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Deciding which cancer patients need immediate treatment and who can safely wait is an uncomfortable assessment for cancer clinicians during the COVID-19 pandemic.
In early April, as the COVID-19 surge was bearing down on New York City, those treatment decisions were “a juggling act every single day,” Jonathan Yang, MD, PhD, a radiation oncologist from New York’s Memorial Sloan Kettering Cancer Center, told Medscape Medical News.
Eventually, a glut of guidelines, recommendations, and expert opinions aimed at helping oncologists emerged. The tools help navigate the complicated risk-benefit analysis of their patient’s risk of infection by SARS-CoV-2 and delaying therapy.
Now, a new tool, which appears to be the first of its kind, quantifies that risk-benefit analysis. But its presence immediately raises the question: can it help?
Three-Tier Systems Are Not Very Sophisticated
OncCOVID, a free tool that was launched May 26 by the University of Michigan, allows physicians to individualize risk estimates for delaying treatment of up to 25 early- to late-stage cancers. It includes more than 45 patient characteristics, such as age, location, cancer type, cancer stage, treatment plan, underlying medical conditions, and proposed length of delay in care.
Combining these personal details with data from the National Cancer Institute’s SEER (Surveillance, Epidemiology, and End Results) registry and the National Cancer Database, the Michigan app then estimates a patient’s 5- or 10-year survival with immediate vs delayed treatment and weighs that against their risk for COVID-19 using data from the Johns Hopkins Coronavirus Resource Center.
“We thought, isn’t it better to at least provide some evidence-based quantification, rather than a back-of-the-envelope three-tier system that is just sort of ‘made up’?“ explained one of the developers, Daniel Spratt, MD, associate professor of radiation oncology at Michigan Medicine.
Spratt explained that almost every organization, professional society, and government has created something like a three-tier system. Tier 1 represents urgent cases and patients who need immediate treatment. For tier 2, treatment can be delayed weeks or a month, and with tier 3, it can be delayed until the pandemic is over or it’s deemed safe.
“[This system] sounds good at first glance, but in cancer, we’re always talking about personalized medicine, and it’s mind-blowing that these tier systems are only based on urgency and prognosis,” he told Medscape Medical News.
Spratt offered an example. Consider a patient with a very aggressive brain tumor ― that patient is in tier 1 and should undergo treatment immediately. But will the treatment actually help? And how helpful would the procedure be if, say, the patient is 80 years old and, if infected, would have a 30% to 50% chance of dying from the coronavirus?
“If the model says this guy has a 5% harm and this one has 30% harm, you can use that to help prioritize,” summarized Spratt.
The app can generate risk estimates for patients living anywhere in the world and has already been accessed by people from 37 countries. However, Spratt cautions that it is primarily “designed and calibrated for the US.
“The estimates are based on very large US registries, and though it’s probably somewhat similar across much of the world, there’s probably certain cancer types that are more region specific ― especially something like stomach cancer or certain types of head and neck cancer in parts of Asia, for example,” he said.
Although the app’s COVID-19 data are specific to the county level in the United States, elsewhere in the world, it is only country specific.
“We’re using the best data we have for coronavirus, but everyone knows we still have large data gaps,” he acknowledged.
How Accurate?
Asked to comment on the app, Richard Bleicher, MD, leader of the Breast Cancer Program at Fox Chase Cancer Center, Philadelphia, praised the effort and the goal but had some concerns.
“Several questions arise, most important of which is, How accurate is this, and how has this been validated, if at all ― especially as it is too soon to see the outcomes of patients affected in this pandemic?” he told Medscape Medical News.
“We are imposing delays on a broad scale because of the coronavirus, and we are getting continuously changing data as we test more patients. But both situations are novel and may not be accurately represented by the data being pulled, because the datasets use patients from a few years ago, and confounders in these datasets may not apply to this situation,” Bleicher continued.
Although acknowledging the “value in delineating the risk of dying from cancer vs the risk of dying from the SARS-CoV-2 pandemic,” Bleicher urged caution in using the tool to make individual patient decisions.
“We need to remember that the best of modeling ... can be wildly inaccurate and needs to be validated using patients having the circumstances in question. ... This won’t be possible until long after the pandemic is completed, and so the model’s accuracy remains unknown.”
That sentiment was echoed by Giampaolo Bianchini, MD, head of the Breast Cancer Group, Department of Medical Oncology, Ospedale San Raffaele, in Milan, Italy.
“Arbitrarily postponing and modifying treatment strategies including surgery, radiation therapy, and medical therapy without properly balancing the risk/benefit ratio may lead to significantly worse cancer-related outcomes, which largely exceed the actual risks for COVID,” he wrote in an email.
“The OncCOVID app is a remarkable attempt to fill the gap between perception and estimation,” he said. The app provides side by side the COVID-19 risk estimation and the consequences of arbitrary deviation from the standard of care, observed Bianchini.
However, he pointed out weaknesses, including the fact that the “data generated in literature are not always of high quality and do not take into consideration relevant characteristics of the disease and treatment benefit. It should for sure be used, but then also interpreted with caution.”
Another Italian group responded more positively.
“In our opinion, it could be a useful tool for clinicians,” wrote colleagues Alessio Cortelinni and Giampiero Porzio, both medical oncologists at San Salvatore Hospital and the University of L’Aquila, in Italy. “This Web app might assist clinicians in balancing the risk/benefit ratio of being treated and/or access to the outpatient cancer center for each kind of patient (both early and advanced stages), in order to make a more tailored counseling,” they wrote in an email. “Importantly, the Web app might help those clinicians who work ‘alone,’ in peripheral centers, without resources, colleagues, and multidisciplinary tumor boards on whom they can rely.”
Bleicher, who was involved in the COVID-19 Breast Cancer Consortium’s recommendations for prioritizing breast cancer treatment, summarized that the app “may end up being close or accurate, but we won’t know except in hindsight.”
This article first appeared on Medscape.com.
Deciding which cancer patients need immediate treatment and who can safely wait is an uncomfortable assessment for cancer clinicians during the COVID-19 pandemic.
In early April, as the COVID-19 surge was bearing down on New York City, those treatment decisions were “a juggling act every single day,” Jonathan Yang, MD, PhD, a radiation oncologist from New York’s Memorial Sloan Kettering Cancer Center, told Medscape Medical News.
Eventually, a glut of guidelines, recommendations, and expert opinions aimed at helping oncologists emerged. The tools help navigate the complicated risk-benefit analysis of their patient’s risk of infection by SARS-CoV-2 and delaying therapy.
Now, a new tool, which appears to be the first of its kind, quantifies that risk-benefit analysis. But its presence immediately raises the question: can it help?
Three-Tier Systems Are Not Very Sophisticated
OncCOVID, a free tool that was launched May 26 by the University of Michigan, allows physicians to individualize risk estimates for delaying treatment of up to 25 early- to late-stage cancers. It includes more than 45 patient characteristics, such as age, location, cancer type, cancer stage, treatment plan, underlying medical conditions, and proposed length of delay in care.
Combining these personal details with data from the National Cancer Institute’s SEER (Surveillance, Epidemiology, and End Results) registry and the National Cancer Database, the Michigan app then estimates a patient’s 5- or 10-year survival with immediate vs delayed treatment and weighs that against their risk for COVID-19 using data from the Johns Hopkins Coronavirus Resource Center.
“We thought, isn’t it better to at least provide some evidence-based quantification, rather than a back-of-the-envelope three-tier system that is just sort of ‘made up’?“ explained one of the developers, Daniel Spratt, MD, associate professor of radiation oncology at Michigan Medicine.
Spratt explained that almost every organization, professional society, and government has created something like a three-tier system. Tier 1 represents urgent cases and patients who need immediate treatment. For tier 2, treatment can be delayed weeks or a month, and with tier 3, it can be delayed until the pandemic is over or it’s deemed safe.
“[This system] sounds good at first glance, but in cancer, we’re always talking about personalized medicine, and it’s mind-blowing that these tier systems are only based on urgency and prognosis,” he told Medscape Medical News.
Spratt offered an example. Consider a patient with a very aggressive brain tumor ― that patient is in tier 1 and should undergo treatment immediately. But will the treatment actually help? And how helpful would the procedure be if, say, the patient is 80 years old and, if infected, would have a 30% to 50% chance of dying from the coronavirus?
“If the model says this guy has a 5% harm and this one has 30% harm, you can use that to help prioritize,” summarized Spratt.
The app can generate risk estimates for patients living anywhere in the world and has already been accessed by people from 37 countries. However, Spratt cautions that it is primarily “designed and calibrated for the US.
“The estimates are based on very large US registries, and though it’s probably somewhat similar across much of the world, there’s probably certain cancer types that are more region specific ― especially something like stomach cancer or certain types of head and neck cancer in parts of Asia, for example,” he said.
Although the app’s COVID-19 data are specific to the county level in the United States, elsewhere in the world, it is only country specific.
“We’re using the best data we have for coronavirus, but everyone knows we still have large data gaps,” he acknowledged.
How Accurate?
Asked to comment on the app, Richard Bleicher, MD, leader of the Breast Cancer Program at Fox Chase Cancer Center, Philadelphia, praised the effort and the goal but had some concerns.
“Several questions arise, most important of which is, How accurate is this, and how has this been validated, if at all ― especially as it is too soon to see the outcomes of patients affected in this pandemic?” he told Medscape Medical News.
“We are imposing delays on a broad scale because of the coronavirus, and we are getting continuously changing data as we test more patients. But both situations are novel and may not be accurately represented by the data being pulled, because the datasets use patients from a few years ago, and confounders in these datasets may not apply to this situation,” Bleicher continued.
Although acknowledging the “value in delineating the risk of dying from cancer vs the risk of dying from the SARS-CoV-2 pandemic,” Bleicher urged caution in using the tool to make individual patient decisions.
“We need to remember that the best of modeling ... can be wildly inaccurate and needs to be validated using patients having the circumstances in question. ... This won’t be possible until long after the pandemic is completed, and so the model’s accuracy remains unknown.”
That sentiment was echoed by Giampaolo Bianchini, MD, head of the Breast Cancer Group, Department of Medical Oncology, Ospedale San Raffaele, in Milan, Italy.
“Arbitrarily postponing and modifying treatment strategies including surgery, radiation therapy, and medical therapy without properly balancing the risk/benefit ratio may lead to significantly worse cancer-related outcomes, which largely exceed the actual risks for COVID,” he wrote in an email.
“The OncCOVID app is a remarkable attempt to fill the gap between perception and estimation,” he said. The app provides side by side the COVID-19 risk estimation and the consequences of arbitrary deviation from the standard of care, observed Bianchini.
However, he pointed out weaknesses, including the fact that the “data generated in literature are not always of high quality and do not take into consideration relevant characteristics of the disease and treatment benefit. It should for sure be used, but then also interpreted with caution.”
Another Italian group responded more positively.
“In our opinion, it could be a useful tool for clinicians,” wrote colleagues Alessio Cortelinni and Giampiero Porzio, both medical oncologists at San Salvatore Hospital and the University of L’Aquila, in Italy. “This Web app might assist clinicians in balancing the risk/benefit ratio of being treated and/or access to the outpatient cancer center for each kind of patient (both early and advanced stages), in order to make a more tailored counseling,” they wrote in an email. “Importantly, the Web app might help those clinicians who work ‘alone,’ in peripheral centers, without resources, colleagues, and multidisciplinary tumor boards on whom they can rely.”
Bleicher, who was involved in the COVID-19 Breast Cancer Consortium’s recommendations for prioritizing breast cancer treatment, summarized that the app “may end up being close or accurate, but we won’t know except in hindsight.”
This article first appeared on Medscape.com.
Deciding which cancer patients need immediate treatment and who can safely wait is an uncomfortable assessment for cancer clinicians during the COVID-19 pandemic.
In early April, as the COVID-19 surge was bearing down on New York City, those treatment decisions were “a juggling act every single day,” Jonathan Yang, MD, PhD, a radiation oncologist from New York’s Memorial Sloan Kettering Cancer Center, told Medscape Medical News.
Eventually, a glut of guidelines, recommendations, and expert opinions aimed at helping oncologists emerged. The tools help navigate the complicated risk-benefit analysis of their patient’s risk of infection by SARS-CoV-2 and delaying therapy.
Now, a new tool, which appears to be the first of its kind, quantifies that risk-benefit analysis. But its presence immediately raises the question: can it help?
Three-Tier Systems Are Not Very Sophisticated
OncCOVID, a free tool that was launched May 26 by the University of Michigan, allows physicians to individualize risk estimates for delaying treatment of up to 25 early- to late-stage cancers. It includes more than 45 patient characteristics, such as age, location, cancer type, cancer stage, treatment plan, underlying medical conditions, and proposed length of delay in care.
Combining these personal details with data from the National Cancer Institute’s SEER (Surveillance, Epidemiology, and End Results) registry and the National Cancer Database, the Michigan app then estimates a patient’s 5- or 10-year survival with immediate vs delayed treatment and weighs that against their risk for COVID-19 using data from the Johns Hopkins Coronavirus Resource Center.
“We thought, isn’t it better to at least provide some evidence-based quantification, rather than a back-of-the-envelope three-tier system that is just sort of ‘made up’?“ explained one of the developers, Daniel Spratt, MD, associate professor of radiation oncology at Michigan Medicine.
Spratt explained that almost every organization, professional society, and government has created something like a three-tier system. Tier 1 represents urgent cases and patients who need immediate treatment. For tier 2, treatment can be delayed weeks or a month, and with tier 3, it can be delayed until the pandemic is over or it’s deemed safe.
“[This system] sounds good at first glance, but in cancer, we’re always talking about personalized medicine, and it’s mind-blowing that these tier systems are only based on urgency and prognosis,” he told Medscape Medical News.
Spratt offered an example. Consider a patient with a very aggressive brain tumor ― that patient is in tier 1 and should undergo treatment immediately. But will the treatment actually help? And how helpful would the procedure be if, say, the patient is 80 years old and, if infected, would have a 30% to 50% chance of dying from the coronavirus?
“If the model says this guy has a 5% harm and this one has 30% harm, you can use that to help prioritize,” summarized Spratt.
The app can generate risk estimates for patients living anywhere in the world and has already been accessed by people from 37 countries. However, Spratt cautions that it is primarily “designed and calibrated for the US.
“The estimates are based on very large US registries, and though it’s probably somewhat similar across much of the world, there’s probably certain cancer types that are more region specific ― especially something like stomach cancer or certain types of head and neck cancer in parts of Asia, for example,” he said.
Although the app’s COVID-19 data are specific to the county level in the United States, elsewhere in the world, it is only country specific.
“We’re using the best data we have for coronavirus, but everyone knows we still have large data gaps,” he acknowledged.
How Accurate?
Asked to comment on the app, Richard Bleicher, MD, leader of the Breast Cancer Program at Fox Chase Cancer Center, Philadelphia, praised the effort and the goal but had some concerns.
“Several questions arise, most important of which is, How accurate is this, and how has this been validated, if at all ― especially as it is too soon to see the outcomes of patients affected in this pandemic?” he told Medscape Medical News.
“We are imposing delays on a broad scale because of the coronavirus, and we are getting continuously changing data as we test more patients. But both situations are novel and may not be accurately represented by the data being pulled, because the datasets use patients from a few years ago, and confounders in these datasets may not apply to this situation,” Bleicher continued.
Although acknowledging the “value in delineating the risk of dying from cancer vs the risk of dying from the SARS-CoV-2 pandemic,” Bleicher urged caution in using the tool to make individual patient decisions.
“We need to remember that the best of modeling ... can be wildly inaccurate and needs to be validated using patients having the circumstances in question. ... This won’t be possible until long after the pandemic is completed, and so the model’s accuracy remains unknown.”
That sentiment was echoed by Giampaolo Bianchini, MD, head of the Breast Cancer Group, Department of Medical Oncology, Ospedale San Raffaele, in Milan, Italy.
“Arbitrarily postponing and modifying treatment strategies including surgery, radiation therapy, and medical therapy without properly balancing the risk/benefit ratio may lead to significantly worse cancer-related outcomes, which largely exceed the actual risks for COVID,” he wrote in an email.
“The OncCOVID app is a remarkable attempt to fill the gap between perception and estimation,” he said. The app provides side by side the COVID-19 risk estimation and the consequences of arbitrary deviation from the standard of care, observed Bianchini.
However, he pointed out weaknesses, including the fact that the “data generated in literature are not always of high quality and do not take into consideration relevant characteristics of the disease and treatment benefit. It should for sure be used, but then also interpreted with caution.”
Another Italian group responded more positively.
“In our opinion, it could be a useful tool for clinicians,” wrote colleagues Alessio Cortelinni and Giampiero Porzio, both medical oncologists at San Salvatore Hospital and the University of L’Aquila, in Italy. “This Web app might assist clinicians in balancing the risk/benefit ratio of being treated and/or access to the outpatient cancer center for each kind of patient (both early and advanced stages), in order to make a more tailored counseling,” they wrote in an email. “Importantly, the Web app might help those clinicians who work ‘alone,’ in peripheral centers, without resources, colleagues, and multidisciplinary tumor boards on whom they can rely.”
Bleicher, who was involved in the COVID-19 Breast Cancer Consortium’s recommendations for prioritizing breast cancer treatment, summarized that the app “may end up being close or accurate, but we won’t know except in hindsight.”
This article first appeared on Medscape.com.