Cancer patients have new app to calculate the bigger risk: Delaying treatment or catching the coronavirus

University of Michigan model personalizes risk analysis with 45 data points including type of cancer, age, and the local COVID-19 case load.

Cancer patients have a new app to help them calculate how risky it is to delay treatment to avoid catching COVID-19, thanks to researchers at the University of Michigan. 

Since the start of the pandemic, people with cancer have had to make a difficult decision: Get treatment at the hospital and risk contracting COVID-19 or delay treatment until the pandemic eases up. People with cancer are at a higher risk of catching the virus. Holly Hartman, a Ph.D. student in biostatistics at the University of Michigan’s School of Public Health and leading the OncCOVID app project at U-M’s Rogel Cancer Center, said the app will reassure patients that it’s OK to delay treatment.

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“We can show that the risk of delaying treatment isn’t going to be as severe when you compare the risk of going to the hospital and contracting COVID-19 there,” she said in a broadcast interview.

There are three tabs for data entry: Patient characteristics, cancer characteristics, and community COVID-19 data. The app calculates the risk of delay based on an individual’s risk factors, such as age, type of cancer, and cancer stage, as well as the number of COVID-19 cases at the county level. The app uses this data from more than 45 characteristics about a patient to calculate the patient’s likely five- or 10-year survival with immediate treatment and delayed treatment.

This customized risk benefit analysis replaces the generic approach most oncologists have been using for making this decision. Daniel Spratt, associate professor of radiation oncology at Michigan Medicine and one of the senior researchers on the project, said hospitals have basically been using a three-tiered approach to making this decision: Treat now, delay a little or delay a lot.

“Our goal was to create a resource that could be tailored both to the individual patient and to their local community,” he said in a press release. 

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After a doctor or patient enters personal characteristics in the app, the model calculates an estimated survival time for both immediate treatment or delayed treatment. An individual can see the different totals in both years and days. Doctors can specify the extent of the delay as well in days, months, and years.  

Spratt said healthcare systems rescheduling delayed cancer treatments also can use the OncCOVID app to prioritize a backlog of patients whose treatment was put on hold due to the pandemic.

The model that powers that app draws on millions of records contained in the National Cancer Institute’s Surveillance, Epidemiology, and End Results (SEER) registry and the National Cancer Database, combined with county-level COVID infection data from Johns Hopkins University.
 
Advanced features allow all of the app’s underlying statistical assumptions to be adjusted, such as the baseline mortality risk from COVID and the disease’s infection rate. The researchers said the app can inform decisions about when to schedule or delay treatment, but not provide medical advice. 

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Hartman said the next goal for the model behind the app is to look at the long-term effects of delaying cancer treatments at a national scale.
 
Matthew Schipper, associate professor of radiation oncology and biostatistics at U-M, was also a co-creator of the app. Other collaborators on the project include: Nicholas Zaorsky, Xi Wang, Ming Wang, and Vonn Walter of Pennsylvania State University; and Yilun Sun, Emily Morris, Elizabeth Chase, Theresa Devasia, Pin Li, Kelley Kidwell, Robert Dess, and William Jackson of U-M.
 
The work was supported, in part, by grants from the National Institutes of Health.

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