App weighs risks of cancer treatment delay during COVID-19
A new app helps doctors weigh the risks of delaying cancer treatment during the pandemic against the risk of COVID-19 infection while getting that care.
May 27, 2020 • 7 min • Source
A new app compares the long-term risks of delaying treatment for cancer patients during the COVID-19 pandemic to the risk of potential infection if someone undergoes surgery, chemotherapy, and/or radiation.
As the COVID-19 pandemic has overwhelmed health care systems across the country, doctors have postponed surgery and other treatments for thousands of patients with cancer. These delays may last for months, especially for those with early stage and less aggressive disease.
The OncCOVID app draws on large, national cancer datasets to help assess the risk from immediate treatment versus delayed treatment, depending on a patient’s individual characteristics, as well as on COVID’s impact on their local community.
“For many types of cancer, the data show delays in treatment lead to worse outcomes for patients,” says lead researcher Holly Hartman, a doctoral student in biostatistics at the University of Michigan’s School of Public Health.
“But each time a cancer patient goes to the hospital to receive care, they’re also putting themselves at higher risk of contracting COVID-19. So, it’s essential to balance the need for treatment for this very serious disease and the extra risk that COVID-19 poses for cancer patients, whose immune systems are often compromised.”
Risk of delaying cancer treatment
The researchers envision doctors using OncCOVID to help identify patients for whom the benefits of immediate treatment outweigh the risk from COVID-19.
“We also see the app providing additional reassurance to oncologists and their patients when the data show that delaying treatment will likely have little or no impact on a patient’s long-term outcome,” Hartman says.
Meanwhile, health care systems ramping services back up that need to prioritize a backlog of patients whose treatment was put on hold due to the pandemic could also use the OncCOVID app, says Daniel Spratt , associate professor of radiation oncology at Michigan Medicine and a senior researcher on the project.
“ Hospitals have basically been using a three-tiered system during COVID: treat, delay a little, or delay a lot,” he says. “Unfortunately, this tiered system is an extremely blunt instrument. Our goal was to create a resource that could be tailored both to the individual patient and to their local community.”
The app allows doctors to enter more than 45 characteristics about a patient—including their age, location, cancer type and stage, treatment plan, underlying medical conditions, and the proposed length of a delay in care. It then calculates the patient’s likely five- or 10-year survival following immediate treatment and delayed treatment.
Different situations, different assessments
Under the hood, the 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.
In some cases, the personalized risk assessments run counter to the generic, three-tiered approach.
For example, Spratt says, the team’s model shows that an otherwise healthy 45-year-old woman from Ann Arbor with stage 1 breast cancer actually has a slightly higher risk of dying over the next five years if treatment is delayed more than three months than if she’s treated immediately.
“Under the three-tiered model, care for this patient wouldn’t be considered life-threatening and it’s likely her care may be delayed for months under most of the published tier-based systems,” he says.
Conversely, under the team’s data model, immediate treatment would put a 70-year-old woman from New York City—where COVID-19 infections have been high—with stage 1 breast cancer and several underlying health conditions at significantly more risk than a three-month delay.
For the data savvy, advanced features allow for the adjustment of all of the app’s underlying statistical assumptions—such as the baseline mortality risk from COVID-19 and the disease’s infection rate.
In the future, the researchers plan to use the same data model to start looking at the effects that treatment delays due to the coronavirus pandemic may have on cancer mortality nationally, Hartman says.
The researchers caution the OncCOVID app should not provide medical advice to patients. A number of factors may figure into a care provider’s recommendation to delay or proceed with cancer treatment, including their local hospital’s capacity to safely treat cancer patients during the pandemic.
Additional collaborators are from Penn State and the University of Michigan. The National Institutes of Health supported the work.
Source: University of Michigan
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