from the Streptomyces peucetius bacterium — or taxanes such as docetaxel and paclitaxel, both commonly used in breast cancer treatment, or a combination of these agents. In addition, some patients may also have had hormone therapy at some point during treatment, said Kenny.

Participants completed neurocognitive prescreening tests every 3 months using a specialized artificial intelligence–driven platform, allowing them to take detailed memory assessments online from home.

Among those prescreened, 18 individuals with lower neurocognitive scores (mean age, 55 years) and 19 cognitively normal control individuals without breast cancer (mean age, 67 years) underwent comprehensive, in-person, neurocognitive evaluations and MRI scans.

Researchers analyzed the scans using region of interest (ROI) and voxel-based morphometry (VBM), which uses sophisticated computer software, to assess gray matter volumes and surface areas.

The ROI analysis revealed significant reductions in gray matter volume (measured in mm³) and surface area (measured in mm²) among patients experiencing chemobrain, particularly affecting the isthmus cingulate and pars opercularis, with changes extending into the orbitofrontal and temporal regions.

 

Significant Atrophy

The VBM analysis confirmed significant atrophy in the frontal, parietal, and cingulate regions of patients with chemobrain compared with control individuals (P < .05). Edison noted that this pattern overlaps with brain changes typically observed in Alzheimer’s disease and vascular cognitive impairment.

For both analyses, “we demonstrated there is some amount of shrinkage in the brain among patients with chemobrain,” he said. “The fact that controls are older means the results are even more significant as there’s more brain atrophy as people age.”

Some of the affected brain regions may be linked to impaired memory, a hallmark of Alzheimer’s disease, but Edison cautioned that given the small sample size this finding should be interpreted with caution.

While the analysis demonstrated overall lower brain volumes in patients with “chemobrain” compared with controls, Edison emphasized that this finding reflects a single time point and does not indicate brain shrinkage over time.

Other events, including stroke — can also cause brain changes.

Edison highlighted the importance of determining the significance of these brain changes, how they affect patients and whether they can be prevented.

In-person neurocognitive testing revealed significantly reduced semantic and verbal fluency, as well as lower Mini-Mental State Examination scores in patients with chemobrain. Edison noted that these results support the MRI findings.

The team plans to follow patients to track brain changes and memory recovery, Kenny said. While patients with breast cancer are a common focus, the researchers intend to expand the study to other cancers in both men and women, said Kenny. 

Based on discussions with her oncology colleagues, Kenny noted that many patients anecdotally report experiencing memory problems during chemotherapy.

 

More Research Needed

Commenting for this news organization, Rebecca M. Edelmayer, PhD, vice president, scientific engagement, at the Alzheimer’s Association, said the research may help shed light on why women are more likely to develop dementia than men.

For years now, experts have been trying to figure out what puts women at higher risk for AD and other dementias, said Edelmayer.

“We still don’t understand whether this involves biologically driven risk factors or socially driven risk factors.”

Research linking treatments for other health conditions to increased memory problems may offer some clues, she noted, suggesting a potential avenue for further investigation into the intersection of chemotherapy and neurodegenerative diseases such as Alzheimer’s.

However, Edelmayer emphasized that this line of research is still in its infancy. Much more work is needed to determine whether there is a direct cause-and-effect relationship with specific chemotherapy drugs, and whether some patients may already be predisposed or at higher risk for cognitive decline, she said.

Also commenting for this news organization, Eric Brown, MD, associate scientist and associate chief of geriatric psychiatry at the Centre for Addiction and Mental Health in Toronto, raised concerns about the study’s design.

One issue, he noted, is that the researchers did not image all patients who received chemotherapy but instead selected those with the most significant cognitive impairment. As a result, the findings may not have reflected outcomes in the average post-chemotherapy patients but rather represent the most severely affected subgroup.

Brown pointed out that the study did not clarify whether this subgroup had comorbid conditions. It’s possible, he said, that some individuals may have had Alzheimer’s disease or other forms of dementia unrelated to chemotherapy.

He agreed that tracking longitudinal changes in both cognitive scores and neuroimaging — comparing patients who receive chemotherapy with those who do not — would be a valuable next step.

The investigators, Edelmayer, and Brown reported no relevant conflicts of interest. A version of this article first appeared on Medscape.com.

TOPLINE:

Bone health management for older women with breast cancer receiving aromatase inhibitors (AIs) varied substantially across 5 UK hospitals. Despite the higher risk for fractures, women aged > 80 years were less likely to receive DEXA scans or bisphosphonates, highlighting the urgent need for standardised bone monitoring and treatment in frail older patients.

METHODOLOGY:

• This secondary analysis of the multicentre Age Gap study included 529 women (age ≥ 70 years) with oestrogen receptor-positive early breast cancer who received AIs, either as primary or adjuvant treatment, at five hospitals in the UK.
• Researchers collected comprehensive data including the type of endocrine therapy, DEXA scan results, bisphosphonate usage, calcium and vitamin D supplementation, and the incidence of fractures during or after AI therapy.
• Frailty was assessed using a modified Rockwood Frailty Index, with scores being calculated across 75 variables to categorise patients as robust (< 0.08), prefrail (0.08-0.25), or frail (> 0.25).

TAKEAWAY:

• Overall, 67% of patients had baseline DEXA scans. Of these, 42% were osteopenic and 18% osteoporotic. Scans were more common in 70- to 79-year-olds than in those aged ≥ 80 years and in women undergoing surgery than in those undergoing primary endocrine therapy, with marked variation across centres (P < .001 for all).
• Among patients receiving AI therapy, 43% were prescribed bisphosphonates, especially those who had surgery (hazard ratio [HR], 1.36; P = .04) and those aged 70-79 years (HR, 1.31; P = .02); 33% had vitamin D plus calcium along with bisphosphonates.
• During follow-up, 23% of patients had fractures, with significant variation across centres (P = .02), and 38% of these patients had received prior bisphosphonates.
• Although 94% of patients were frail or prefrail, frailty did not correlate with baseline hip (P = .10) or spine (P = .89) T scores. Bisphosphonates plus AIs were prescribed in 70% of nonfrail participants vs 43% of prefrail and 47% of frail participants (P = .02).

IN PRACTICE:

“Patient’s age and general health influence bone health decision making, with older and frailer patients often receiving non-standard care. Despite national and international recommendations, there is still wide variation in bone health management, highlighting the need for further education and standardised bone health care in older women with breast cancer,” the authors wrote.

SOURCE:

This study was led by Elisavet Theodoulou, University of Sheffield, Sheffield, England. It was published online, in the Journal of Geriatric Oncology.

LIMITATIONS:

The study’s inclusion of only 5 hospital sites limited the ability to draw broader conclusions about bone health management practices across a wider range of centres. Additionally, the interpretation of the results was complicated by the introduction of adjuvant bisphosphonates during the study period, making the cohort unstable in terms of bisphosphonate usage indications.

DISCLOSURES:

The Age Gap study was supported by the National Institute for Health and Care Research Programme Grants for Applied Research. The authors declared having no conflicts of interest.

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:

Bone health management for older women with breast cancer receiving aromatase inhibitors (AIs) varied substantially across 5 UK hospitals. Despite the higher risk for fractures, women aged > 80 years were less likely to receive DEXA scans or bisphosphonates, highlighting the urgent need for standardised bone monitoring and treatment in frail older patients.

METHODOLOGY:

• This secondary analysis of the multicentre Age Gap study included 529 women (age ≥ 70 years) with oestrogen receptor-positive early breast cancer who received AIs, either as primary or adjuvant treatment, at five hospitals in the UK.
• Researchers collected comprehensive data including the type of endocrine therapy, DEXA scan results, bisphosphonate usage, calcium and vitamin D supplementation, and the incidence of fractures during or after AI therapy.
• Frailty was assessed using a modified Rockwood Frailty Index, with scores being calculated across 75 variables to categorise patients as robust (< 0.08), prefrail (0.08-0.25), or frail (> 0.25).

TAKEAWAY:

• Overall, 67% of patients had baseline DEXA scans. Of these, 42% were osteopenic and 18% osteoporotic. Scans were more common in 70- to 79-year-olds than in those aged ≥ 80 years and in women undergoing surgery than in those undergoing primary endocrine therapy, with marked variation across centres (P < .001 for all).
• Among patients receiving AI therapy, 43% were prescribed bisphosphonates, especially those who had surgery (hazard ratio [HR], 1.36; P = .04) and those aged 70-79 years (HR, 1.31; P = .02); 33% had vitamin D plus calcium along with bisphosphonates.
• During follow-up, 23% of patients had fractures, with significant variation across centres (P = .02), and 38% of these patients had received prior bisphosphonates.
• Although 94% of patients were frail or prefrail, frailty did not correlate with baseline hip (P = .10) or spine (P = .89) T scores. Bisphosphonates plus AIs were prescribed in 70% of nonfrail participants vs 43% of prefrail and 47% of frail participants (P = .02).

IN PRACTICE:

“Patient’s age and general health influence bone health decision making, with older and frailer patients often receiving non-standard care. Despite national and international recommendations, there is still wide variation in bone health management, highlighting the need for further education and standardised bone health care in older women with breast cancer,” the authors wrote.

SOURCE:

This study was led by Elisavet Theodoulou, University of Sheffield, Sheffield, England. It was published online, in the Journal of Geriatric Oncology.

LIMITATIONS:

The study’s inclusion of only 5 hospital sites limited the ability to draw broader conclusions about bone health management practices across a wider range of centres. Additionally, the interpretation of the results was complicated by the introduction of adjuvant bisphosphonates during the study period, making the cohort unstable in terms of bisphosphonate usage indications.

DISCLOSURES:

The Age Gap study was supported by the National Institute for Health and Care Research Programme Grants for Applied Research. The authors declared having no conflicts of interest.

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:

Bone health management for older women with breast cancer receiving aromatase inhibitors (AIs) varied substantially across 5 UK hospitals. Despite the higher risk for fractures, women aged > 80 years were less likely to receive DEXA scans or bisphosphonates, highlighting the urgent need for standardised bone monitoring and treatment in frail older patients.

METHODOLOGY:

• This secondary analysis of the multicentre Age Gap study included 529 women (age ≥ 70 years) with oestrogen receptor-positive early breast cancer who received AIs, either as primary or adjuvant treatment, at five hospitals in the UK.
• Researchers collected comprehensive data including the type of endocrine therapy, DEXA scan results, bisphosphonate usage, calcium and vitamin D supplementation, and the incidence of fractures during or after AI therapy.
• Frailty was assessed using a modified Rockwood Frailty Index, with scores being calculated across 75 variables to categorise patients as robust (< 0.08), prefrail (0.08-0.25), or frail (> 0.25).

TAKEAWAY:

• Overall, 67% of patients had baseline DEXA scans. Of these, 42% were osteopenic and 18% osteoporotic. Scans were more common in 70- to 79-year-olds than in those aged ≥ 80 years and in women undergoing surgery than in those undergoing primary endocrine therapy, with marked variation across centres (P < .001 for all).
• Among patients receiving AI therapy, 43% were prescribed bisphosphonates, especially those who had surgery (hazard ratio [HR], 1.36; P = .04) and those aged 70-79 years (HR, 1.31; P = .02); 33% had vitamin D plus calcium along with bisphosphonates.
• During follow-up, 23% of patients had fractures, with significant variation across centres (P = .02), and 38% of these patients had received prior bisphosphonates.
• Although 94% of patients were frail or prefrail, frailty did not correlate with baseline hip (P = .10) or spine (P = .89) T scores. Bisphosphonates plus AIs were prescribed in 70% of nonfrail participants vs 43% of prefrail and 47% of frail participants (P = .02).

IN PRACTICE:

“Patient’s age and general health influence bone health decision making, with older and frailer patients often receiving non-standard care. Despite national and international recommendations, there is still wide variation in bone health management, highlighting the need for further education and standardised bone health care in older women with breast cancer,” the authors wrote.

SOURCE:

This study was led by Elisavet Theodoulou, University of Sheffield, Sheffield, England. It was published online, in the Journal of Geriatric Oncology.

LIMITATIONS:

The study’s inclusion of only 5 hospital sites limited the ability to draw broader conclusions about bone health management practices across a wider range of centres. Additionally, the interpretation of the results was complicated by the introduction of adjuvant bisphosphonates during the study period, making the cohort unstable in terms of bisphosphonate usage indications.

DISCLOSURES:

The Age Gap study was supported by the National Institute for Health and Care Research Programme Grants for Applied Research. The authors declared having no conflicts of interest.

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.

Despite concerns about cognitive decline after cancer treatment, most breast cancer survivors show no increased risk of developing Alzheimer’s disease, and some may have a slightly lower risk than their cancer-free peers, according to a large retrospective study from Korea.

However, any apparent protective effect faded with time, the investigators reported online in JAMA Network Open.

Overall, this is “reassuring news for cancer survivors,” Tim Ahles, PhD, a psychologist with Memorial Sloan Kettering Cancer Center, New York City, who wasn’t involved in the study, told  this news organization.

“I get this question from patients a lot,” Ahles said. And based on these findings, “it doesn’t look like a history of breast cancer and breast cancer treatment increases your risk for Alzheimer’s disease.”

Breast cancer survivors often report cancer-related cognitive impairment, such as difficulties with concentration and memory, both during and after cancer treatment. But evidence surrounding patients’ risk for Alzheimer’s disease is mixed. One large study based in Sweden, for instance, reported a 35% increased risk for Alzheimer’s disease among patients diagnosed with breast cancer after the age of 65 years, but not among younger patients. A population-based study from Taiwan, however, found no increase in the risk for dementia overall compared with cancer-free individuals but did note a lower dementia risk in patients who had received tamoxifen.

To help clarify the evidence, investigators assessed Alzheimer’s disease risk in a large cohort of patients and explored the association by treatment type, age, and important risk factors.

Using the Korean National Health Insurance Service database, the researchers matched 70,701 patients who underwent breast cancer surgery between 2010 and 2016 with 180,360 cancer-free control individuals.

The mean age of breast cancer survivors was 53.1 years. Overall, 72% received radiotherapy. Cyclophosphamide (57%) and anthracycline (50%) were the most commonly used chemotherapies, and tamoxifen (47%) and aromatase inhibitors (30%) were the most commonly used endocrine therapies.

The primary outcome of this study was the incidence of newly diagnosed Alzheimer’s disease, which was defined on the basis of at least one prescription for medications to manage dementia associated with Alzheimer’s disease (donepezil, rivastigmine, galantamine, or memantine).

During a median follow-up of about 7 years, 1229 newly diagnosed Alzheimer’s disease cases were detected in breast cancer survivors and 3430 cases in control individuals — incidence rates of 2.45 and 2.63 per 1000 person-years, respectively.

This corresponded to an 8% lower risk for Alzheimer’s disease in breast cancer survivors compared with cancer-free control individuals at 6 months (subdistribution hazard ratio [SHR], 0.92; 95% CI, 0.86-0.98). The association was especially notable in survivors older than 65 years (SHR, 0.92; 95% CI, 0.85-0.99).

Looking at individual treatment modalities, only radiation therapy was associated with significantly lower risk for Alzheimer’s disease among breast cancer survivors (adjusted HR [aHR], 0.77).

Several risk factors were associated with a significantly higher risk for Alzheimer’s disease: current smoker vs never or ex-smokers (aHR, 2.04), diabetes (aHR, 1.58), and chronic kidney disease (aHR, 3.11). Notably, alcohol use, physical activity level, and hypertension were not associated with Alzheimer’s disease risk.

However, any potential protective effect may be short-lived. The reduced risk for Alzheimer’s disease was no longer significant at 1 year (SHR, 0.94; 95% CI, 0.87-1.01), 3 years (SHR, 0.97; 95% CI, 0.90-1.05), or 5 years (SHR, 0.98; 95% CI, 0.89-1.08).

Even so, breast cancer survivors can still feel reassured by the findings.

“Concerns about chemobrain and the long-term adverse effects of breast cancer treatment on cognition are common, but our findings suggest that this treatment does not directly lead to Alzheimer’s disease,” wrote the authors, led by Su-Min Jeong, MD, with Seoul National University College of Medicine, Seoul, South Korea.

Ahles agreed. The general takeaway from this study is that there is “no strong evidence that the cancer treatment is going to increase your risk for developing Alzheimer’s,” Ahles said. When patients ask about the risk for Alzheimer’s disease, “I can say, ‘Here’s yet another new study that supports the idea that there’s no increased risk.’”

He cautioned, however, that the study doesn’t address whether people with a genetic predisposition to Alzheimer’s might develop it sooner due to cancer treatment.

“Does the cancer treatment increase your probability or nudge you along? The study doesn’t answer that question,” Ahles said.

The study reported having no commercial funding. Jeong and Ahles reported having no relevant disclosures.

A version of this article first appeared on Medscape.com.

Despite concerns about cognitive decline after cancer treatment, most breast cancer survivors show no increased risk of developing Alzheimer’s disease, and some may have a slightly lower risk than their cancer-free peers, according to a large retrospective study from Korea.

However, any apparent protective effect faded with time, the investigators reported online in JAMA Network Open.

Overall, this is “reassuring news for cancer survivors,” Tim Ahles, PhD, a psychologist with Memorial Sloan Kettering Cancer Center, New York City, who wasn’t involved in the study, told  this news organization.

“I get this question from patients a lot,” Ahles said. And based on these findings, “it doesn’t look like a history of breast cancer and breast cancer treatment increases your risk for Alzheimer’s disease.”

Breast cancer survivors often report cancer-related cognitive impairment, such as difficulties with concentration and memory, both during and after cancer treatment. But evidence surrounding patients’ risk for Alzheimer’s disease is mixed. One large study based in Sweden, for instance, reported a 35% increased risk for Alzheimer’s disease among patients diagnosed with breast cancer after the age of 65 years, but not among younger patients. A population-based study from Taiwan, however, found no increase in the risk for dementia overall compared with cancer-free individuals but did note a lower dementia risk in patients who had received tamoxifen.

To help clarify the evidence, investigators assessed Alzheimer’s disease risk in a large cohort of patients and explored the association by treatment type, age, and important risk factors.

Using the Korean National Health Insurance Service database, the researchers matched 70,701 patients who underwent breast cancer surgery between 2010 and 2016 with 180,360 cancer-free control individuals.

The mean age of breast cancer survivors was 53.1 years. Overall, 72% received radiotherapy. Cyclophosphamide (57%) and anthracycline (50%) were the most commonly used chemotherapies, and tamoxifen (47%) and aromatase inhibitors (30%) were the most commonly used endocrine therapies.

The primary outcome of this study was the incidence of newly diagnosed Alzheimer’s disease, which was defined on the basis of at least one prescription for medications to manage dementia associated with Alzheimer’s disease (donepezil, rivastigmine, galantamine, or memantine).

During a median follow-up of about 7 years, 1229 newly diagnosed Alzheimer’s disease cases were detected in breast cancer survivors and 3430 cases in control individuals — incidence rates of 2.45 and 2.63 per 1000 person-years, respectively.

This corresponded to an 8% lower risk for Alzheimer’s disease in breast cancer survivors compared with cancer-free control individuals at 6 months (subdistribution hazard ratio [SHR], 0.92; 95% CI, 0.86-0.98). The association was especially notable in survivors older than 65 years (SHR, 0.92; 95% CI, 0.85-0.99).

Looking at individual treatment modalities, only radiation therapy was associated with significantly lower risk for Alzheimer’s disease among breast cancer survivors (adjusted HR [aHR], 0.77).

Several risk factors were associated with a significantly higher risk for Alzheimer’s disease: current smoker vs never or ex-smokers (aHR, 2.04), diabetes (aHR, 1.58), and chronic kidney disease (aHR, 3.11). Notably, alcohol use, physical activity level, and hypertension were not associated with Alzheimer’s disease risk.

However, any potential protective effect may be short-lived. The reduced risk for Alzheimer’s disease was no longer significant at 1 year (SHR, 0.94; 95% CI, 0.87-1.01), 3 years (SHR, 0.97; 95% CI, 0.90-1.05), or 5 years (SHR, 0.98; 95% CI, 0.89-1.08).

Even so, breast cancer survivors can still feel reassured by the findings.

“Concerns about chemobrain and the long-term adverse effects of breast cancer treatment on cognition are common, but our findings suggest that this treatment does not directly lead to Alzheimer’s disease,” wrote the authors, led by Su-Min Jeong, MD, with Seoul National University College of Medicine, Seoul, South Korea.

Ahles agreed. The general takeaway from this study is that there is “no strong evidence that the cancer treatment is going to increase your risk for developing Alzheimer’s,” Ahles said. When patients ask about the risk for Alzheimer’s disease, “I can say, ‘Here’s yet another new study that supports the idea that there’s no increased risk.’”

He cautioned, however, that the study doesn’t address whether people with a genetic predisposition to Alzheimer’s might develop it sooner due to cancer treatment.

“Does the cancer treatment increase your probability or nudge you along? The study doesn’t answer that question,” Ahles said.

The study reported having no commercial funding. Jeong and Ahles reported having no relevant disclosures.

A version of this article first appeared on Medscape.com.

Despite concerns about cognitive decline after cancer treatment, most breast cancer survivors show no increased risk of developing Alzheimer’s disease, and some may have a slightly lower risk than their cancer-free peers, according to a large retrospective study from Korea.

However, any apparent protective effect faded with time, the investigators reported online in JAMA Network Open.

Overall, this is “reassuring news for cancer survivors,” Tim Ahles, PhD, a psychologist with Memorial Sloan Kettering Cancer Center, New York City, who wasn’t involved in the study, told  this news organization.

“I get this question from patients a lot,” Ahles said. And based on these findings, “it doesn’t look like a history of breast cancer and breast cancer treatment increases your risk for Alzheimer’s disease.”

Breast cancer survivors often report cancer-related cognitive impairment, such as difficulties with concentration and memory, both during and after cancer treatment. But evidence surrounding patients’ risk for Alzheimer’s disease is mixed. One large study based in Sweden, for instance, reported a 35% increased risk for Alzheimer’s disease among patients diagnosed with breast cancer after the age of 65 years, but not among younger patients. A population-based study from Taiwan, however, found no increase in the risk for dementia overall compared with cancer-free individuals but did note a lower dementia risk in patients who had received tamoxifen.

To help clarify the evidence, investigators assessed Alzheimer’s disease risk in a large cohort of patients and explored the association by treatment type, age, and important risk factors.

Using the Korean National Health Insurance Service database, the researchers matched 70,701 patients who underwent breast cancer surgery between 2010 and 2016 with 180,360 cancer-free control individuals.

The mean age of breast cancer survivors was 53.1 years. Overall, 72% received radiotherapy. Cyclophosphamide (57%) and anthracycline (50%) were the most commonly used chemotherapies, and tamoxifen (47%) and aromatase inhibitors (30%) were the most commonly used endocrine therapies.

The primary outcome of this study was the incidence of newly diagnosed Alzheimer’s disease, which was defined on the basis of at least one prescription for medications to manage dementia associated with Alzheimer’s disease (donepezil, rivastigmine, galantamine, or memantine).

During a median follow-up of about 7 years, 1229 newly diagnosed Alzheimer’s disease cases were detected in breast cancer survivors and 3430 cases in control individuals — incidence rates of 2.45 and 2.63 per 1000 person-years, respectively.

This corresponded to an 8% lower risk for Alzheimer’s disease in breast cancer survivors compared with cancer-free control individuals at 6 months (subdistribution hazard ratio [SHR], 0.92; 95% CI, 0.86-0.98). The association was especially notable in survivors older than 65 years (SHR, 0.92; 95% CI, 0.85-0.99).

Looking at individual treatment modalities, only radiation therapy was associated with significantly lower risk for Alzheimer’s disease among breast cancer survivors (adjusted HR [aHR], 0.77).

Several risk factors were associated with a significantly higher risk for Alzheimer’s disease: current smoker vs never or ex-smokers (aHR, 2.04), diabetes (aHR, 1.58), and chronic kidney disease (aHR, 3.11). Notably, alcohol use, physical activity level, and hypertension were not associated with Alzheimer’s disease risk.

However, any potential protective effect may be short-lived. The reduced risk for Alzheimer’s disease was no longer significant at 1 year (SHR, 0.94; 95% CI, 0.87-1.01), 3 years (SHR, 0.97; 95% CI, 0.90-1.05), or 5 years (SHR, 0.98; 95% CI, 0.89-1.08).

Even so, breast cancer survivors can still feel reassured by the findings.

“Concerns about chemobrain and the long-term adverse effects of breast cancer treatment on cognition are common, but our findings suggest that this treatment does not directly lead to Alzheimer’s disease,” wrote the authors, led by Su-Min Jeong, MD, with Seoul National University College of Medicine, Seoul, South Korea.

Ahles agreed. The general takeaway from this study is that there is “no strong evidence that the cancer treatment is going to increase your risk for developing Alzheimer’s,” Ahles said. When patients ask about the risk for Alzheimer’s disease, “I can say, ‘Here’s yet another new study that supports the idea that there’s no increased risk.’”

He cautioned, however, that the study doesn’t address whether people with a genetic predisposition to Alzheimer’s might develop it sooner due to cancer treatment.

“Does the cancer treatment increase your probability or nudge you along? The study doesn’t answer that question,” Ahles said.

The study reported having no commercial funding. Jeong and Ahles reported having no relevant disclosures.

A version of this article first appeared on Medscape.com.

TOPLINE:

A recent study found that 3 months of resistance training did not worsen lymphedema in breast cancer survivors and instead significantly improved fluid balance and increased upper extremity muscle mass. The edema index also improved, suggesting potential therapeutic benefits of intense resistance training for managing lymphedema.

METHODOLOGY:

• Lymphedema is a common adverse effect of breast cancer treatment that can limit mobility. Although strength training can have multiple benefits for breast cancer survivors, such as increased bone density and metabolism, data on whether more intense resistance training exacerbates lymphedema in this population are limited. Worries that more intense training will lead to or worsen lymphedema have typically led to cautious recommendations.
• Researchers conducted a cohort study involving 115 women with breast cancer (median age, 54 years; 96% White; 4% Black) between September 2022 and March 2024. Most (83%) underwent sentinel lymph node biopsy (SLNB), while 12% had axillary lymph node dissection (ALND). At baseline, 13% had clinical lymphedema, including 37% in the ALND group and 8% in the SLNB group.
• Participants attended resistance training sessions three times a week, with intensity escalation over 3 months. Exercises involved hand weights, resistance bands, and body weight (eg, pushups) to promote strength, mobility, and muscle hypertrophy.
• Bioimpedance analysis measured intracellular water, extracellular water, and total body water before and after exercise. Lymphedema was defined as more than a 3% increase in arm circumference discrepancy relative to preoperative ipsilateral arm measurements, along with an elevated edema index (extracellular water to total body water ratio).

TAKEAWAY:

• No participants experienced subjective or clinical worsening of lymphedema after completing the resistance training regimen.
• Lean mass in the affected arm increased from a median of 5.45 lb to 5.64 lb (P < .001), while lean mass in the unaffected arm rose from 5.51 lb to 5.53 lb (P < .001) after the resistance training.
• Overall, participants’ fluid balance improved. The edema index in both arms showed a significant reduction at training completion (mean, 0.383) vs baseline (mean, 0.385), indicating reduced lymphedema. Subgroup analysis of women who underwent SLNB showed similar improvements in the edema index.

IN PRACTICE:

“These findings highlight the safety of strength and resistance training in a large group of patients with breast cancer during and after treatment,” the authors wrote. Beyond that, the authors noted, the results point to a potential role for resistance training in reducing lymphedema.

SOURCE:

This study, led by Parisa Shamsesfandabadi, MD, Allegheny Health Network, Pittsburgh, was published online in JAMA Network Open.

LIMITATIONS:

A major limitation was the absence of a control group, which prevented a direct comparison between the effects of exercise and the natural progression of lymphedema. The 3-month intervention provided limited insight into the long-term sustainability of benefits. Patient-reported outcomes were not included. Additionally, potential confounding variables such as diet, medication use, and baseline physical activity levels were not controlled for in the analysis.

DISCLOSURES:

The authors did not disclose any funding information. Several authors reported having ties with various sources. Additional disclosures are noted in the original article.

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:

A recent study found that 3 months of resistance training did not worsen lymphedema in breast cancer survivors and instead significantly improved fluid balance and increased upper extremity muscle mass. The edema index also improved, suggesting potential therapeutic benefits of intense resistance training for managing lymphedema.

METHODOLOGY:

• Lymphedema is a common adverse effect of breast cancer treatment that can limit mobility. Although strength training can have multiple benefits for breast cancer survivors, such as increased bone density and metabolism, data on whether more intense resistance training exacerbates lymphedema in this population are limited. Worries that more intense training will lead to or worsen lymphedema have typically led to cautious recommendations.
• Researchers conducted a cohort study involving 115 women with breast cancer (median age, 54 years; 96% White; 4% Black) between September 2022 and March 2024. Most (83%) underwent sentinel lymph node biopsy (SLNB), while 12% had axillary lymph node dissection (ALND). At baseline, 13% had clinical lymphedema, including 37% in the ALND group and 8% in the SLNB group.
• Participants attended resistance training sessions three times a week, with intensity escalation over 3 months. Exercises involved hand weights, resistance bands, and body weight (eg, pushups) to promote strength, mobility, and muscle hypertrophy.
• Bioimpedance analysis measured intracellular water, extracellular water, and total body water before and after exercise. Lymphedema was defined as more than a 3% increase in arm circumference discrepancy relative to preoperative ipsilateral arm measurements, along with an elevated edema index (extracellular water to total body water ratio).

TAKEAWAY:

• No participants experienced subjective or clinical worsening of lymphedema after completing the resistance training regimen.
• Lean mass in the affected arm increased from a median of 5.45 lb to 5.64 lb (P < .001), while lean mass in the unaffected arm rose from 5.51 lb to 5.53 lb (P < .001) after the resistance training.
• Overall, participants’ fluid balance improved. The edema index in both arms showed a significant reduction at training completion (mean, 0.383) vs baseline (mean, 0.385), indicating reduced lymphedema. Subgroup analysis of women who underwent SLNB showed similar improvements in the edema index.

IN PRACTICE:

“These findings highlight the safety of strength and resistance training in a large group of patients with breast cancer during and after treatment,” the authors wrote. Beyond that, the authors noted, the results point to a potential role for resistance training in reducing lymphedema.

SOURCE:

This study, led by Parisa Shamsesfandabadi, MD, Allegheny Health Network, Pittsburgh, was published online in JAMA Network Open.

LIMITATIONS:

A major limitation was the absence of a control group, which prevented a direct comparison between the effects of exercise and the natural progression of lymphedema. The 3-month intervention provided limited insight into the long-term sustainability of benefits. Patient-reported outcomes were not included. Additionally, potential confounding variables such as diet, medication use, and baseline physical activity levels were not controlled for in the analysis.

DISCLOSURES:

The authors did not disclose any funding information. Several authors reported having ties with various sources. Additional disclosures are noted in the original article.

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:

A recent study found that 3 months of resistance training did not worsen lymphedema in breast cancer survivors and instead significantly improved fluid balance and increased upper extremity muscle mass. The edema index also improved, suggesting potential therapeutic benefits of intense resistance training for managing lymphedema.

METHODOLOGY:

• Lymphedema is a common adverse effect of breast cancer treatment that can limit mobility. Although strength training can have multiple benefits for breast cancer survivors, such as increased bone density and metabolism, data on whether more intense resistance training exacerbates lymphedema in this population are limited. Worries that more intense training will lead to or worsen lymphedema have typically led to cautious recommendations.
• Researchers conducted a cohort study involving 115 women with breast cancer (median age, 54 years; 96% White; 4% Black) between September 2022 and March 2024. Most (83%) underwent sentinel lymph node biopsy (SLNB), while 12% had axillary lymph node dissection (ALND). At baseline, 13% had clinical lymphedema, including 37% in the ALND group and 8% in the SLNB group.
• Participants attended resistance training sessions three times a week, with intensity escalation over 3 months. Exercises involved hand weights, resistance bands, and body weight (eg, pushups) to promote strength, mobility, and muscle hypertrophy.
• Bioimpedance analysis measured intracellular water, extracellular water, and total body water before and after exercise. Lymphedema was defined as more than a 3% increase in arm circumference discrepancy relative to preoperative ipsilateral arm measurements, along with an elevated edema index (extracellular water to total body water ratio).

TAKEAWAY:

• No participants experienced subjective or clinical worsening of lymphedema after completing the resistance training regimen.
• Lean mass in the affected arm increased from a median of 5.45 lb to 5.64 lb (P < .001), while lean mass in the unaffected arm rose from 5.51 lb to 5.53 lb (P < .001) after the resistance training.
• Overall, participants’ fluid balance improved. The edema index in both arms showed a significant reduction at training completion (mean, 0.383) vs baseline (mean, 0.385), indicating reduced lymphedema. Subgroup analysis of women who underwent SLNB showed similar improvements in the edema index.

IN PRACTICE:

“These findings highlight the safety of strength and resistance training in a large group of patients with breast cancer during and after treatment,” the authors wrote. Beyond that, the authors noted, the results point to a potential role for resistance training in reducing lymphedema.

SOURCE:

This study, led by Parisa Shamsesfandabadi, MD, Allegheny Health Network, Pittsburgh, was published online in JAMA Network Open.

LIMITATIONS:

A major limitation was the absence of a control group, which prevented a direct comparison between the effects of exercise and the natural progression of lymphedema. The 3-month intervention provided limited insight into the long-term sustainability of benefits. Patient-reported outcomes were not included. Additionally, potential confounding variables such as diet, medication use, and baseline physical activity levels were not controlled for in the analysis.

DISCLOSURES:

The authors did not disclose any funding information. Several authors reported having ties with various sources. Additional disclosures are noted in the original article.

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.

Breast cancer is the most common cancer in women worldwide and a leading cause of cancer-related deaths. The most common form of breast cancer is invasive ductal carcinoma, which accounts for 75%-80% of breast cancers. The second most common form is invasive lobular carcinoma, which accounts for 10%-15% of cases.

Surgical treatment of breast cancer involves removal and pathological staging of the cancerous tissue. Breast-conserving surgery and mastectomy are two surgical treatment options for patients with breast cancer. Breast-conserving surgery, which involves resection of the tumor and the surrounding margin of healthy tissue to achieve clean margins, is usually combined with radiotherapy. Mastectomy is considered in patients with relative and absolute contraindications to breast-conserving therapeutic options (eg, patients with a genetic predisposition to breast cancer, tumors > 5 cm, extensive margins, prior radiation to breast or chest wall, first-trimester pregnancy, extensive ductal carcinoma in situ, inflammatory breast cancer). Although surgical treatment of breast cancer is widely used, there have been calls to minimize unnecessary invasive surgical interventions in patients with early-stage breast cancer.

 

Reassessing the Role of Surgery in the Early Stages 

Some surgical procedures, including axillary lymph node dissection (ALND) and contralateral prophylactic mastectomy (CPM), once considered standard treatment for early-stage breast cancer, are now being recognized as unnecessary in most cases of early-stage breast cancer without sentinel node metastases. Although ALND, which involves removal of all lymphatic tissue in the axilla, has been used for decades in the surgical management of early-stage breast cancer, this intervention typically results in lymphedema and significant morbidity. 

Contralateral prophylactic mastectomy is a surgical option chosen by some women with early-stage unilateral breast cancer. However, this procedure is considered controversial in this patient population since evidence shows no survival advantage with CPM. A large-scale survey by Jagsi et al of female patients with in situ or early-stage breast cancer concluded that CPM was more common in patients who were White, had a higher level of education, and had private health insurance. In the study, 598 of the 1569 patients without an identified mutation or high genetic risk reported that a surgeon recommended against CPM. Of this group, only 1.9% underwent CPM. In contrast, of the 746 patients who reported that they did not receive any recommendation from a surgeon, 19% underwent CPM. 

Re-excision and mastectomy are considered in patients with early-stage breast cancer when clear margins are not achieved with breast-conserving surgery. To prevent unnecessary reoperations and mastectomies, the 2013 invasive cancer margin consensus guideline by the American Society for Radiation Oncology (ASTRO) and the Society of Surgical Oncology, defined adequate margins in breast-conserving surgery in invasive breast cancer as “no ink on tumor.” The guideline is endorsed by the American Society of Breast Surgeons, ASTRO, and the St Gallen Consensus Conference. 

 

A Shift in Practice: Moving Away From Routine Node Dissection

Based on findings from multiple clinical trials, experts recommend sentinel lymph node biopsy (SLNB) over ANLD and omit axillary surgery in certain patients. Findings from ACOSOG Z1071, SENTINA, and SN FNAC prospective multi-institutional trials support the use of SLNB as the initial diagnostic procedure. Sentinel lobe biopsy involves removal and evaluation of the first lymph node which receives lymphatic drainage from the breast cancer site. Negative biopsy findings on SLNB can avoid ALND as it is less likely that metastasis has occurred.

Although SLNB is preferred in younger patients with early-stage breast cancer, it is not routinely recommended for women aged ≥ 70 years of age with clinically node-negative, early-stage, HR-positive and HER2-negative breast cancer. This recommendation is based on study findings showing no difference in survival of women aged > 70 years with HR-positive clinical stage I breast cancer who did and did not undergo axillary evaluation. 

The Z0011 trial by the American College of Surgeons Oncology Group found SLNB alone was not inferior to ALND regarding overall and disease-free survival in patients with clinically node-negative cancer undergoing breast conservation surgery and radiation therapy.

 

SLNB: A Less Invasive Alternative to ALND

Compared to SLNB, ALND is associated with more morbidity, physical symptoms, and poorer quality of life. A systemic review by Bakri et al evaluating the impact of ALND vs SLNB found higher rates of lymphedema, pain, reduced strength, and range of motion in patients who underwent ALND. In addition, an analysis of the National Cancer Database by Cocco et al found that patients with limited CN+ T1-2 breast cancer had favorable survival outcomes after undergoing SLNB and regional node irradiation vs ALND.

 

Rethinking First Steps: Non-Surgical Strategies

While surgical intervention with or without radiation therapy remains a primary treatment in early-stage breast cancer, there is an increased emphasis on de-escalation to minimize surgery and consider nonsurgical options in this patient population. A neoadjuvant systemic therapeutic approach by Kuerer et al for HER2-positive breast cancer and triple-negative breast cancer yielded a pathological complete response in 62% of patients. This multicenter, single-arm, phase 2 trial evaluated patients with HER2-positive breast cancer and a residual breast lesion < 2 cm or unicentric cT1-2N0-1M0 triple-negative breast cancer. Patients in the study underwent radiotherapy alone after excluding invasive in-situ disease. 

 

The Clinician’s Role in Shaping Conservative Surgical Approaches

De-escalating surgery in breast cancer should involve acknowledging the patient’s fears and misperceptions regarding the risks of cancer recurrence that can lead them to opt for more invasive surgical treatments. Patients may not or fully regard the long-term effects of electing an invasive procedure in the absence of clinical indications. For example, patients undergoing more invasive interventions may experience worse body image and quality of life. 

Clinicians may also not adequately estimate other harms associated with unnecessary surgical interventions. Providing clinicians with data that focuses on the psychological outcomes and satisfaction of patients post surgery may help them to better interpret and consider patient values and wishes and minimize future unnecessary surgeries.

Breast cancer remains one of the best-studied cancers with multiple high-quality randomized controlled trials supporting de-escalation of surgery. De-escalation of breast cancer surgery has been successful in multiple ways, including the implementation of ALND in early-stage breast cancer. However, other options such as CPM remain common. Proper patient and physician education involving data from clinical trials and reports of patient satisfaction may further decrease unnecessary surgical interventions.

Nameera Temkar has disclosed no relevant financial relationships.

A version of this article first appeared on Medscape.com.

Breast cancer is the most common cancer in women worldwide and a leading cause of cancer-related deaths. The most common form of breast cancer is invasive ductal carcinoma, which accounts for 75%-80% of breast cancers. The second most common form is invasive lobular carcinoma, which accounts for 10%-15% of cases.

Surgical treatment of breast cancer involves removal and pathological staging of the cancerous tissue. Breast-conserving surgery and mastectomy are two surgical treatment options for patients with breast cancer. Breast-conserving surgery, which involves resection of the tumor and the surrounding margin of healthy tissue to achieve clean margins, is usually combined with radiotherapy. Mastectomy is considered in patients with relative and absolute contraindications to breast-conserving therapeutic options (eg, patients with a genetic predisposition to breast cancer, tumors > 5 cm, extensive margins, prior radiation to breast or chest wall, first-trimester pregnancy, extensive ductal carcinoma in situ, inflammatory breast cancer). Although surgical treatment of breast cancer is widely used, there have been calls to minimize unnecessary invasive surgical interventions in patients with early-stage breast cancer.

 

Reassessing the Role of Surgery in the Early Stages 

Some surgical procedures, including axillary lymph node dissection (ALND) and contralateral prophylactic mastectomy (CPM), once considered standard treatment for early-stage breast cancer, are now being recognized as unnecessary in most cases of early-stage breast cancer without sentinel node metastases. Although ALND, which involves removal of all lymphatic tissue in the axilla, has been used for decades in the surgical management of early-stage breast cancer, this intervention typically results in lymphedema and significant morbidity. 

Contralateral prophylactic mastectomy is a surgical option chosen by some women with early-stage unilateral breast cancer. However, this procedure is considered controversial in this patient population since evidence shows no survival advantage with CPM. A large-scale survey by Jagsi et al of female patients with in situ or early-stage breast cancer concluded that CPM was more common in patients who were White, had a higher level of education, and had private health insurance. In the study, 598 of the 1569 patients without an identified mutation or high genetic risk reported that a surgeon recommended against CPM. Of this group, only 1.9% underwent CPM. In contrast, of the 746 patients who reported that they did not receive any recommendation from a surgeon, 19% underwent CPM. 

Re-excision and mastectomy are considered in patients with early-stage breast cancer when clear margins are not achieved with breast-conserving surgery. To prevent unnecessary reoperations and mastectomies, the 2013 invasive cancer margin consensus guideline by the American Society for Radiation Oncology (ASTRO) and the Society of Surgical Oncology, defined adequate margins in breast-conserving surgery in invasive breast cancer as “no ink on tumor.” The guideline is endorsed by the American Society of Breast Surgeons, ASTRO, and the St Gallen Consensus Conference. 

 

A Shift in Practice: Moving Away From Routine Node Dissection

Based on findings from multiple clinical trials, experts recommend sentinel lymph node biopsy (SLNB) over ANLD and omit axillary surgery in certain patients. Findings from ACOSOG Z1071, SENTINA, and SN FNAC prospective multi-institutional trials support the use of SLNB as the initial diagnostic procedure. Sentinel lobe biopsy involves removal and evaluation of the first lymph node which receives lymphatic drainage from the breast cancer site. Negative biopsy findings on SLNB can avoid ALND as it is less likely that metastasis has occurred.

Although SLNB is preferred in younger patients with early-stage breast cancer, it is not routinely recommended for women aged ≥ 70 years of age with clinically node-negative, early-stage, HR-positive and HER2-negative breast cancer. This recommendation is based on study findings showing no difference in survival of women aged > 70 years with HR-positive clinical stage I breast cancer who did and did not undergo axillary evaluation. 

The Z0011 trial by the American College of Surgeons Oncology Group found SLNB alone was not inferior to ALND regarding overall and disease-free survival in patients with clinically node-negative cancer undergoing breast conservation surgery and radiation therapy.

 

SLNB: A Less Invasive Alternative to ALND

Compared to SLNB, ALND is associated with more morbidity, physical symptoms, and poorer quality of life. A systemic review by Bakri et al evaluating the impact of ALND vs SLNB found higher rates of lymphedema, pain, reduced strength, and range of motion in patients who underwent ALND. In addition, an analysis of the National Cancer Database by Cocco et al found that patients with limited CN+ T1-2 breast cancer had favorable survival outcomes after undergoing SLNB and regional node irradiation vs ALND.

 

Rethinking First Steps: Non-Surgical Strategies

While surgical intervention with or without radiation therapy remains a primary treatment in early-stage breast cancer, there is an increased emphasis on de-escalation to minimize surgery and consider nonsurgical options in this patient population. A neoadjuvant systemic therapeutic approach by Kuerer et al for HER2-positive breast cancer and triple-negative breast cancer yielded a pathological complete response in 62% of patients. This multicenter, single-arm, phase 2 trial evaluated patients with HER2-positive breast cancer and a residual breast lesion < 2 cm or unicentric cT1-2N0-1M0 triple-negative breast cancer. Patients in the study underwent radiotherapy alone after excluding invasive in-situ disease. 

 

The Clinician’s Role in Shaping Conservative Surgical Approaches

De-escalating surgery in breast cancer should involve acknowledging the patient’s fears and misperceptions regarding the risks of cancer recurrence that can lead them to opt for more invasive surgical treatments. Patients may not or fully regard the long-term effects of electing an invasive procedure in the absence of clinical indications. For example, patients undergoing more invasive interventions may experience worse body image and quality of life. 

Clinicians may also not adequately estimate other harms associated with unnecessary surgical interventions. Providing clinicians with data that focuses on the psychological outcomes and satisfaction of patients post surgery may help them to better interpret and consider patient values and wishes and minimize future unnecessary surgeries.

Breast cancer remains one of the best-studied cancers with multiple high-quality randomized controlled trials supporting de-escalation of surgery. De-escalation of breast cancer surgery has been successful in multiple ways, including the implementation of ALND in early-stage breast cancer. However, other options such as CPM remain common. Proper patient and physician education involving data from clinical trials and reports of patient satisfaction may further decrease unnecessary surgical interventions.

Nameera Temkar has disclosed no relevant financial relationships.

A version of this article first appeared on Medscape.com.

Breast cancer is the most common cancer in women worldwide and a leading cause of cancer-related deaths. The most common form of breast cancer is invasive ductal carcinoma, which accounts for 75%-80% of breast cancers. The second most common form is invasive lobular carcinoma, which accounts for 10%-15% of cases.

Surgical treatment of breast cancer involves removal and pathological staging of the cancerous tissue. Breast-conserving surgery and mastectomy are two surgical treatment options for patients with breast cancer. Breast-conserving surgery, which involves resection of the tumor and the surrounding margin of healthy tissue to achieve clean margins, is usually combined with radiotherapy. Mastectomy is considered in patients with relative and absolute contraindications to breast-conserving therapeutic options (eg, patients with a genetic predisposition to breast cancer, tumors > 5 cm, extensive margins, prior radiation to breast or chest wall, first-trimester pregnancy, extensive ductal carcinoma in situ, inflammatory breast cancer). Although surgical treatment of breast cancer is widely used, there have been calls to minimize unnecessary invasive surgical interventions in patients with early-stage breast cancer.

 

Reassessing the Role of Surgery in the Early Stages 

Some surgical procedures, including axillary lymph node dissection (ALND) and contralateral prophylactic mastectomy (CPM), once considered standard treatment for early-stage breast cancer, are now being recognized as unnecessary in most cases of early-stage breast cancer without sentinel node metastases. Although ALND, which involves removal of all lymphatic tissue in the axilla, has been used for decades in the surgical management of early-stage breast cancer, this intervention typically results in lymphedema and significant morbidity. 

Contralateral prophylactic mastectomy is a surgical option chosen by some women with early-stage unilateral breast cancer. However, this procedure is considered controversial in this patient population since evidence shows no survival advantage with CPM. A large-scale survey by Jagsi et al of female patients with in situ or early-stage breast cancer concluded that CPM was more common in patients who were White, had a higher level of education, and had private health insurance. In the study, 598 of the 1569 patients without an identified mutation or high genetic risk reported that a surgeon recommended against CPM. Of this group, only 1.9% underwent CPM. In contrast, of the 746 patients who reported that they did not receive any recommendation from a surgeon, 19% underwent CPM. 

Re-excision and mastectomy are considered in patients with early-stage breast cancer when clear margins are not achieved with breast-conserving surgery. To prevent unnecessary reoperations and mastectomies, the 2013 invasive cancer margin consensus guideline by the American Society for Radiation Oncology (ASTRO) and the Society of Surgical Oncology, defined adequate margins in breast-conserving surgery in invasive breast cancer as “no ink on tumor.” The guideline is endorsed by the American Society of Breast Surgeons, ASTRO, and the St Gallen Consensus Conference. 

 

A Shift in Practice: Moving Away From Routine Node Dissection

Based on findings from multiple clinical trials, experts recommend sentinel lymph node biopsy (SLNB) over ANLD and omit axillary surgery in certain patients. Findings from ACOSOG Z1071, SENTINA, and SN FNAC prospective multi-institutional trials support the use of SLNB as the initial diagnostic procedure. Sentinel lobe biopsy involves removal and evaluation of the first lymph node which receives lymphatic drainage from the breast cancer site. Negative biopsy findings on SLNB can avoid ALND as it is less likely that metastasis has occurred.

Although SLNB is preferred in younger patients with early-stage breast cancer, it is not routinely recommended for women aged ≥ 70 years of age with clinically node-negative, early-stage, HR-positive and HER2-negative breast cancer. This recommendation is based on study findings showing no difference in survival of women aged > 70 years with HR-positive clinical stage I breast cancer who did and did not undergo axillary evaluation. 

The Z0011 trial by the American College of Surgeons Oncology Group found SLNB alone was not inferior to ALND regarding overall and disease-free survival in patients with clinically node-negative cancer undergoing breast conservation surgery and radiation therapy.

 

SLNB: A Less Invasive Alternative to ALND

Compared to SLNB, ALND is associated with more morbidity, physical symptoms, and poorer quality of life. A systemic review by Bakri et al evaluating the impact of ALND vs SLNB found higher rates of lymphedema, pain, reduced strength, and range of motion in patients who underwent ALND. In addition, an analysis of the National Cancer Database by Cocco et al found that patients with limited CN+ T1-2 breast cancer had favorable survival outcomes after undergoing SLNB and regional node irradiation vs ALND.

 

Rethinking First Steps: Non-Surgical Strategies

While surgical intervention with or without radiation therapy remains a primary treatment in early-stage breast cancer, there is an increased emphasis on de-escalation to minimize surgery and consider nonsurgical options in this patient population. A neoadjuvant systemic therapeutic approach by Kuerer et al for HER2-positive breast cancer and triple-negative breast cancer yielded a pathological complete response in 62% of patients. This multicenter, single-arm, phase 2 trial evaluated patients with HER2-positive breast cancer and a residual breast lesion < 2 cm or unicentric cT1-2N0-1M0 triple-negative breast cancer. Patients in the study underwent radiotherapy alone after excluding invasive in-situ disease. 

 

The Clinician’s Role in Shaping Conservative Surgical Approaches

De-escalating surgery in breast cancer should involve acknowledging the patient’s fears and misperceptions regarding the risks of cancer recurrence that can lead them to opt for more invasive surgical treatments. Patients may not or fully regard the long-term effects of electing an invasive procedure in the absence of clinical indications. For example, patients undergoing more invasive interventions may experience worse body image and quality of life. 

Clinicians may also not adequately estimate other harms associated with unnecessary surgical interventions. Providing clinicians with data that focuses on the psychological outcomes and satisfaction of patients post surgery may help them to better interpret and consider patient values and wishes and minimize future unnecessary surgeries.

Breast cancer remains one of the best-studied cancers with multiple high-quality randomized controlled trials supporting de-escalation of surgery. De-escalation of breast cancer surgery has been successful in multiple ways, including the implementation of ALND in early-stage breast cancer. However, other options such as CPM remain common. Proper patient and physician education involving data from clinical trials and reports of patient satisfaction may further decrease unnecessary surgical interventions.

Nameera Temkar has disclosed no relevant financial relationships.

A version of this article first appeared on Medscape.com.

TOPLINE: A national survey of 8996 females reveals comparable mammography screening rates between those who identify as veterans (57.9%) and nonveterans (55.2%).

METHODOLOGY:

• Researchers analyzed data from the 2019 National Health Interview Survey, a cross-sectional national survey tracking health information.

• Female respondents aged 40 to 74 years without history of breast cancer were included in the analysis.

• Analysis evaluated the association between screening and veteran status through logistic regression, adjusting for potential confounders.

• Survey procedures accounted for complex sampling design to obtain valid estimates for the civilian, noninstitutionalized US population.

TAKEAWAY:

• Analysis included 8996 female survey respondents, including 169 veterans (1.9%) and 320 (3.2%) reported having military health coverage.

• Mammography screening rates within the last year were comparable between veterans (57.9%) and nonveterans (55.2%).

• Veteran status showed no significant association with differences in mammography screening percentages (P = .96).

• Among insured participants, military health insurance demonstrated no significant association with mammography screening percentages (P = .13).

• The authors suggest that radiology practices should design proactive outreach strategies to address the needs of the growing number of female veterans who may face increased breast cancer risk due to military environmental exposures.

IN PRACTICE: “Although the results from our study demonstrate comparable mammography screening percentages, veterans may face additional risk factors for breast cancer due to occupational,” the authors argue.

SOURCE: This summary is based on a preprint published online in the Journal of the American College of Radiology: Milton A, Miles R, Gettle LM, Van Geertruyden P, Narayan AK. Utilization of Mammography Screening in Female Veterans: Cross-Sectional Survey Results from the National Health Interview Survey. J Am Coll Radiol. Published online April 24, 2025. doi:10.1016/j.jacr.2025.04.017

LIMITATIONS: The study relied on self-reported adherence data, which could overestimate screening percentages. Data collection occurred prior to updated United States Preventive Services Task Force guidelines recommending routine mammography screening for women starting at age 40 years every 2 years. The relatively small number of female veteran respondents limited the precision of population estimates. Additionally, the data were collected before the COVID-19 pandemic, which has been associated with reduced mammographic screening, particularly in medically underserved populations.

DISCLOSURES: Anand Narayan disclosed receiving financial support from Susan G. Komen Breast Cancer Foundation and National Academy of Medicine. The study did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. The remaining authors reported no potential conflicts of interest. Additional disclosures are noted in the original article.

This article was created using several editorial tools, including AI, as part of the process. Human editors reviewed this content before publication.

TOPLINE: A national survey of 8996 females reveals comparable mammography screening rates between those who identify as veterans (57.9%) and nonveterans (55.2%).

METHODOLOGY:

• Researchers analyzed data from the 2019 National Health Interview Survey, a cross-sectional national survey tracking health information.

• Female respondents aged 40 to 74 years without history of breast cancer were included in the analysis.

• Analysis evaluated the association between screening and veteran status through logistic regression, adjusting for potential confounders.

• Survey procedures accounted for complex sampling design to obtain valid estimates for the civilian, noninstitutionalized US population.

TAKEAWAY:

• Analysis included 8996 female survey respondents, including 169 veterans (1.9%) and 320 (3.2%) reported having military health coverage.

• Mammography screening rates within the last year were comparable between veterans (57.9%) and nonveterans (55.2%).

• Veteran status showed no significant association with differences in mammography screening percentages (P = .96).

• Among insured participants, military health insurance demonstrated no significant association with mammography screening percentages (P = .13).

• The authors suggest that radiology practices should design proactive outreach strategies to address the needs of the growing number of female veterans who may face increased breast cancer risk due to military environmental exposures.

IN PRACTICE: “Although the results from our study demonstrate comparable mammography screening percentages, veterans may face additional risk factors for breast cancer due to occupational,” the authors argue.

SOURCE: This summary is based on a preprint published online in the Journal of the American College of Radiology: Milton A, Miles R, Gettle LM, Van Geertruyden P, Narayan AK. Utilization of Mammography Screening in Female Veterans: Cross-Sectional Survey Results from the National Health Interview Survey. J Am Coll Radiol. Published online April 24, 2025. doi:10.1016/j.jacr.2025.04.017

LIMITATIONS: The study relied on self-reported adherence data, which could overestimate screening percentages. Data collection occurred prior to updated United States Preventive Services Task Force guidelines recommending routine mammography screening for women starting at age 40 years every 2 years. The relatively small number of female veteran respondents limited the precision of population estimates. Additionally, the data were collected before the COVID-19 pandemic, which has been associated with reduced mammographic screening, particularly in medically underserved populations.

DISCLOSURES: Anand Narayan disclosed receiving financial support from Susan G. Komen Breast Cancer Foundation and National Academy of Medicine. The study did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. The remaining authors reported no potential conflicts of interest. Additional disclosures are noted in the original article.

This article was created using several editorial tools, including AI, as part of the process. Human editors reviewed this content before publication.

TOPLINE: A national survey of 8996 females reveals comparable mammography screening rates between those who identify as veterans (57.9%) and nonveterans (55.2%).

METHODOLOGY:

• Researchers analyzed data from the 2019 National Health Interview Survey, a cross-sectional national survey tracking health information.

• Female respondents aged 40 to 74 years without history of breast cancer were included in the analysis.

• Analysis evaluated the association between screening and veteran status through logistic regression, adjusting for potential confounders.

• Survey procedures accounted for complex sampling design to obtain valid estimates for the civilian, noninstitutionalized US population.

TAKEAWAY:

• Analysis included 8996 female survey respondents, including 169 veterans (1.9%) and 320 (3.2%) reported having military health coverage.

• Mammography screening rates within the last year were comparable between veterans (57.9%) and nonveterans (55.2%).

• Veteran status showed no significant association with differences in mammography screening percentages (P = .96).

• Among insured participants, military health insurance demonstrated no significant association with mammography screening percentages (P = .13).

• The authors suggest that radiology practices should design proactive outreach strategies to address the needs of the growing number of female veterans who may face increased breast cancer risk due to military environmental exposures.

IN PRACTICE: “Although the results from our study demonstrate comparable mammography screening percentages, veterans may face additional risk factors for breast cancer due to occupational,” the authors argue.

SOURCE: This summary is based on a preprint published online in the Journal of the American College of Radiology: Milton A, Miles R, Gettle LM, Van Geertruyden P, Narayan AK. Utilization of Mammography Screening in Female Veterans: Cross-Sectional Survey Results from the National Health Interview Survey. J Am Coll Radiol. Published online April 24, 2025. doi:10.1016/j.jacr.2025.04.017

LIMITATIONS: The study relied on self-reported adherence data, which could overestimate screening percentages. Data collection occurred prior to updated United States Preventive Services Task Force guidelines recommending routine mammography screening for women starting at age 40 years every 2 years. The relatively small number of female veteran respondents limited the precision of population estimates. Additionally, the data were collected before the COVID-19 pandemic, which has been associated with reduced mammographic screening, particularly in medically underserved populations.

DISCLOSURES: Anand Narayan disclosed receiving financial support from Susan G. Komen Breast Cancer Foundation and National Academy of Medicine. The study did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. The remaining authors reported no potential conflicts of interest. Additional disclosures are noted in the original article.

This article was created using several editorial tools, including AI, as part of the process. Human editors reviewed this content before publication.