COVID-19 Resource Center
COVID-19 Resource Center
Source: Press Release
Disclosures: Spratt reports nonrelevant conflicts of interest with AstraZeneca, Blue Earth and Janssen.
August 11, 2020
4 min read
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App estimates risk of delaying cancer treatment during pandemic

Source: Press Release
Disclosures: Spratt reports nonrelevant conflicts of interest with AstraZeneca, Blue Earth and Janssen.
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As the COVID-19 pandemic continues to impact various aspects of cancer care, oncologists must decide whether to delay treatment or proceed despite increased risk for infection with the novel coronavirus.

“The solution of almost every major organization was to develop a three-tier system,” Daniel Spratt, MD, associate professor of radiation oncology at University of Michigan’s Rogel Cancer Center, said in an interview with Healio. “Tier one is basically an emergency; you need to treat them. At tier two, you can delay a little bit. At tier three, we need to wait until the pandemic is over. The questions then become, who goes into those tiers and who decides this? Where are the data to guide the decision? There really aren’t any. The big problem is that it’s subjective.”

To address this lack of clarity, Spratt; Holly Hartman, MS, a PhD candidate in biostatistics; and colleagues at University of Michigan developed a free, web-based application to evaluate a patient’s risk with immediate vs. delayed treatment. The OncCOVID app utilizes large, national cancer data sets to determine risk based on the patient’s characteristics and the extent of COVID-19 infection in their local community.

Daniel Spratt
Daniel Spratt

Spratt spoke with Healio about this tool and its potential to guide physician decision-making while ensuring patient safety.

Question: How did the OncCOVID app come to be?

Answer: Because of the pandemic, hospitals were stopping cancer surgeries, reducing radiation treatments and being more selective with chemotherapy. I think surgery was affected most because patients undergoing surgery need hospital beds and ventilators, which were needed for patients with COVID-19. This prompted us to consider the effect for patients with cancer. Is it right to delay their treatment?

The tier system was quick and easy to implement. There is nothing wrong with it, but we thought we could improve upon it. We talk about precision medicine all the time, and this is about as far from that as possible. Also, treatments are very different. Some consist of one radiation treatment and you’re home. Some are 6 months of chemotherapy. A lot of factors go into it. A 40-year-old is very different than an 80-year-old in terms of their risk for dying of the coronavirus. A patient’s geographic location is very important, as well. So, we decided to focus our research efforts on this problem.

Q: How did you design your app to calculate the risks and benefits of delaying or continuing treatment?

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A: We leveraged a bunch of data sources. The first was the SEER registry, which includes data on over 25 cancer types. We’re embedding it for each cancer stage and type. Then we leveraged data from the National Cancer Database, which provides information on the time from diagnosis to treatment. Holly Hartman led the efforts in building a big model for as many cancer types as we could, looking at a patient’s age, as well as stage and type of cancer. With early-stage prostate cancer, for example, you could wait 6 months; a delay is not going to affect that guy’s survival. Someone with a high-grade brain tumor, however, might die if you wait 6 months.

Next, we looked at data from China, Italy, South Korea and the U.S. to determine what factors are related to patients dying of coronavirus. Older age increases the risk for death, as do heart disease and high blood pressure. We built a model around that which, based on the patient’s age and number of comorbidities, looks at the chance the patient will die of COVID-19 if they get the virus.

We also a the susceptible-infected-recovered (SIR) model, as well as the worldwide COVID-19 tracker. This tracks how many cases, worldwide by county, have been confirmed. It’s updated every day. So, if you put in “I am at the University of Michigan,” which is in Washtenaw County, Michigan, you can see that its rate and the shape of its curve are very different than those of Queens, New York.

We looked at other variables that have been shown to increase the risk for contracting or dying of COVID-19 and put this together with a group of about 10 biostatisticians, led by Holly Hartman. It’s integrated into the app online and shows a patient’s OS with continued immediate treatment vs. delayed treatment.

We have seen, in comparing this with the tiered approach, that there are patients in tier one who should probably be in tier three, and patients in tier two who should be in tier one — it’s all over the place.

Q: How might the app provide reassurance to patients?

A: Some of my patients are very afraid to come in for treatment. With this, I can say, “Look, you have a 0.05% chance of dying of the coronavirus from getting treatment, but you have a 10% chance of dying of your cancer if we continue to delay treatment.” Some patients, conversely, are afraid to delay their treatment. So now, in either circumstance, I can give patients information to clarify why that treatment plan is safest for them. The app has been very helpful for me, in many circumstances, to show patients that it’s either very safe to come in for treatment, at least in our county, or that it’s very safe for them to delay.

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Q: Will your app be adopted for widespread use in U.S. institutions?

A: Ultimately, it’s up to institutions in terms of how they want to make these decisions. Some of the more rural hospitals have not been as affected by the coronavirus, so they haven’t had to defer treatment for many patients. Big, urban areas have thousands of patients in the queue who have been deferred.

The OncCOVID model is available online at http://onccovid.med.umich.edu/ and people all over the world have been accessing it.

For more information:

Daniel Spratt, MD, can be reached at sprattda@med.umich.edu.