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Democratic Lawmakers Press Pfizer on Chemotherapy Drug Shortages
In a statement about their February 21 action, the legislators, led by Rep. Jamie Raskin (D-Md.), the committee’s ranking minority member, described their work as a follow up to an earlier investigation into price hikes of generic drugs. While the committee members queried Pfizer over the three oncology medications only, they also sent letters to drugmakers Teva and Sandoz with respect to shortages in other drug classes.
A representative for Pfizer confirmed to MDedge Oncology that the company had received the representatives’ letter but said “we have no further details to provide at this time.”
What is the basis for concern?
All three generic chemotherapy drugs are mainstay treatments used across a broad array of cancers. Though shortages have been reported for several years, they became especially acute after December 2022, when an inspection by the US Food and Drug Administration (FDA) led to regulatory action against an Indian manufacturer, Intas, that produced up to half of the platinum-based therapies supplied globally. The National Comprehensive Cancer Care Network reported in October 2023 that more than 90% of its member centers were struggling to maintain adequate supplies of carboplatin, and 70% had trouble obtaining cisplatin, while the American Society of Clinical Oncology published clinical guidance on alternative treatment strategies.
What has the government done in response to the recent shortages?
The White House and the FDA announced in September that they were working with several manufacturers to help increase supplies of the platinum-based chemotherapies and of methotrexate, and taking measures that included relaxing rules on imports. Recent guidance under a pandemic-era federal law, the 2020 CARES Act, strengthened manufacturer reporting requirements related to drug shortages, and other measures have been proposed. While federal regulators have many tools with which to address drug shortages, they cannot legally oblige a manufacturer to increase production of a drug.
What can the lawmakers expect to achieve with their letter?
By pressuring Pfizer publicly, the lawmakers may be able to nudge the company to take measures to assure more consistent supplies of the three drugs. The lawmakers also said they hoped to glean from Pfizer more insight into the root causes of the shortages and potential remedies. They noted that, in a May 2023 letter by Pfizer to customers, the company had warned of depleted and limited supplies of the three drugs and said it was “working diligently” to increase output. However, the lawmakers wrote, “the root cause is not yet resolved and carboplatin, cisplatin, and methotrexate continue to experience residual delays.”
Why did the committee target Pfizer specifically?
Pfizer and its subsidiaries are among the major manufacturers of the three generic chemotherapy agents mentioned in the letter. The legislators noted that “pharmaceutical companies may not be motivated to produce generic drugs like carboplatin, cisplatin, and methotrexate, because they are not as lucrative as producing patented brand name drugs,” and that “as a principal supplier of carboplatin, cisplatin, and methotrexate, it is critical that Pfizer continues to increase production of these life-sustaining cancer medications, even amidst potential lower profitability.”
The committee members also made reference to news reports of price-gouging with these medications, as smaller hospitals or oncology centers are forced to turn to unscrupulous third-party suppliers.
What is being demanded of Pfizer?
Pfizer was given until March 6 to respond, in writing and in a briefing with committee staff, to a six questions. These queries concern what specific steps the company has taken to increase supplies of the three generic oncology drugs, what Pfizer is doing to help avert price-gouging, whether further oncology drug shortages are anticipated, and how the company is working with the FDA on the matter.
In a statement about their February 21 action, the legislators, led by Rep. Jamie Raskin (D-Md.), the committee’s ranking minority member, described their work as a follow up to an earlier investigation into price hikes of generic drugs. While the committee members queried Pfizer over the three oncology medications only, they also sent letters to drugmakers Teva and Sandoz with respect to shortages in other drug classes.
A representative for Pfizer confirmed to MDedge Oncology that the company had received the representatives’ letter but said “we have no further details to provide at this time.”
What is the basis for concern?
All three generic chemotherapy drugs are mainstay treatments used across a broad array of cancers. Though shortages have been reported for several years, they became especially acute after December 2022, when an inspection by the US Food and Drug Administration (FDA) led to regulatory action against an Indian manufacturer, Intas, that produced up to half of the platinum-based therapies supplied globally. The National Comprehensive Cancer Care Network reported in October 2023 that more than 90% of its member centers were struggling to maintain adequate supplies of carboplatin, and 70% had trouble obtaining cisplatin, while the American Society of Clinical Oncology published clinical guidance on alternative treatment strategies.
What has the government done in response to the recent shortages?
The White House and the FDA announced in September that they were working with several manufacturers to help increase supplies of the platinum-based chemotherapies and of methotrexate, and taking measures that included relaxing rules on imports. Recent guidance under a pandemic-era federal law, the 2020 CARES Act, strengthened manufacturer reporting requirements related to drug shortages, and other measures have been proposed. While federal regulators have many tools with which to address drug shortages, they cannot legally oblige a manufacturer to increase production of a drug.
What can the lawmakers expect to achieve with their letter?
By pressuring Pfizer publicly, the lawmakers may be able to nudge the company to take measures to assure more consistent supplies of the three drugs. The lawmakers also said they hoped to glean from Pfizer more insight into the root causes of the shortages and potential remedies. They noted that, in a May 2023 letter by Pfizer to customers, the company had warned of depleted and limited supplies of the three drugs and said it was “working diligently” to increase output. However, the lawmakers wrote, “the root cause is not yet resolved and carboplatin, cisplatin, and methotrexate continue to experience residual delays.”
Why did the committee target Pfizer specifically?
Pfizer and its subsidiaries are among the major manufacturers of the three generic chemotherapy agents mentioned in the letter. The legislators noted that “pharmaceutical companies may not be motivated to produce generic drugs like carboplatin, cisplatin, and methotrexate, because they are not as lucrative as producing patented brand name drugs,” and that “as a principal supplier of carboplatin, cisplatin, and methotrexate, it is critical that Pfizer continues to increase production of these life-sustaining cancer medications, even amidst potential lower profitability.”
The committee members also made reference to news reports of price-gouging with these medications, as smaller hospitals or oncology centers are forced to turn to unscrupulous third-party suppliers.
What is being demanded of Pfizer?
Pfizer was given until March 6 to respond, in writing and in a briefing with committee staff, to a six questions. These queries concern what specific steps the company has taken to increase supplies of the three generic oncology drugs, what Pfizer is doing to help avert price-gouging, whether further oncology drug shortages are anticipated, and how the company is working with the FDA on the matter.
In a statement about their February 21 action, the legislators, led by Rep. Jamie Raskin (D-Md.), the committee’s ranking minority member, described their work as a follow up to an earlier investigation into price hikes of generic drugs. While the committee members queried Pfizer over the three oncology medications only, they also sent letters to drugmakers Teva and Sandoz with respect to shortages in other drug classes.
A representative for Pfizer confirmed to MDedge Oncology that the company had received the representatives’ letter but said “we have no further details to provide at this time.”
What is the basis for concern?
All three generic chemotherapy drugs are mainstay treatments used across a broad array of cancers. Though shortages have been reported for several years, they became especially acute after December 2022, when an inspection by the US Food and Drug Administration (FDA) led to regulatory action against an Indian manufacturer, Intas, that produced up to half of the platinum-based therapies supplied globally. The National Comprehensive Cancer Care Network reported in October 2023 that more than 90% of its member centers were struggling to maintain adequate supplies of carboplatin, and 70% had trouble obtaining cisplatin, while the American Society of Clinical Oncology published clinical guidance on alternative treatment strategies.
What has the government done in response to the recent shortages?
The White House and the FDA announced in September that they were working with several manufacturers to help increase supplies of the platinum-based chemotherapies and of methotrexate, and taking measures that included relaxing rules on imports. Recent guidance under a pandemic-era federal law, the 2020 CARES Act, strengthened manufacturer reporting requirements related to drug shortages, and other measures have been proposed. While federal regulators have many tools with which to address drug shortages, they cannot legally oblige a manufacturer to increase production of a drug.
What can the lawmakers expect to achieve with their letter?
By pressuring Pfizer publicly, the lawmakers may be able to nudge the company to take measures to assure more consistent supplies of the three drugs. The lawmakers also said they hoped to glean from Pfizer more insight into the root causes of the shortages and potential remedies. They noted that, in a May 2023 letter by Pfizer to customers, the company had warned of depleted and limited supplies of the three drugs and said it was “working diligently” to increase output. However, the lawmakers wrote, “the root cause is not yet resolved and carboplatin, cisplatin, and methotrexate continue to experience residual delays.”
Why did the committee target Pfizer specifically?
Pfizer and its subsidiaries are among the major manufacturers of the three generic chemotherapy agents mentioned in the letter. The legislators noted that “pharmaceutical companies may not be motivated to produce generic drugs like carboplatin, cisplatin, and methotrexate, because they are not as lucrative as producing patented brand name drugs,” and that “as a principal supplier of carboplatin, cisplatin, and methotrexate, it is critical that Pfizer continues to increase production of these life-sustaining cancer medications, even amidst potential lower profitability.”
The committee members also made reference to news reports of price-gouging with these medications, as smaller hospitals or oncology centers are forced to turn to unscrupulous third-party suppliers.
What is being demanded of Pfizer?
Pfizer was given until March 6 to respond, in writing and in a briefing with committee staff, to a six questions. These queries concern what specific steps the company has taken to increase supplies of the three generic oncology drugs, what Pfizer is doing to help avert price-gouging, whether further oncology drug shortages are anticipated, and how the company is working with the FDA on the matter.
Is Mammography Ready for AI? Opinions Mixed on Usage, Cost Methods
Screening mammograms miss close to one in eight breast cancers. But early research suggests artificial intelligence (AI) could close this detection gap and markedly improve early diagnosis of the disease. Still, questions remain regarding how to best incorporate AI into screenings and whether it’s too soon to deploy the technology.
Already, some radiology clinics are offering AI analysis of mammograms through an add-on cost method.
Mammography patients who visit RadNet facilities, for example, have the option of an additional AI screening of their images. RadNet, the largest national owner and operator of fixed-site diagnostic imaging centers in the United States with more than 370 locations, first launched its AI program in the Northeast. The company has now rolled out its product across all regions in the country.
Because the AI is not reimbursed by insurers, patients must pay a $40 out-of-pocket fee if they want the AI analysis.
“RadNet practices have identified more than 400 women whose cancer was found earlier than it would have been had the AI not been present,” said Greg Sorensen MD, chief science officer for RadNet.
How RadNet’s AI Program Works
Patients coming to RadNet facilities for screening mammography undergo 3D high-resolution mammography that includes the use of 70-micron resolution detector technology, said Dr. Sorensen. The mammogram is reviewed by a qualified radiologist with assistance from two Food and Drug Administration–cleared AI programs, Saige-Q and Saige-Density. The radiologist then makes an interpretation.
Saige-Q is an AI tool that helps identify more suspicious mammograms by providing a quick signal to radiologists if the AI considers a given mammogram to be in a suspicious category, according to Dr. Sorensen. Saige-Density provides a density rating for each mammogram using one of the four standard categories:
- A. Almost entirely fatty
- B. Scattered areas of fibroglandular density
- C. Heterogeneously dense
- D. Extremely dense
Starting in September 2024, the FDA will require all mammogram reports to indicate density.
For patients who choose the $40 add-on service, called Enhanced Breast Cancer Detection, two other FDA-registered AI programs are also applied: Saige-Dx and Saige-Assure. These AI programs go a step further by placing marks on areas within the images that they find suspicious. Mammograms flagged as “high-suspicion” by the AI are then reviewed by a second human radiologist. The first and second radiologists confer to agree on a final diagnosis, Dr. Sorensen explained.
“Our research shows that approximately 20% more cancers are found when the safeguard review process is in place,” Dr. Sorensen said. “We also have seen [30%] decreases in recall rates” — the percentage of screening cases in which further tests are recommended by the radiologist.
Bethesda radiologist Janet Storella, MD, has used the AI program for about 3 years and said the technology has improved her screening performance.
The AI is linked to her practice’s imaging software, and radiologists have the option of turning the AI on at any time during their reading of screening mammograms, Dr. Storella explained. Some radiologists review the mammogram first and then initiate the AI, while others like Dr. Storella turn it on at the start, she said. Once initiated, the AI draws bounding boxes — or outlines — around areas that it deems suspicious.
The AI helps focus Dr. Storella’s attention on suspicious areas and grades the level of suspicion into one of four categories: high, intermediate, low, and minimal, she said.
“I find it especially useful in patients who have dense breast tissue,” said Dr. Storella, medical director of women’s imaging at Community Radiology Associates, a RadNet practice. “In these situations, the tissue on the mammogram is a field of white, and cancers are also white, so you’re looking for that little white golf ball on a sea of snow. The AI really helps hone that down to specific areas.”
About 35% of RadNet’s screening mammography patients have enrolled in the Enhanced Breast Cancer Detection program, according to RadNet data. In a recent study of nine general radiologists and nine breast imaging specialists, all radiologists improved their interpretation performance of DBT screening mammograms when reading with RadNet’s AI versus without it. (An average AUC [area under the receiver operating characteristic curve] of 0.93 versus 0.87, demonstrating a difference in AUC of 0.06 (95% CI, 0.04-0.08; P < .001)
Is Mammography Ready for AI?
RadNet is among a growing number of commercial companies offering AI solutions for mammography. MammoScreen and Hologic, for example, are two other companies that provide AI programs to assist radiologists in reading screening mammograms.
“We are at the start of the AI integration into breast imaging at this point,” said Laura Heacock, MD, a breast imaging radiologist and associate professor of radiology at NYU Langone Health. “There are multiple commercial AI models now available to radiologists to use in their practice [ and] there will likely be more. We’re in the transition stage where people are still deciding: Which is the best model to go with? How do I put it in my system? How do I ensure it works they way it was intended? Every practice and medical system will have a different answer to that question.”
At NYU Langone Health, researchers have been developing and studying optimal AI models for breast imaging for several years, Dr. Heacock said. Researchers thus far, have developed AI models for 2D digital mammography, 3D mammograms, breast ultrasound, and breast MRI. Similar to commercial AI systems, the AI is embedded into the picture archiving and communication (PACS) system used by radiologists to review images. Radiologists press a button to launch the AI, which draws a box around suspicious areas of the image and scores the suspicion.
“I take a look of where it is on the mammogram and decide whether that fits my level of suspicion,” Dr. Heacock said. The AI may not understand things about the mammogram like we do. For example, surgical scars look very suspicious to an AI model. But if I’m looking at a mammogram where [the patient] has had a stable scar that hasn’t changed in 10 years, I’m not concerned that the AI found it suspicious. My clinical judgment is the ultimate decider. This is just an additional piece of information that’s helpful to me.”
Research by New York University (NYU) has shown that when used by an expert radiologist the AI models have improved breast cancer detection in all four modalities, she said.
However, the AI has not yet launched at NYU Langone. More research is needed before deploying the technology, according to Dr. Heacock.
“At NYU, we are still testing the benefits to patients,” she said. “We know it improves cancer detection, but we want to make sure there are no drawbacks. We are still exploring the best ways to put it into effect at our institution.”
Dr. Heacock pointed to recent studies on AI in screening mammography that show promise.
An analysis of more than 80,000 women, for example, published in The Lancet Oncology in August, found that AI-supported screen reading led to a similar cancer detection rate as compared with a two-person reader system. This screening resulted in 244 screen-detected cancers, 861 recalls, and a total of 46,345 screen readings, according to the study. Standard screening resulted in 203 screen-detected cancers, 817 recalls, and a total of 83,231 screen readings.
The AI system also reduced the screen-reading workload for radiologists by 44%, the study found.
Meanwhile, a September 2023 study, published in The Lancet Digital Health, found that replacing one radiologist with AI resulted in more cancer detection without a large increase in false-positive cases. The AI led to a 4% higher, noninferior cancer detection rate, compared with radiologist double reading, the study found.
Dr. Heacock emphasized that both studies were conducted in Europe where the standard is for two radiologists to evaluate mammograms.
“That makes the results exciting, but not directly applicable to US practice just yet,” she said.
What Do the Experts Recommend?
Stamatia V. Destounis, MD, FACR, chair of the American College of Radiology (ACR) Breast Imaging Commission, said the college welcomes ongoing research into the efficacy of AI technologies and that AI may prove to be beneficial as an improved workflow tool.
The ACR has not released any guidance about the use of AI for radiologists and have no recommendation about best practices, Dr. Destounis said.
“The decisions regarding which technologies that various health systems and radiology sites choose to use are made by those facilities,” she said.
Dr. Destounis said more research is needed to demonstrate whether or not AI technologies help radiologists produce better results in identifying disease, injury, and illnesses among the general population or in specific groups — whether based on age, physical characteristics, race, ethnicity or risk status for breast cancer.
“Also, a way to measure each AI product is needed so that we can be certain they are relatively equivalent in their efficacy and accuracy — initially and over a prolonged period of time,” she said.
No consensus or concrete recommendation exists about the use of AI in mammography screening, adds Peter P. Yu, MD, FACP, FASCO, physician-in-chief at the Hartford HealthCare Cancer Institute and a member of the newly-created American Society of Clinical Oncology AI task force.
One of the many discussions concerning AI is to what degree patients should be aware that AI is being used in their healthcare and whether they should be required to give consent to its use, Dr. Yu said.
If AI is used to assist radiologists with mammographic interpretation, radiologists should discuss with patients how it’s being used and explain the ultimate reading is in the hands of their physician radiologist, he said.
“In the unlikely situation where there wasn’t a human in the loop and AI was in effect making a medical decision, the patient needs to be aware,” he said. “I’m not aware that any such situation exists today. AI is more likely to be subtly embedded in the software that operates technology, much like it is embedded in manufacturing and transportation.”
Who Will Pay for AI?
When it comes to payment, Dr. Yu said shifting the cost of AI to patients creates serious risk.
“It has enormous potential to increase health inequities,” he said. “If we believe health care is a fundamental human right, AI should inure to the benefit of all, not just those who can afford it. Healthcare should not be a luxury item; if it works, it works for all.”
In general, the issue of payment for AI is still pretty “thorny,” Dr. Heacock noted. Currently, there’s no way for physicians to request direct reimbursement for AI reads of mammograms.
While Dr. Heacock says she is sympathetic to the companies that spend significant time and effort on their AI technology, she doesn’t think charging patients is the right solution.
“We know that many women already have difficulty in paying for mammography-related services and this is just one more charge to confuse them or that they can’t pay,” she said.
Dr. Sorensen expects that, similar to 3D mammography, payers will eventually cover RadNet’s AI technology and that patients will no longer need to pay out of pocket. One Blue Cross carrier will start covering the AI in April 2024, he said.
Screening mammograms miss close to one in eight breast cancers. But early research suggests artificial intelligence (AI) could close this detection gap and markedly improve early diagnosis of the disease. Still, questions remain regarding how to best incorporate AI into screenings and whether it’s too soon to deploy the technology.
Already, some radiology clinics are offering AI analysis of mammograms through an add-on cost method.
Mammography patients who visit RadNet facilities, for example, have the option of an additional AI screening of their images. RadNet, the largest national owner and operator of fixed-site diagnostic imaging centers in the United States with more than 370 locations, first launched its AI program in the Northeast. The company has now rolled out its product across all regions in the country.
Because the AI is not reimbursed by insurers, patients must pay a $40 out-of-pocket fee if they want the AI analysis.
“RadNet practices have identified more than 400 women whose cancer was found earlier than it would have been had the AI not been present,” said Greg Sorensen MD, chief science officer for RadNet.
How RadNet’s AI Program Works
Patients coming to RadNet facilities for screening mammography undergo 3D high-resolution mammography that includes the use of 70-micron resolution detector technology, said Dr. Sorensen. The mammogram is reviewed by a qualified radiologist with assistance from two Food and Drug Administration–cleared AI programs, Saige-Q and Saige-Density. The radiologist then makes an interpretation.
Saige-Q is an AI tool that helps identify more suspicious mammograms by providing a quick signal to radiologists if the AI considers a given mammogram to be in a suspicious category, according to Dr. Sorensen. Saige-Density provides a density rating for each mammogram using one of the four standard categories:
- A. Almost entirely fatty
- B. Scattered areas of fibroglandular density
- C. Heterogeneously dense
- D. Extremely dense
Starting in September 2024, the FDA will require all mammogram reports to indicate density.
For patients who choose the $40 add-on service, called Enhanced Breast Cancer Detection, two other FDA-registered AI programs are also applied: Saige-Dx and Saige-Assure. These AI programs go a step further by placing marks on areas within the images that they find suspicious. Mammograms flagged as “high-suspicion” by the AI are then reviewed by a second human radiologist. The first and second radiologists confer to agree on a final diagnosis, Dr. Sorensen explained.
“Our research shows that approximately 20% more cancers are found when the safeguard review process is in place,” Dr. Sorensen said. “We also have seen [30%] decreases in recall rates” — the percentage of screening cases in which further tests are recommended by the radiologist.
Bethesda radiologist Janet Storella, MD, has used the AI program for about 3 years and said the technology has improved her screening performance.
The AI is linked to her practice’s imaging software, and radiologists have the option of turning the AI on at any time during their reading of screening mammograms, Dr. Storella explained. Some radiologists review the mammogram first and then initiate the AI, while others like Dr. Storella turn it on at the start, she said. Once initiated, the AI draws bounding boxes — or outlines — around areas that it deems suspicious.
The AI helps focus Dr. Storella’s attention on suspicious areas and grades the level of suspicion into one of four categories: high, intermediate, low, and minimal, she said.
“I find it especially useful in patients who have dense breast tissue,” said Dr. Storella, medical director of women’s imaging at Community Radiology Associates, a RadNet practice. “In these situations, the tissue on the mammogram is a field of white, and cancers are also white, so you’re looking for that little white golf ball on a sea of snow. The AI really helps hone that down to specific areas.”
About 35% of RadNet’s screening mammography patients have enrolled in the Enhanced Breast Cancer Detection program, according to RadNet data. In a recent study of nine general radiologists and nine breast imaging specialists, all radiologists improved their interpretation performance of DBT screening mammograms when reading with RadNet’s AI versus without it. (An average AUC [area under the receiver operating characteristic curve] of 0.93 versus 0.87, demonstrating a difference in AUC of 0.06 (95% CI, 0.04-0.08; P < .001)
Is Mammography Ready for AI?
RadNet is among a growing number of commercial companies offering AI solutions for mammography. MammoScreen and Hologic, for example, are two other companies that provide AI programs to assist radiologists in reading screening mammograms.
“We are at the start of the AI integration into breast imaging at this point,” said Laura Heacock, MD, a breast imaging radiologist and associate professor of radiology at NYU Langone Health. “There are multiple commercial AI models now available to radiologists to use in their practice [ and] there will likely be more. We’re in the transition stage where people are still deciding: Which is the best model to go with? How do I put it in my system? How do I ensure it works they way it was intended? Every practice and medical system will have a different answer to that question.”
At NYU Langone Health, researchers have been developing and studying optimal AI models for breast imaging for several years, Dr. Heacock said. Researchers thus far, have developed AI models for 2D digital mammography, 3D mammograms, breast ultrasound, and breast MRI. Similar to commercial AI systems, the AI is embedded into the picture archiving and communication (PACS) system used by radiologists to review images. Radiologists press a button to launch the AI, which draws a box around suspicious areas of the image and scores the suspicion.
“I take a look of where it is on the mammogram and decide whether that fits my level of suspicion,” Dr. Heacock said. The AI may not understand things about the mammogram like we do. For example, surgical scars look very suspicious to an AI model. But if I’m looking at a mammogram where [the patient] has had a stable scar that hasn’t changed in 10 years, I’m not concerned that the AI found it suspicious. My clinical judgment is the ultimate decider. This is just an additional piece of information that’s helpful to me.”
Research by New York University (NYU) has shown that when used by an expert radiologist the AI models have improved breast cancer detection in all four modalities, she said.
However, the AI has not yet launched at NYU Langone. More research is needed before deploying the technology, according to Dr. Heacock.
“At NYU, we are still testing the benefits to patients,” she said. “We know it improves cancer detection, but we want to make sure there are no drawbacks. We are still exploring the best ways to put it into effect at our institution.”
Dr. Heacock pointed to recent studies on AI in screening mammography that show promise.
An analysis of more than 80,000 women, for example, published in The Lancet Oncology in August, found that AI-supported screen reading led to a similar cancer detection rate as compared with a two-person reader system. This screening resulted in 244 screen-detected cancers, 861 recalls, and a total of 46,345 screen readings, according to the study. Standard screening resulted in 203 screen-detected cancers, 817 recalls, and a total of 83,231 screen readings.
The AI system also reduced the screen-reading workload for radiologists by 44%, the study found.
Meanwhile, a September 2023 study, published in The Lancet Digital Health, found that replacing one radiologist with AI resulted in more cancer detection without a large increase in false-positive cases. The AI led to a 4% higher, noninferior cancer detection rate, compared with radiologist double reading, the study found.
Dr. Heacock emphasized that both studies were conducted in Europe where the standard is for two radiologists to evaluate mammograms.
“That makes the results exciting, but not directly applicable to US practice just yet,” she said.
What Do the Experts Recommend?
Stamatia V. Destounis, MD, FACR, chair of the American College of Radiology (ACR) Breast Imaging Commission, said the college welcomes ongoing research into the efficacy of AI technologies and that AI may prove to be beneficial as an improved workflow tool.
The ACR has not released any guidance about the use of AI for radiologists and have no recommendation about best practices, Dr. Destounis said.
“The decisions regarding which technologies that various health systems and radiology sites choose to use are made by those facilities,” she said.
Dr. Destounis said more research is needed to demonstrate whether or not AI technologies help radiologists produce better results in identifying disease, injury, and illnesses among the general population or in specific groups — whether based on age, physical characteristics, race, ethnicity or risk status for breast cancer.
“Also, a way to measure each AI product is needed so that we can be certain they are relatively equivalent in their efficacy and accuracy — initially and over a prolonged period of time,” she said.
No consensus or concrete recommendation exists about the use of AI in mammography screening, adds Peter P. Yu, MD, FACP, FASCO, physician-in-chief at the Hartford HealthCare Cancer Institute and a member of the newly-created American Society of Clinical Oncology AI task force.
One of the many discussions concerning AI is to what degree patients should be aware that AI is being used in their healthcare and whether they should be required to give consent to its use, Dr. Yu said.
If AI is used to assist radiologists with mammographic interpretation, radiologists should discuss with patients how it’s being used and explain the ultimate reading is in the hands of their physician radiologist, he said.
“In the unlikely situation where there wasn’t a human in the loop and AI was in effect making a medical decision, the patient needs to be aware,” he said. “I’m not aware that any such situation exists today. AI is more likely to be subtly embedded in the software that operates technology, much like it is embedded in manufacturing and transportation.”
Who Will Pay for AI?
When it comes to payment, Dr. Yu said shifting the cost of AI to patients creates serious risk.
“It has enormous potential to increase health inequities,” he said. “If we believe health care is a fundamental human right, AI should inure to the benefit of all, not just those who can afford it. Healthcare should not be a luxury item; if it works, it works for all.”
In general, the issue of payment for AI is still pretty “thorny,” Dr. Heacock noted. Currently, there’s no way for physicians to request direct reimbursement for AI reads of mammograms.
While Dr. Heacock says she is sympathetic to the companies that spend significant time and effort on their AI technology, she doesn’t think charging patients is the right solution.
“We know that many women already have difficulty in paying for mammography-related services and this is just one more charge to confuse them or that they can’t pay,” she said.
Dr. Sorensen expects that, similar to 3D mammography, payers will eventually cover RadNet’s AI technology and that patients will no longer need to pay out of pocket. One Blue Cross carrier will start covering the AI in April 2024, he said.
Screening mammograms miss close to one in eight breast cancers. But early research suggests artificial intelligence (AI) could close this detection gap and markedly improve early diagnosis of the disease. Still, questions remain regarding how to best incorporate AI into screenings and whether it’s too soon to deploy the technology.
Already, some radiology clinics are offering AI analysis of mammograms through an add-on cost method.
Mammography patients who visit RadNet facilities, for example, have the option of an additional AI screening of their images. RadNet, the largest national owner and operator of fixed-site diagnostic imaging centers in the United States with more than 370 locations, first launched its AI program in the Northeast. The company has now rolled out its product across all regions in the country.
Because the AI is not reimbursed by insurers, patients must pay a $40 out-of-pocket fee if they want the AI analysis.
“RadNet practices have identified more than 400 women whose cancer was found earlier than it would have been had the AI not been present,” said Greg Sorensen MD, chief science officer for RadNet.
How RadNet’s AI Program Works
Patients coming to RadNet facilities for screening mammography undergo 3D high-resolution mammography that includes the use of 70-micron resolution detector technology, said Dr. Sorensen. The mammogram is reviewed by a qualified radiologist with assistance from two Food and Drug Administration–cleared AI programs, Saige-Q and Saige-Density. The radiologist then makes an interpretation.
Saige-Q is an AI tool that helps identify more suspicious mammograms by providing a quick signal to radiologists if the AI considers a given mammogram to be in a suspicious category, according to Dr. Sorensen. Saige-Density provides a density rating for each mammogram using one of the four standard categories:
- A. Almost entirely fatty
- B. Scattered areas of fibroglandular density
- C. Heterogeneously dense
- D. Extremely dense
Starting in September 2024, the FDA will require all mammogram reports to indicate density.
For patients who choose the $40 add-on service, called Enhanced Breast Cancer Detection, two other FDA-registered AI programs are also applied: Saige-Dx and Saige-Assure. These AI programs go a step further by placing marks on areas within the images that they find suspicious. Mammograms flagged as “high-suspicion” by the AI are then reviewed by a second human radiologist. The first and second radiologists confer to agree on a final diagnosis, Dr. Sorensen explained.
“Our research shows that approximately 20% more cancers are found when the safeguard review process is in place,” Dr. Sorensen said. “We also have seen [30%] decreases in recall rates” — the percentage of screening cases in which further tests are recommended by the radiologist.
Bethesda radiologist Janet Storella, MD, has used the AI program for about 3 years and said the technology has improved her screening performance.
The AI is linked to her practice’s imaging software, and radiologists have the option of turning the AI on at any time during their reading of screening mammograms, Dr. Storella explained. Some radiologists review the mammogram first and then initiate the AI, while others like Dr. Storella turn it on at the start, she said. Once initiated, the AI draws bounding boxes — or outlines — around areas that it deems suspicious.
The AI helps focus Dr. Storella’s attention on suspicious areas and grades the level of suspicion into one of four categories: high, intermediate, low, and minimal, she said.
“I find it especially useful in patients who have dense breast tissue,” said Dr. Storella, medical director of women’s imaging at Community Radiology Associates, a RadNet practice. “In these situations, the tissue on the mammogram is a field of white, and cancers are also white, so you’re looking for that little white golf ball on a sea of snow. The AI really helps hone that down to specific areas.”
About 35% of RadNet’s screening mammography patients have enrolled in the Enhanced Breast Cancer Detection program, according to RadNet data. In a recent study of nine general radiologists and nine breast imaging specialists, all radiologists improved their interpretation performance of DBT screening mammograms when reading with RadNet’s AI versus without it. (An average AUC [area under the receiver operating characteristic curve] of 0.93 versus 0.87, demonstrating a difference in AUC of 0.06 (95% CI, 0.04-0.08; P < .001)
Is Mammography Ready for AI?
RadNet is among a growing number of commercial companies offering AI solutions for mammography. MammoScreen and Hologic, for example, are two other companies that provide AI programs to assist radiologists in reading screening mammograms.
“We are at the start of the AI integration into breast imaging at this point,” said Laura Heacock, MD, a breast imaging radiologist and associate professor of radiology at NYU Langone Health. “There are multiple commercial AI models now available to radiologists to use in their practice [ and] there will likely be more. We’re in the transition stage where people are still deciding: Which is the best model to go with? How do I put it in my system? How do I ensure it works they way it was intended? Every practice and medical system will have a different answer to that question.”
At NYU Langone Health, researchers have been developing and studying optimal AI models for breast imaging for several years, Dr. Heacock said. Researchers thus far, have developed AI models for 2D digital mammography, 3D mammograms, breast ultrasound, and breast MRI. Similar to commercial AI systems, the AI is embedded into the picture archiving and communication (PACS) system used by radiologists to review images. Radiologists press a button to launch the AI, which draws a box around suspicious areas of the image and scores the suspicion.
“I take a look of where it is on the mammogram and decide whether that fits my level of suspicion,” Dr. Heacock said. The AI may not understand things about the mammogram like we do. For example, surgical scars look very suspicious to an AI model. But if I’m looking at a mammogram where [the patient] has had a stable scar that hasn’t changed in 10 years, I’m not concerned that the AI found it suspicious. My clinical judgment is the ultimate decider. This is just an additional piece of information that’s helpful to me.”
Research by New York University (NYU) has shown that when used by an expert radiologist the AI models have improved breast cancer detection in all four modalities, she said.
However, the AI has not yet launched at NYU Langone. More research is needed before deploying the technology, according to Dr. Heacock.
“At NYU, we are still testing the benefits to patients,” she said. “We know it improves cancer detection, but we want to make sure there are no drawbacks. We are still exploring the best ways to put it into effect at our institution.”
Dr. Heacock pointed to recent studies on AI in screening mammography that show promise.
An analysis of more than 80,000 women, for example, published in The Lancet Oncology in August, found that AI-supported screen reading led to a similar cancer detection rate as compared with a two-person reader system. This screening resulted in 244 screen-detected cancers, 861 recalls, and a total of 46,345 screen readings, according to the study. Standard screening resulted in 203 screen-detected cancers, 817 recalls, and a total of 83,231 screen readings.
The AI system also reduced the screen-reading workload for radiologists by 44%, the study found.
Meanwhile, a September 2023 study, published in The Lancet Digital Health, found that replacing one radiologist with AI resulted in more cancer detection without a large increase in false-positive cases. The AI led to a 4% higher, noninferior cancer detection rate, compared with radiologist double reading, the study found.
Dr. Heacock emphasized that both studies were conducted in Europe where the standard is for two radiologists to evaluate mammograms.
“That makes the results exciting, but not directly applicable to US practice just yet,” she said.
What Do the Experts Recommend?
Stamatia V. Destounis, MD, FACR, chair of the American College of Radiology (ACR) Breast Imaging Commission, said the college welcomes ongoing research into the efficacy of AI technologies and that AI may prove to be beneficial as an improved workflow tool.
The ACR has not released any guidance about the use of AI for radiologists and have no recommendation about best practices, Dr. Destounis said.
“The decisions regarding which technologies that various health systems and radiology sites choose to use are made by those facilities,” she said.
Dr. Destounis said more research is needed to demonstrate whether or not AI technologies help radiologists produce better results in identifying disease, injury, and illnesses among the general population or in specific groups — whether based on age, physical characteristics, race, ethnicity or risk status for breast cancer.
“Also, a way to measure each AI product is needed so that we can be certain they are relatively equivalent in their efficacy and accuracy — initially and over a prolonged period of time,” she said.
No consensus or concrete recommendation exists about the use of AI in mammography screening, adds Peter P. Yu, MD, FACP, FASCO, physician-in-chief at the Hartford HealthCare Cancer Institute and a member of the newly-created American Society of Clinical Oncology AI task force.
One of the many discussions concerning AI is to what degree patients should be aware that AI is being used in their healthcare and whether they should be required to give consent to its use, Dr. Yu said.
If AI is used to assist radiologists with mammographic interpretation, radiologists should discuss with patients how it’s being used and explain the ultimate reading is in the hands of their physician radiologist, he said.
“In the unlikely situation where there wasn’t a human in the loop and AI was in effect making a medical decision, the patient needs to be aware,” he said. “I’m not aware that any such situation exists today. AI is more likely to be subtly embedded in the software that operates technology, much like it is embedded in manufacturing and transportation.”
Who Will Pay for AI?
When it comes to payment, Dr. Yu said shifting the cost of AI to patients creates serious risk.
“It has enormous potential to increase health inequities,” he said. “If we believe health care is a fundamental human right, AI should inure to the benefit of all, not just those who can afford it. Healthcare should not be a luxury item; if it works, it works for all.”
In general, the issue of payment for AI is still pretty “thorny,” Dr. Heacock noted. Currently, there’s no way for physicians to request direct reimbursement for AI reads of mammograms.
While Dr. Heacock says she is sympathetic to the companies that spend significant time and effort on their AI technology, she doesn’t think charging patients is the right solution.
“We know that many women already have difficulty in paying for mammography-related services and this is just one more charge to confuse them or that they can’t pay,” she said.
Dr. Sorensen expects that, similar to 3D mammography, payers will eventually cover RadNet’s AI technology and that patients will no longer need to pay out of pocket. One Blue Cross carrier will start covering the AI in April 2024, he said.
Unleashing Our Immune Response to Quash Cancer
This article was originally published on February 10 in Eric Topol’s substack “Ground Truths.”
It’s astounding how devious cancer cells and tumor tissue can be. This week in Science we learned how certain lung cancer cells can function like “Catch Me If You Can” — changing their driver mutation and cell identity to escape targeted therapy. This histologic transformation, as seen in an experimental model, is just one of so many cancer tricks that we are learning about.
Recently, as shown by single-cell sequencing, cancer cells can steal the mitochondria from T cells, a double whammy that turbocharges cancer cells with the hijacked fuel supply and, at the same time, dismantles the immune response.
Last week, we saw how tumor cells can release a virus-like protein that unleashes a vicious autoimmune response.
And then there’s the finding that cancer cell spread predominantly is occurring while we sleep.
As I previously reviewed, the ability for cancer cells to hijack neurons and neural circuits is now well established, no less their ability to reprogram neurons to become adrenergic and stimulate tumor progression, and interfere with the immune response. Stay tuned on that for a new Ground Truths podcast with Prof Michelle Monje, a leader in cancer neuroscience, which will post soon.
Add advancing age’s immunosenescence as yet another challenge to the long and growing list of formidable ways that cancer cells, and the tumor microenvironment, evade our immune response.
An Ever-Expanding Armamentarium
Immune Checkpoint Inhibitors
The field of immunotherapies took off with the immune checkpoint inhibitors, first approved by the FDA in 2011, that take the brakes off of T cells, with the programmed death-1 (PD-1), PD-ligand1, and anti-CTLA-4 monoclonal antibodies.
But we’re clearly learning they are not enough to prevail over cancer with common recurrences, only short term success in most patients, with some notable exceptions. Adding other immune response strategies, such as a vaccine, or antibody-drug conjugates, or engineered T cells, are showing improved chances for success.
Therapeutic Cancer Vaccines
There are many therapeutic cancer vaccines in the works, as reviewed in depth here.
Here’s a list of ongoing clinical trials of cancer vaccines. You’ll note most of these are on top of a checkpoint inhibitor and use personalized neoantigens (cancer cell surface proteins) derived from sequencing (whole-exome or whole genome, RNA-sequencing and HLA-profiling) the patient’s tumor.
An example of positive findings is with the combination of an mRNA-nanoparticle vaccine with up to 34 personalized neoantigens and pembrolizumab (Keytruda) vs pembrolizumab alone in advanced melanoma after resection, with improved outcomes at 3-year follow-up, cutting death or relapse rate in half.
Antibody-Drug Conjugates (ADC)
There is considerable excitement about antibody-drug conjugates (ADC) whereby a linker is used to attach a chemotherapy agent to the checkpoint inhibitor antibody, specifically targeting the cancer cell and facilitating entry of the chemotherapy into the cell. Akin to these are bispecific antibodies (BiTEs, binding to a tumor antigen and T cell receptor simultaneously), both of these conjugates acting as “biologic” or “guided” missiles.
A very good example of the potency of an ADC was seen in a “HER2-low” breast cancer randomized trial. The absence or very low expression or amplification of the HER2 receptor is common in breast cancer and successful treatment has been elusive. A randomized trial of an ADC (trastuzumab deruxtecan) compared to physician’s choice therapy demonstrated a marked success for progression-free survival in HER2-low patients, which was characterized as “unheard-of success” by media coverage.
This strategy is being used to target some of the most difficult cancer driver mutations such as TP53 and KRAS.
Oncolytic Viruses
Modifying viruses to infect the tumor and make it more visible to the immune system, potentiating anti-tumor responses, known as oncolytic viruses, have been proposed as a way to rev up the immune response for a long time but without positive Phase 3 clinical trials.
After decades of failure, a recent trial in refractory bladder cancer showed marked success, along with others, summarized here, now providing very encouraging results. It looks like oncolytic viruses are on a comeback path.
Engineering T Cells (Chimeric Antigen Receptor [CAR-T])
As I recently reviewed, there are over 500 ongoing clinical trials to build on the success of the first CAR-T approval for leukemia 7 years ago. I won’t go through that all again here, but to reiterate most of the success to date has been in “liquid” blood (leukemia and lymphoma) cancer tumors. This week in Nature is the discovery of a T cell cancer mutation, a gene fusion CARD11-PIK3R3, from a T cell lymphoma that can potentially be used to augment CAR-T efficacy. It has pronounced and prolonged effects in the experimental model. Instead of 1 million cells needed for treatment, even 20,000 were enough to melt the tumor. This is a noteworthy discovery since CAR-T work to date has largely not exploited such naturally occurring mutations, while instead concentrating on those seen in the patient’s set of key tumor mutations.
As currently conceived, CAR-T, and what is being referred to more broadly as adoptive cell therapies, involves removing T cells from the patient’s body and engineering their activation, then reintroducing them back to the patient. This is laborious, technically difficult, and very expensive. Recently, the idea of achieving all of this via an injection of virus that specifically infects T cells and inserts the genes needed, was advanced by two biotech companies with preclinical results, one in non-human primates.
Gearing up to meet the challenge of solid tumor CAR-T intervention, there’s more work using CRISPR genome editing of T cell receptors. A.I. is increasingly being exploited to process the data from sequencing and identify optimal neoantigens.
Instead of just CAR-T, we’re seeing the emergence of CAR-macrophage and CAR-natural killer (NK) cells strategies, and rapidly expanding potential combinations of all the strategies I’ve mentioned. No less, there’s been maturation of on-off suicide switches programmed in, to limit cytokine release and promote safety of these interventions. Overall, major side effects of immunotherapies are not only cytokine release syndromes, but also include interstitial pneumonitis and neurotoxicity.
Summary
Given the multitude of ways cancer cells and tumor tissue can evade our immune response, durably successful treatment remains a daunting challenge. But the ingenuity of so many different approaches to unleash our immune response, and their combinations, provides considerable hope that we’ll increasingly meet the challenge in the years ahead. We have clearly learned that combining different immunotherapy strategies will be essential for many patients with the most resilient solid tumors.
Of concern, as noted by a recent editorial in The Lancet, entitled “Cancer Research Equity: Innovations For The Many, Not The Few,” is that these individualized, sophisticated strategies are not scalable; they will have limited reach and benefit. The movement towards “off the shelf” CAR-T and inexpensive, orally active checkpoint inhibitors may help mitigate this issue.
Notwithstanding this important concern, we’re seeing an array of diverse and potent immunotherapy strategies that are providing highly encouraging results, engendering more excitement than we’ve seen in this space for some time. These should propel substantial improvements in outcomes for patients in the years ahead. It can’t happen soon enough.
Thanks for reading this edition of Ground Truths. If you found it informative, please share it with your colleagues.
Dr. Topol has disclosed the following relevant financial relationships: Serve(d) as a director, officer, partner, employee, advisor, consultant, or trustee for Dexcom; Illumina; Molecular Stethoscope; Quest Diagnostics; Blue Cross Blue Shield Association. Received research grant from National Institutes of Health.
A version of this article appeared on Medscape.com.
This article was originally published on February 10 in Eric Topol’s substack “Ground Truths.”
It’s astounding how devious cancer cells and tumor tissue can be. This week in Science we learned how certain lung cancer cells can function like “Catch Me If You Can” — changing their driver mutation and cell identity to escape targeted therapy. This histologic transformation, as seen in an experimental model, is just one of so many cancer tricks that we are learning about.
Recently, as shown by single-cell sequencing, cancer cells can steal the mitochondria from T cells, a double whammy that turbocharges cancer cells with the hijacked fuel supply and, at the same time, dismantles the immune response.
Last week, we saw how tumor cells can release a virus-like protein that unleashes a vicious autoimmune response.
And then there’s the finding that cancer cell spread predominantly is occurring while we sleep.
As I previously reviewed, the ability for cancer cells to hijack neurons and neural circuits is now well established, no less their ability to reprogram neurons to become adrenergic and stimulate tumor progression, and interfere with the immune response. Stay tuned on that for a new Ground Truths podcast with Prof Michelle Monje, a leader in cancer neuroscience, which will post soon.
Add advancing age’s immunosenescence as yet another challenge to the long and growing list of formidable ways that cancer cells, and the tumor microenvironment, evade our immune response.
An Ever-Expanding Armamentarium
Immune Checkpoint Inhibitors
The field of immunotherapies took off with the immune checkpoint inhibitors, first approved by the FDA in 2011, that take the brakes off of T cells, with the programmed death-1 (PD-1), PD-ligand1, and anti-CTLA-4 monoclonal antibodies.
But we’re clearly learning they are not enough to prevail over cancer with common recurrences, only short term success in most patients, with some notable exceptions. Adding other immune response strategies, such as a vaccine, or antibody-drug conjugates, or engineered T cells, are showing improved chances for success.
Therapeutic Cancer Vaccines
There are many therapeutic cancer vaccines in the works, as reviewed in depth here.
Here’s a list of ongoing clinical trials of cancer vaccines. You’ll note most of these are on top of a checkpoint inhibitor and use personalized neoantigens (cancer cell surface proteins) derived from sequencing (whole-exome or whole genome, RNA-sequencing and HLA-profiling) the patient’s tumor.
An example of positive findings is with the combination of an mRNA-nanoparticle vaccine with up to 34 personalized neoantigens and pembrolizumab (Keytruda) vs pembrolizumab alone in advanced melanoma after resection, with improved outcomes at 3-year follow-up, cutting death or relapse rate in half.
Antibody-Drug Conjugates (ADC)
There is considerable excitement about antibody-drug conjugates (ADC) whereby a linker is used to attach a chemotherapy agent to the checkpoint inhibitor antibody, specifically targeting the cancer cell and facilitating entry of the chemotherapy into the cell. Akin to these are bispecific antibodies (BiTEs, binding to a tumor antigen and T cell receptor simultaneously), both of these conjugates acting as “biologic” or “guided” missiles.
A very good example of the potency of an ADC was seen in a “HER2-low” breast cancer randomized trial. The absence or very low expression or amplification of the HER2 receptor is common in breast cancer and successful treatment has been elusive. A randomized trial of an ADC (trastuzumab deruxtecan) compared to physician’s choice therapy demonstrated a marked success for progression-free survival in HER2-low patients, which was characterized as “unheard-of success” by media coverage.
This strategy is being used to target some of the most difficult cancer driver mutations such as TP53 and KRAS.
Oncolytic Viruses
Modifying viruses to infect the tumor and make it more visible to the immune system, potentiating anti-tumor responses, known as oncolytic viruses, have been proposed as a way to rev up the immune response for a long time but without positive Phase 3 clinical trials.
After decades of failure, a recent trial in refractory bladder cancer showed marked success, along with others, summarized here, now providing very encouraging results. It looks like oncolytic viruses are on a comeback path.
Engineering T Cells (Chimeric Antigen Receptor [CAR-T])
As I recently reviewed, there are over 500 ongoing clinical trials to build on the success of the first CAR-T approval for leukemia 7 years ago. I won’t go through that all again here, but to reiterate most of the success to date has been in “liquid” blood (leukemia and lymphoma) cancer tumors. This week in Nature is the discovery of a T cell cancer mutation, a gene fusion CARD11-PIK3R3, from a T cell lymphoma that can potentially be used to augment CAR-T efficacy. It has pronounced and prolonged effects in the experimental model. Instead of 1 million cells needed for treatment, even 20,000 were enough to melt the tumor. This is a noteworthy discovery since CAR-T work to date has largely not exploited such naturally occurring mutations, while instead concentrating on those seen in the patient’s set of key tumor mutations.
As currently conceived, CAR-T, and what is being referred to more broadly as adoptive cell therapies, involves removing T cells from the patient’s body and engineering their activation, then reintroducing them back to the patient. This is laborious, technically difficult, and very expensive. Recently, the idea of achieving all of this via an injection of virus that specifically infects T cells and inserts the genes needed, was advanced by two biotech companies with preclinical results, one in non-human primates.
Gearing up to meet the challenge of solid tumor CAR-T intervention, there’s more work using CRISPR genome editing of T cell receptors. A.I. is increasingly being exploited to process the data from sequencing and identify optimal neoantigens.
Instead of just CAR-T, we’re seeing the emergence of CAR-macrophage and CAR-natural killer (NK) cells strategies, and rapidly expanding potential combinations of all the strategies I’ve mentioned. No less, there’s been maturation of on-off suicide switches programmed in, to limit cytokine release and promote safety of these interventions. Overall, major side effects of immunotherapies are not only cytokine release syndromes, but also include interstitial pneumonitis and neurotoxicity.
Summary
Given the multitude of ways cancer cells and tumor tissue can evade our immune response, durably successful treatment remains a daunting challenge. But the ingenuity of so many different approaches to unleash our immune response, and their combinations, provides considerable hope that we’ll increasingly meet the challenge in the years ahead. We have clearly learned that combining different immunotherapy strategies will be essential for many patients with the most resilient solid tumors.
Of concern, as noted by a recent editorial in The Lancet, entitled “Cancer Research Equity: Innovations For The Many, Not The Few,” is that these individualized, sophisticated strategies are not scalable; they will have limited reach and benefit. The movement towards “off the shelf” CAR-T and inexpensive, orally active checkpoint inhibitors may help mitigate this issue.
Notwithstanding this important concern, we’re seeing an array of diverse and potent immunotherapy strategies that are providing highly encouraging results, engendering more excitement than we’ve seen in this space for some time. These should propel substantial improvements in outcomes for patients in the years ahead. It can’t happen soon enough.
Thanks for reading this edition of Ground Truths. If you found it informative, please share it with your colleagues.
Dr. Topol has disclosed the following relevant financial relationships: Serve(d) as a director, officer, partner, employee, advisor, consultant, or trustee for Dexcom; Illumina; Molecular Stethoscope; Quest Diagnostics; Blue Cross Blue Shield Association. Received research grant from National Institutes of Health.
A version of this article appeared on Medscape.com.
This article was originally published on February 10 in Eric Topol’s substack “Ground Truths.”
It’s astounding how devious cancer cells and tumor tissue can be. This week in Science we learned how certain lung cancer cells can function like “Catch Me If You Can” — changing their driver mutation and cell identity to escape targeted therapy. This histologic transformation, as seen in an experimental model, is just one of so many cancer tricks that we are learning about.
Recently, as shown by single-cell sequencing, cancer cells can steal the mitochondria from T cells, a double whammy that turbocharges cancer cells with the hijacked fuel supply and, at the same time, dismantles the immune response.
Last week, we saw how tumor cells can release a virus-like protein that unleashes a vicious autoimmune response.
And then there’s the finding that cancer cell spread predominantly is occurring while we sleep.
As I previously reviewed, the ability for cancer cells to hijack neurons and neural circuits is now well established, no less their ability to reprogram neurons to become adrenergic and stimulate tumor progression, and interfere with the immune response. Stay tuned on that for a new Ground Truths podcast with Prof Michelle Monje, a leader in cancer neuroscience, which will post soon.
Add advancing age’s immunosenescence as yet another challenge to the long and growing list of formidable ways that cancer cells, and the tumor microenvironment, evade our immune response.
An Ever-Expanding Armamentarium
Immune Checkpoint Inhibitors
The field of immunotherapies took off with the immune checkpoint inhibitors, first approved by the FDA in 2011, that take the brakes off of T cells, with the programmed death-1 (PD-1), PD-ligand1, and anti-CTLA-4 monoclonal antibodies.
But we’re clearly learning they are not enough to prevail over cancer with common recurrences, only short term success in most patients, with some notable exceptions. Adding other immune response strategies, such as a vaccine, or antibody-drug conjugates, or engineered T cells, are showing improved chances for success.
Therapeutic Cancer Vaccines
There are many therapeutic cancer vaccines in the works, as reviewed in depth here.
Here’s a list of ongoing clinical trials of cancer vaccines. You’ll note most of these are on top of a checkpoint inhibitor and use personalized neoantigens (cancer cell surface proteins) derived from sequencing (whole-exome or whole genome, RNA-sequencing and HLA-profiling) the patient’s tumor.
An example of positive findings is with the combination of an mRNA-nanoparticle vaccine with up to 34 personalized neoantigens and pembrolizumab (Keytruda) vs pembrolizumab alone in advanced melanoma after resection, with improved outcomes at 3-year follow-up, cutting death or relapse rate in half.
Antibody-Drug Conjugates (ADC)
There is considerable excitement about antibody-drug conjugates (ADC) whereby a linker is used to attach a chemotherapy agent to the checkpoint inhibitor antibody, specifically targeting the cancer cell and facilitating entry of the chemotherapy into the cell. Akin to these are bispecific antibodies (BiTEs, binding to a tumor antigen and T cell receptor simultaneously), both of these conjugates acting as “biologic” or “guided” missiles.
A very good example of the potency of an ADC was seen in a “HER2-low” breast cancer randomized trial. The absence or very low expression or amplification of the HER2 receptor is common in breast cancer and successful treatment has been elusive. A randomized trial of an ADC (trastuzumab deruxtecan) compared to physician’s choice therapy demonstrated a marked success for progression-free survival in HER2-low patients, which was characterized as “unheard-of success” by media coverage.
This strategy is being used to target some of the most difficult cancer driver mutations such as TP53 and KRAS.
Oncolytic Viruses
Modifying viruses to infect the tumor and make it more visible to the immune system, potentiating anti-tumor responses, known as oncolytic viruses, have been proposed as a way to rev up the immune response for a long time but without positive Phase 3 clinical trials.
After decades of failure, a recent trial in refractory bladder cancer showed marked success, along with others, summarized here, now providing very encouraging results. It looks like oncolytic viruses are on a comeback path.
Engineering T Cells (Chimeric Antigen Receptor [CAR-T])
As I recently reviewed, there are over 500 ongoing clinical trials to build on the success of the first CAR-T approval for leukemia 7 years ago. I won’t go through that all again here, but to reiterate most of the success to date has been in “liquid” blood (leukemia and lymphoma) cancer tumors. This week in Nature is the discovery of a T cell cancer mutation, a gene fusion CARD11-PIK3R3, from a T cell lymphoma that can potentially be used to augment CAR-T efficacy. It has pronounced and prolonged effects in the experimental model. Instead of 1 million cells needed for treatment, even 20,000 were enough to melt the tumor. This is a noteworthy discovery since CAR-T work to date has largely not exploited such naturally occurring mutations, while instead concentrating on those seen in the patient’s set of key tumor mutations.
As currently conceived, CAR-T, and what is being referred to more broadly as adoptive cell therapies, involves removing T cells from the patient’s body and engineering their activation, then reintroducing them back to the patient. This is laborious, technically difficult, and very expensive. Recently, the idea of achieving all of this via an injection of virus that specifically infects T cells and inserts the genes needed, was advanced by two biotech companies with preclinical results, one in non-human primates.
Gearing up to meet the challenge of solid tumor CAR-T intervention, there’s more work using CRISPR genome editing of T cell receptors. A.I. is increasingly being exploited to process the data from sequencing and identify optimal neoantigens.
Instead of just CAR-T, we’re seeing the emergence of CAR-macrophage and CAR-natural killer (NK) cells strategies, and rapidly expanding potential combinations of all the strategies I’ve mentioned. No less, there’s been maturation of on-off suicide switches programmed in, to limit cytokine release and promote safety of these interventions. Overall, major side effects of immunotherapies are not only cytokine release syndromes, but also include interstitial pneumonitis and neurotoxicity.
Summary
Given the multitude of ways cancer cells and tumor tissue can evade our immune response, durably successful treatment remains a daunting challenge. But the ingenuity of so many different approaches to unleash our immune response, and their combinations, provides considerable hope that we’ll increasingly meet the challenge in the years ahead. We have clearly learned that combining different immunotherapy strategies will be essential for many patients with the most resilient solid tumors.
Of concern, as noted by a recent editorial in The Lancet, entitled “Cancer Research Equity: Innovations For The Many, Not The Few,” is that these individualized, sophisticated strategies are not scalable; they will have limited reach and benefit. The movement towards “off the shelf” CAR-T and inexpensive, orally active checkpoint inhibitors may help mitigate this issue.
Notwithstanding this important concern, we’re seeing an array of diverse and potent immunotherapy strategies that are providing highly encouraging results, engendering more excitement than we’ve seen in this space for some time. These should propel substantial improvements in outcomes for patients in the years ahead. It can’t happen soon enough.
Thanks for reading this edition of Ground Truths. If you found it informative, please share it with your colleagues.
Dr. Topol has disclosed the following relevant financial relationships: Serve(d) as a director, officer, partner, employee, advisor, consultant, or trustee for Dexcom; Illumina; Molecular Stethoscope; Quest Diagnostics; Blue Cross Blue Shield Association. Received research grant from National Institutes of Health.
A version of this article appeared on Medscape.com.
Good Efficacy-Safety Profile of nab-Paclitaxel in Taxane-pretreated Metastatic Breast Cancer
Key clinical point: Nanoparticle albumin‐bound (nab) paclitaxel showed promising clinical activity and tolerable safety in patients with metastatic breast cancer (BC) who were previously treated with taxanes, regardless of their sensitivity or resistance to taxane therapy.
Major finding: The median progression-free survival (PFS) was 7.20 months (95% CI 6.63-7.80 months) for all patients. The median PFS was significantly longer (7.57 vs 4.43 months; P < .001) and the disease control rate was 88.24% vs 68.00% in patients who were taxane-sensitive vs taxane-resistant. Neutropenia (21.19%), leukopenia (19.49%), and sensory neuropathy (6.36%) were the most frequent grade 3-4 adverse events.
Study details: Findings are from a retrospective study including 236 taxane-pretreated women with metastatic BC, of whom 184 were sensitive and 52 were resistant to taxanes based on previous treatment and received nab-paclitaxel as monotherapy or combination therapy.
Disclosures: This study was supported by the Jiangsu Provincial Medical Youth Talent and the Talents Program of Jiangsu Cancer Hospital, China. The authors declared no conflicts of interest.
Source: Xiong W, Xu T, Liu X, Zhang L, Yuan Y. Efficacy and safety of nanoparticle albumin-bound paclitaxel in taxane-pretreated metastatic breast cancer patients. Cancer. 2024 (Jan 25). doi: 10.1002/cncr.35206 Source
Key clinical point: Nanoparticle albumin‐bound (nab) paclitaxel showed promising clinical activity and tolerable safety in patients with metastatic breast cancer (BC) who were previously treated with taxanes, regardless of their sensitivity or resistance to taxane therapy.
Major finding: The median progression-free survival (PFS) was 7.20 months (95% CI 6.63-7.80 months) for all patients. The median PFS was significantly longer (7.57 vs 4.43 months; P < .001) and the disease control rate was 88.24% vs 68.00% in patients who were taxane-sensitive vs taxane-resistant. Neutropenia (21.19%), leukopenia (19.49%), and sensory neuropathy (6.36%) were the most frequent grade 3-4 adverse events.
Study details: Findings are from a retrospective study including 236 taxane-pretreated women with metastatic BC, of whom 184 were sensitive and 52 were resistant to taxanes based on previous treatment and received nab-paclitaxel as monotherapy or combination therapy.
Disclosures: This study was supported by the Jiangsu Provincial Medical Youth Talent and the Talents Program of Jiangsu Cancer Hospital, China. The authors declared no conflicts of interest.
Source: Xiong W, Xu T, Liu X, Zhang L, Yuan Y. Efficacy and safety of nanoparticle albumin-bound paclitaxel in taxane-pretreated metastatic breast cancer patients. Cancer. 2024 (Jan 25). doi: 10.1002/cncr.35206 Source
Key clinical point: Nanoparticle albumin‐bound (nab) paclitaxel showed promising clinical activity and tolerable safety in patients with metastatic breast cancer (BC) who were previously treated with taxanes, regardless of their sensitivity or resistance to taxane therapy.
Major finding: The median progression-free survival (PFS) was 7.20 months (95% CI 6.63-7.80 months) for all patients. The median PFS was significantly longer (7.57 vs 4.43 months; P < .001) and the disease control rate was 88.24% vs 68.00% in patients who were taxane-sensitive vs taxane-resistant. Neutropenia (21.19%), leukopenia (19.49%), and sensory neuropathy (6.36%) were the most frequent grade 3-4 adverse events.
Study details: Findings are from a retrospective study including 236 taxane-pretreated women with metastatic BC, of whom 184 were sensitive and 52 were resistant to taxanes based on previous treatment and received nab-paclitaxel as monotherapy or combination therapy.
Disclosures: This study was supported by the Jiangsu Provincial Medical Youth Talent and the Talents Program of Jiangsu Cancer Hospital, China. The authors declared no conflicts of interest.
Source: Xiong W, Xu T, Liu X, Zhang L, Yuan Y. Efficacy and safety of nanoparticle albumin-bound paclitaxel in taxane-pretreated metastatic breast cancer patients. Cancer. 2024 (Jan 25). doi: 10.1002/cncr.35206 Source
Poziotinib Shows Promising Antitumor Activity in Heavily Pretreated HER2+ BC in Phase 2
Key clinical point: Poziotinib demonstrated promising antitumor activity but high toxicity in patients with human epidermal growth factor receptor 2-positive (HER2+) advanced breast cancer (BC) who were heavily pretreated with HER2-directed therapy.
Major finding: Intermittent and continuous dosing schedules of poziotinib led to objective response rates of 30% each (P = .98) and disease control rates of 60% and 78% (P = .15), respectively. Grades 3-4 treatment-related adverse events were reported by 67% and 76% of patients receiving intermittent and continuous dosing schedules of poziotinib, respectively.
Study details: This phase 2 trial included 67 patients with HER2+ advanced BC who were previously treated with two or more HER2-directed regimens and who received 24 mg poziotinib once daily on an intermittent dosing schedule (n = 33) or 16 mg poziotinib once daily on a continuous dosing schedule (n = 34).
Disclosures: This study received financial support from Spectrum Pharmaceuticals. Gajanan Bhat and Szu-Yun Leu declared being employees of Spectrum Pharmaceuticals. Adam Brufsky declared serving as a consultant for and receiving research support from various sources. The other authors did not declare any conflicts of interest.
Source: Nasrazadani A, Marti JLG, Lathrop K, et al. Poziotinib treatment in patients with HER2-positive advanced breast cancer who have received prior anti-HER2 regimens. Breast Cancer Res Treat. 2024 (Jan 23). doi: 10.1007/s10549-023-07236-z Source
Key clinical point: Poziotinib demonstrated promising antitumor activity but high toxicity in patients with human epidermal growth factor receptor 2-positive (HER2+) advanced breast cancer (BC) who were heavily pretreated with HER2-directed therapy.
Major finding: Intermittent and continuous dosing schedules of poziotinib led to objective response rates of 30% each (P = .98) and disease control rates of 60% and 78% (P = .15), respectively. Grades 3-4 treatment-related adverse events were reported by 67% and 76% of patients receiving intermittent and continuous dosing schedules of poziotinib, respectively.
Study details: This phase 2 trial included 67 patients with HER2+ advanced BC who were previously treated with two or more HER2-directed regimens and who received 24 mg poziotinib once daily on an intermittent dosing schedule (n = 33) or 16 mg poziotinib once daily on a continuous dosing schedule (n = 34).
Disclosures: This study received financial support from Spectrum Pharmaceuticals. Gajanan Bhat and Szu-Yun Leu declared being employees of Spectrum Pharmaceuticals. Adam Brufsky declared serving as a consultant for and receiving research support from various sources. The other authors did not declare any conflicts of interest.
Source: Nasrazadani A, Marti JLG, Lathrop K, et al. Poziotinib treatment in patients with HER2-positive advanced breast cancer who have received prior anti-HER2 regimens. Breast Cancer Res Treat. 2024 (Jan 23). doi: 10.1007/s10549-023-07236-z Source
Key clinical point: Poziotinib demonstrated promising antitumor activity but high toxicity in patients with human epidermal growth factor receptor 2-positive (HER2+) advanced breast cancer (BC) who were heavily pretreated with HER2-directed therapy.
Major finding: Intermittent and continuous dosing schedules of poziotinib led to objective response rates of 30% each (P = .98) and disease control rates of 60% and 78% (P = .15), respectively. Grades 3-4 treatment-related adverse events were reported by 67% and 76% of patients receiving intermittent and continuous dosing schedules of poziotinib, respectively.
Study details: This phase 2 trial included 67 patients with HER2+ advanced BC who were previously treated with two or more HER2-directed regimens and who received 24 mg poziotinib once daily on an intermittent dosing schedule (n = 33) or 16 mg poziotinib once daily on a continuous dosing schedule (n = 34).
Disclosures: This study received financial support from Spectrum Pharmaceuticals. Gajanan Bhat and Szu-Yun Leu declared being employees of Spectrum Pharmaceuticals. Adam Brufsky declared serving as a consultant for and receiving research support from various sources. The other authors did not declare any conflicts of interest.
Source: Nasrazadani A, Marti JLG, Lathrop K, et al. Poziotinib treatment in patients with HER2-positive advanced breast cancer who have received prior anti-HER2 regimens. Breast Cancer Res Treat. 2024 (Jan 23). doi: 10.1007/s10549-023-07236-z Source
Hypofractionated and Conventional Radiotherapy Similarly Effective, Safe in Postoperative BC
Key clinical point: Both hypofractionated (HF) and conventional fractionated (CF) radiotherapy were comparably effective in patients who had undergone surgery for breast cancer (BC); however, the HF vs CF regimen was more effective in reducing skin toxicity and relieving fatigue.
Major finding: CF vs HF radiotherapy demonstrated no significant improvement in terms of local recurrence (odds ratio [OR] 0.91; P = .30) or overall survival (OR 1.08; P = .28) outcomes. Although safety outcomes like breast pain, breast atrophy, lymphedema, pneumonia, pulmonary fibrosis, telangiectasia, and cardiotoxicity were comparable in both groups, HF vs CF regimen led to lower skin toxicity (OR 0.43; P < .01) and improved patient fatigue outcomes (OR 0.73; P < .01).
Study details: This meta-analysis of 35 studies included 18,246 patients diagnosed with BC who underwent surgery and were treated with HF or CF radiotherapy.
Disclosures: This study was supported by the Key Research and Development Projects of Shaanxi Province, China, and other sources. The authors declared no conflicts of interest.
Source: Lu Y, Hui B, Yang D, et al. Efficacy and safety analysis of hypofractionated and conventional fractionated radiotherapy in postoperative breast cancer patients. BMC Cancer. 2024;24:181. doi: 10.1186/s12885-024-11918-2 Source
Key clinical point: Both hypofractionated (HF) and conventional fractionated (CF) radiotherapy were comparably effective in patients who had undergone surgery for breast cancer (BC); however, the HF vs CF regimen was more effective in reducing skin toxicity and relieving fatigue.
Major finding: CF vs HF radiotherapy demonstrated no significant improvement in terms of local recurrence (odds ratio [OR] 0.91; P = .30) or overall survival (OR 1.08; P = .28) outcomes. Although safety outcomes like breast pain, breast atrophy, lymphedema, pneumonia, pulmonary fibrosis, telangiectasia, and cardiotoxicity were comparable in both groups, HF vs CF regimen led to lower skin toxicity (OR 0.43; P < .01) and improved patient fatigue outcomes (OR 0.73; P < .01).
Study details: This meta-analysis of 35 studies included 18,246 patients diagnosed with BC who underwent surgery and were treated with HF or CF radiotherapy.
Disclosures: This study was supported by the Key Research and Development Projects of Shaanxi Province, China, and other sources. The authors declared no conflicts of interest.
Source: Lu Y, Hui B, Yang D, et al. Efficacy and safety analysis of hypofractionated and conventional fractionated radiotherapy in postoperative breast cancer patients. BMC Cancer. 2024;24:181. doi: 10.1186/s12885-024-11918-2 Source
Key clinical point: Both hypofractionated (HF) and conventional fractionated (CF) radiotherapy were comparably effective in patients who had undergone surgery for breast cancer (BC); however, the HF vs CF regimen was more effective in reducing skin toxicity and relieving fatigue.
Major finding: CF vs HF radiotherapy demonstrated no significant improvement in terms of local recurrence (odds ratio [OR] 0.91; P = .30) or overall survival (OR 1.08; P = .28) outcomes. Although safety outcomes like breast pain, breast atrophy, lymphedema, pneumonia, pulmonary fibrosis, telangiectasia, and cardiotoxicity were comparable in both groups, HF vs CF regimen led to lower skin toxicity (OR 0.43; P < .01) and improved patient fatigue outcomes (OR 0.73; P < .01).
Study details: This meta-analysis of 35 studies included 18,246 patients diagnosed with BC who underwent surgery and were treated with HF or CF radiotherapy.
Disclosures: This study was supported by the Key Research and Development Projects of Shaanxi Province, China, and other sources. The authors declared no conflicts of interest.
Source: Lu Y, Hui B, Yang D, et al. Efficacy and safety analysis of hypofractionated and conventional fractionated radiotherapy in postoperative breast cancer patients. BMC Cancer. 2024;24:181. doi: 10.1186/s12885-024-11918-2 Source
Chemotherapy Improves Survival Outcomes in Metaplastic Breast Cancer
Key clinical point: Compared with patients having metaplastic breast cancer (MpBC) who did not receive any chemotherapy, prognostic outcomes were significantly improved in those who received neoadjuvant chemotherapy (NAC) or adjuvant chemotherapy.
Major finding: Compared with patients who did not receive any chemotherapy, the overall survival (OS) improved significantly in those who received adjuvant chemotherapy (hazard ratio [HR] 0.451; P < .001) or responded to NAC (HR 0.479; P < .001). Breast cancer-specific survival also improved in patients who received and responded to NAC or received adjuvant chemotherapy.
Study details: This study analyzed data from the Surveillance, Epidemiology, and End Results (SEER) database and included 1186 patients with MpBC who received NAC (n = 181), adjuvant chemotherapy (n = 647), or did not receive any chemotherapy (n = 358).
Disclosures: This study was supported by the Science and Technology Innovation Plan of Shanghai Science and Technology Commission and the Obstetrics and Gynecology Hospital of Fudan University. The authors declared no conflicts of interest.
Source: Zhang M, Yuan J, Wang M, Zhang M, Chen H. Chemotherapy is of prognostic significance to metaplastic breast cancer. Sci Rep. 2024;14:1210. doi: 10.1038/s41598-024-51627-1 Source
Key clinical point: Compared with patients having metaplastic breast cancer (MpBC) who did not receive any chemotherapy, prognostic outcomes were significantly improved in those who received neoadjuvant chemotherapy (NAC) or adjuvant chemotherapy.
Major finding: Compared with patients who did not receive any chemotherapy, the overall survival (OS) improved significantly in those who received adjuvant chemotherapy (hazard ratio [HR] 0.451; P < .001) or responded to NAC (HR 0.479; P < .001). Breast cancer-specific survival also improved in patients who received and responded to NAC or received adjuvant chemotherapy.
Study details: This study analyzed data from the Surveillance, Epidemiology, and End Results (SEER) database and included 1186 patients with MpBC who received NAC (n = 181), adjuvant chemotherapy (n = 647), or did not receive any chemotherapy (n = 358).
Disclosures: This study was supported by the Science and Technology Innovation Plan of Shanghai Science and Technology Commission and the Obstetrics and Gynecology Hospital of Fudan University. The authors declared no conflicts of interest.
Source: Zhang M, Yuan J, Wang M, Zhang M, Chen H. Chemotherapy is of prognostic significance to metaplastic breast cancer. Sci Rep. 2024;14:1210. doi: 10.1038/s41598-024-51627-1 Source
Key clinical point: Compared with patients having metaplastic breast cancer (MpBC) who did not receive any chemotherapy, prognostic outcomes were significantly improved in those who received neoadjuvant chemotherapy (NAC) or adjuvant chemotherapy.
Major finding: Compared with patients who did not receive any chemotherapy, the overall survival (OS) improved significantly in those who received adjuvant chemotherapy (hazard ratio [HR] 0.451; P < .001) or responded to NAC (HR 0.479; P < .001). Breast cancer-specific survival also improved in patients who received and responded to NAC or received adjuvant chemotherapy.
Study details: This study analyzed data from the Surveillance, Epidemiology, and End Results (SEER) database and included 1186 patients with MpBC who received NAC (n = 181), adjuvant chemotherapy (n = 647), or did not receive any chemotherapy (n = 358).
Disclosures: This study was supported by the Science and Technology Innovation Plan of Shanghai Science and Technology Commission and the Obstetrics and Gynecology Hospital of Fudan University. The authors declared no conflicts of interest.
Source: Zhang M, Yuan J, Wang M, Zhang M, Chen H. Chemotherapy is of prognostic significance to metaplastic breast cancer. Sci Rep. 2024;14:1210. doi: 10.1038/s41598-024-51627-1 Source
Delaying Adjuvant Chemotherapy Beyond 4-6 Weeks Worsens Prognosis in Early TNBC
Key clinical point: Patients with early-stage triple-negative breast cancer (TNBC) should receive adjuvant chemotherapy without unnecessary delays after primary surgery because prognosis may worsen if treatment is postponed beyond 6 weeks.
Major finding: Patients who received adjuvant systemic therapy within 22-28 days after surgery reported the most favorable overall survival (OS) outcomes (median OS 10.2 years), with the OS decreasing in the groups that received adjuvant systemic therapy during 29-35 days, 36-42 days, and >6 weeks after surgery (8.3 years, 7.8 years, and 6.9 years, respectively).
Study details: Findings are from a retrospective cohort study that included 245 patients with early TNBC who received adjuvant chemotherapy after primary surgery.
Disclosures: The open access funding for this study was enabled and organized by Projekt DEAL. Some authors declared receiving honoraria or travel reimbursements from or serving as consultants or board members for various sources.
Source: Hatzipanagiotou ME, Pigerl M, Gerken M, et al. Clinical impact of delaying initiation of adjuvant chemotherapy in patients with early triple negative breast cancer. Breast Cancer Res Treat. 2024 (Jan 19). doi: 10.1007/s10549-023-07207-4 Source
Key clinical point: Patients with early-stage triple-negative breast cancer (TNBC) should receive adjuvant chemotherapy without unnecessary delays after primary surgery because prognosis may worsen if treatment is postponed beyond 6 weeks.
Major finding: Patients who received adjuvant systemic therapy within 22-28 days after surgery reported the most favorable overall survival (OS) outcomes (median OS 10.2 years), with the OS decreasing in the groups that received adjuvant systemic therapy during 29-35 days, 36-42 days, and >6 weeks after surgery (8.3 years, 7.8 years, and 6.9 years, respectively).
Study details: Findings are from a retrospective cohort study that included 245 patients with early TNBC who received adjuvant chemotherapy after primary surgery.
Disclosures: The open access funding for this study was enabled and organized by Projekt DEAL. Some authors declared receiving honoraria or travel reimbursements from or serving as consultants or board members for various sources.
Source: Hatzipanagiotou ME, Pigerl M, Gerken M, et al. Clinical impact of delaying initiation of adjuvant chemotherapy in patients with early triple negative breast cancer. Breast Cancer Res Treat. 2024 (Jan 19). doi: 10.1007/s10549-023-07207-4 Source
Key clinical point: Patients with early-stage triple-negative breast cancer (TNBC) should receive adjuvant chemotherapy without unnecessary delays after primary surgery because prognosis may worsen if treatment is postponed beyond 6 weeks.
Major finding: Patients who received adjuvant systemic therapy within 22-28 days after surgery reported the most favorable overall survival (OS) outcomes (median OS 10.2 years), with the OS decreasing in the groups that received adjuvant systemic therapy during 29-35 days, 36-42 days, and >6 weeks after surgery (8.3 years, 7.8 years, and 6.9 years, respectively).
Study details: Findings are from a retrospective cohort study that included 245 patients with early TNBC who received adjuvant chemotherapy after primary surgery.
Disclosures: The open access funding for this study was enabled and organized by Projekt DEAL. Some authors declared receiving honoraria or travel reimbursements from or serving as consultants or board members for various sources.
Source: Hatzipanagiotou ME, Pigerl M, Gerken M, et al. Clinical impact of delaying initiation of adjuvant chemotherapy in patients with early triple negative breast cancer. Breast Cancer Res Treat. 2024 (Jan 19). doi: 10.1007/s10549-023-07207-4 Source
Veliparib Fails to Show OS Benefits in Advanced BRCA1/2-mutated HER2− BC
Key clinical point: Addition of veliparib vs placebo to carboplatin + paclitaxel did not significantly improve the overall survival (OS) outcomes in patients with BRCA1/2-mutated human epidermal growth factor receptor 2-negative (HER2−) advanced breast cancer (BC).
Major finding: A combination of veliparib and carboplatin + paclitaxel vs placebo + carboplatin + paclitaxel led to numerical but nonsignificant improvements in median OS (32.4 vs 28.2 months; hazard ratio 0.916; P = .434). The addition of veliparib was generally well-tolerated, consistent with previous findings.
Study details: Findings are from the phase 3 BROCADE3 trial which included 509 patients with BRCA1/2-mutated HER2− advanced BC who had received at least two prior lines of chemotherapy and were randomly assigned to receive carboplatin + paclitaxel with either veliparib or placebo.
Disclosures: This study was funded by AbbVie. No other disclosures were reported in this study.
Source: Diéras V, Han HS, Wildiers H, et al. Veliparib with carboplatin and paclitaxel in BRCA-mutated advanced breast cancer (BROCADE3): Final overall survival results from a randomized phase 3 trial. Eur J Cancer. 2024;200:113580. doi: 10.1016/j.ejca.2024.113580 Source
Key clinical point: Addition of veliparib vs placebo to carboplatin + paclitaxel did not significantly improve the overall survival (OS) outcomes in patients with BRCA1/2-mutated human epidermal growth factor receptor 2-negative (HER2−) advanced breast cancer (BC).
Major finding: A combination of veliparib and carboplatin + paclitaxel vs placebo + carboplatin + paclitaxel led to numerical but nonsignificant improvements in median OS (32.4 vs 28.2 months; hazard ratio 0.916; P = .434). The addition of veliparib was generally well-tolerated, consistent with previous findings.
Study details: Findings are from the phase 3 BROCADE3 trial which included 509 patients with BRCA1/2-mutated HER2− advanced BC who had received at least two prior lines of chemotherapy and were randomly assigned to receive carboplatin + paclitaxel with either veliparib or placebo.
Disclosures: This study was funded by AbbVie. No other disclosures were reported in this study.
Source: Diéras V, Han HS, Wildiers H, et al. Veliparib with carboplatin and paclitaxel in BRCA-mutated advanced breast cancer (BROCADE3): Final overall survival results from a randomized phase 3 trial. Eur J Cancer. 2024;200:113580. doi: 10.1016/j.ejca.2024.113580 Source
Key clinical point: Addition of veliparib vs placebo to carboplatin + paclitaxel did not significantly improve the overall survival (OS) outcomes in patients with BRCA1/2-mutated human epidermal growth factor receptor 2-negative (HER2−) advanced breast cancer (BC).
Major finding: A combination of veliparib and carboplatin + paclitaxel vs placebo + carboplatin + paclitaxel led to numerical but nonsignificant improvements in median OS (32.4 vs 28.2 months; hazard ratio 0.916; P = .434). The addition of veliparib was generally well-tolerated, consistent with previous findings.
Study details: Findings are from the phase 3 BROCADE3 trial which included 509 patients with BRCA1/2-mutated HER2− advanced BC who had received at least two prior lines of chemotherapy and were randomly assigned to receive carboplatin + paclitaxel with either veliparib or placebo.
Disclosures: This study was funded by AbbVie. No other disclosures were reported in this study.
Source: Diéras V, Han HS, Wildiers H, et al. Veliparib with carboplatin and paclitaxel in BRCA-mutated advanced breast cancer (BROCADE3): Final overall survival results from a randomized phase 3 trial. Eur J Cancer. 2024;200:113580. doi: 10.1016/j.ejca.2024.113580 Source
Toripalimab Bests Chemo in PD-L1 Positive TNBC in Phase 3
Key clinical point: Treatment with toripalimab + nab-paclitaxel vs placebo + nab-paclitaxel significantly improved progression-free survival (PFS) and showed an acceptable safety profile in patients with programmed death ligand-1 (PD-L1)-positive metastatic or recurrent triple-negative breast cancer (TNBC).
Major finding: Toripalimab + nab-paclitaxel vs placebo + nab-paclitaxel led to a significantly longer PFS (median 8.4 vs 5.6 months) in patients with PD-L1-positive TNBC (hazard ratio 0.65; P = .0102) and similar incidences of grade ≥3 treatment-emergent adverse events (56.4% vs 54.3%) and fatal adverse events (0.6% vs 3.4%).
Study details: Findings are from the phase 3 TORCHLIGHT trial which included 531 patients with metastatic or recurrent locally advanced TNBC who were previously untreated or treated with up to one systemic chemotherapy and were randomly assigned to receive toripalimab + nab-paclitaxel or placebo + nab-paclitaxel. Of these, 300 patients had PD-L1-positive TNBC.
Disclosures: This study was sponsored by Shanghai Junshi Biosciences and supported by other sources. Five authors declared being employees of Shanghai Junshi Biosciences or TopAlliance Biosciences. The other authors declared no competing interests.
Source: Jiang Z, Ouyang Q, Sun T, et al. Toripalimab plus nab-paclitaxel in metastatic or recurrent triple-negative breast cancer: A randomized phase 3 trial. Nat Med. 2024;30:249-256. doi: 10.1038/s41591-023-02677-x Source
Key clinical point: Treatment with toripalimab + nab-paclitaxel vs placebo + nab-paclitaxel significantly improved progression-free survival (PFS) and showed an acceptable safety profile in patients with programmed death ligand-1 (PD-L1)-positive metastatic or recurrent triple-negative breast cancer (TNBC).
Major finding: Toripalimab + nab-paclitaxel vs placebo + nab-paclitaxel led to a significantly longer PFS (median 8.4 vs 5.6 months) in patients with PD-L1-positive TNBC (hazard ratio 0.65; P = .0102) and similar incidences of grade ≥3 treatment-emergent adverse events (56.4% vs 54.3%) and fatal adverse events (0.6% vs 3.4%).
Study details: Findings are from the phase 3 TORCHLIGHT trial which included 531 patients with metastatic or recurrent locally advanced TNBC who were previously untreated or treated with up to one systemic chemotherapy and were randomly assigned to receive toripalimab + nab-paclitaxel or placebo + nab-paclitaxel. Of these, 300 patients had PD-L1-positive TNBC.
Disclosures: This study was sponsored by Shanghai Junshi Biosciences and supported by other sources. Five authors declared being employees of Shanghai Junshi Biosciences or TopAlliance Biosciences. The other authors declared no competing interests.
Source: Jiang Z, Ouyang Q, Sun T, et al. Toripalimab plus nab-paclitaxel in metastatic or recurrent triple-negative breast cancer: A randomized phase 3 trial. Nat Med. 2024;30:249-256. doi: 10.1038/s41591-023-02677-x Source
Key clinical point: Treatment with toripalimab + nab-paclitaxel vs placebo + nab-paclitaxel significantly improved progression-free survival (PFS) and showed an acceptable safety profile in patients with programmed death ligand-1 (PD-L1)-positive metastatic or recurrent triple-negative breast cancer (TNBC).
Major finding: Toripalimab + nab-paclitaxel vs placebo + nab-paclitaxel led to a significantly longer PFS (median 8.4 vs 5.6 months) in patients with PD-L1-positive TNBC (hazard ratio 0.65; P = .0102) and similar incidences of grade ≥3 treatment-emergent adverse events (56.4% vs 54.3%) and fatal adverse events (0.6% vs 3.4%).
Study details: Findings are from the phase 3 TORCHLIGHT trial which included 531 patients with metastatic or recurrent locally advanced TNBC who were previously untreated or treated with up to one systemic chemotherapy and were randomly assigned to receive toripalimab + nab-paclitaxel or placebo + nab-paclitaxel. Of these, 300 patients had PD-L1-positive TNBC.
Disclosures: This study was sponsored by Shanghai Junshi Biosciences and supported by other sources. Five authors declared being employees of Shanghai Junshi Biosciences or TopAlliance Biosciences. The other authors declared no competing interests.
Source: Jiang Z, Ouyang Q, Sun T, et al. Toripalimab plus nab-paclitaxel in metastatic or recurrent triple-negative breast cancer: A randomized phase 3 trial. Nat Med. 2024;30:249-256. doi: 10.1038/s41591-023-02677-x Source