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Nationwide study reveals the deadly impact of the coronavirus on cancer patients In a study of 2,000 cancer patients, hydroxychloroquine showed no clinical benefit. Remdesivir was associated with a lower mortality risk but only certain groups of patients had access to it. Cancer patients also showed a higher risk of dying within 30 days of receiving a coronavirus diagnosis.

While scientists are starting to understand the coronaviruses’ biology and how it kills, we’re still at odds at who’s most at-risk of dying. At first, we thought it would be elderly adults and people with disease, but now reports show young adults and children with COVID-19 infection are becoming severely ill. Age appears to be only one part of the conversation. 

What’s the chance of survival for a person with cancer? There are many unknowns about the virus’s impact on cancer, and cancer patients already have a tough time fighting off infection with their weakened immune systems. For this reason, 100 cancer centers formed the COVID-19 & Cancer Consortium with the goal of understanding how the coronavirus affects cancer patients. Their findings were published in Cancer Discovery.

From March 17th to June 26th, 2,186 cancer patients filled out surveys on treatment history and demographics. Study eligibility included patients with a history of cancer and a positive COVID-19 diagnosis. Patients were excluded from the study if they missed treatment or had missing health information. In addition, patients taking certain types of medications for other diseases before the coronavirus diagnosis were also excluded. This was because drug effects from other treatments could influence the results. 

The ECOG scale. Click image to Enlarge. Ginamisra / CC BY-SA

The severity of cases was different amongst patients with 47% of patients being mild (no hospitalization needed), 40% being moderate (some type of hospitalization recommended), and 12% being severe (hospitalization in the ICU recommended). In terms of patient characteristics, the median age was 67 years old, 51% were non-Hispanic whites, and 46% lived in the Northeast. Approximately 51% of patients were in remission, 28% were in stable or actively responding to treatment, and 11% had actively progressing cancer. The most common pre-existing conditions reported by patients were hypertension (58%), obesity (32%), and heart problems (32%).. The researchers also measured how the disease impacted the patient using the ECOG Performance Scale. This scale allows doctors to describe the overall well-being of a cancer patient on a scale of 0 to 5, where 0 means fully functioning and 5 means dead. A score of 2 or more indicated poor performance: being bed-ridden, disabled, or unable to work. About 16% of patients in the study showed poor performance.

The most common treatment for COVID-19 infection was the anti-malarial drug hydroxychloroquine in combination with the antibiotic azithromycin (23%). Giving hydroxychloroquine (21%) or azithromycin (18%) alone was the next popular option followed by the antiviral drug remdesivir (7%).

To predict the likelihood of a person receiving a certain type of medication, the authors used a model called multiple logistics regression. It involves creating equations that look at how much factors like race and pre-existing health problems contribute to treatment choices. They found patients living in the Western part of the United States and patients with heart problems were less likely to receive hydroxychloroquine plus azithromycin while patients with kidney problems were more likely to be prescribed this treatment. 

For remdesivir, Black patients were half as likely to be prescribed the drug compared to white patients. Patients with kidney problems and patients with an ECOG score of 2+ were less likely to receive it as well. Cancer patients living in the Western US were more likely to be prescribed remdesivir. 

A surprising finding was that 92% of cancer patients died within 30 days of receiving their COVID-19 diagnosis. Did differences in treatment cause this high mortality rate? The team used their equations to calculate the odds of dying within 30 days of receiving a COVID-19 diagnosis, and how much influence treatment and other demographic factors had on this. 

Cancer patients given hydroxychloroquine plus another drug had a higher risk of dying in 30 days. However, this increased risk was not observed in cancer patients who only received hydroxychloroquine. The researchers found high-dose corticosteroids were associated with overall risk of mortality in cancer patients. 

Remdesivir was the only drug to lower the mortality rate within 30 days of a coronavirus diagnosis. Other factors the researchers report were linked to an increased risk of dying in 30 days were old age (27%), active cancer (26%), an ECOG score of 2 or higher (35%), as well as severity of infection. However, decreased mortality correlated with cancer patients living in the Midwest.

As the world battles the coronavirus, some are faring worse than others. According to the authors, cancer patients are at a higher risk of dying from the coronavirus compared to the general population. This current study highlights several reasons that could be increasing this risk and blocking cancer patients from receiving appropriate treatment. For instance, while remdesivir lowered the mortality rate, access to this treatment was low and mostly given if patients were enrolled in clinical trials. The authors say that addressing race and health-related differences in the treatment of cancer patients could help improve their survival rates.

125390cookie-checkNationwide study reveals the deadly impact of the coronavirus on cancer patients In a study of 2,000 cancer patients, hydroxychloroquine showed no clinical benefit. Remdesivir was associated with a lower mortality risk but only certain groups of patients had access to it. Cancer patients also showed a higher risk of dying within 30 days of receiving a coronavirus diagnosis.

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Study Information

Original study: Utilization of COVID-19 treatments and clinical outcomes among patients with cancer: A COVID-19 and Cancer Consortium (CCC19) cohort study

Study published on: July 22, 2020

Study author(s): Donna R Rivera, Solange Peters, Orestis A Panagiotou, Dimpy P Shah, Nicole M. Kuderer, Chih-Yuan Hsu, Samuel M. Rubinstein, Brendan J Lee, Toni K Choueiri, Gilberto de Lima Lopes, Petros Grivas, Corrie A Painter, Brian I. Rini, Michael A. Thompson, Jonathan Arcobello, Ziad Bakouny, Deborah B Doroshow, Pamela C. Egan, Dimitrios Farmakiotis, Leslie Anne Fecher, Christopher R Friese, Matthew D Galsky, Sanjay Goel, Shilpa Gupta, Thorvardur R. Halfdanarson, Balazs Halmos, Jessica E Hawley, Ali Raza Khaki, Christopher A. Lemmon, Sanjay Mishra, Adam J Olszewski, Nathan A Pennell, Matthew M. Puc, Sanjay G. Revankar, Lidia Schapira, Andrew Schmidt, Gary K. Schwartz, Sumit A Shah, Julie T Wu, Zhuoer Xie, Albert C. Yeh, Huili Zhu, Yu Shyr, Gary H. Lyman and Jeremy L Warner

The study was done at: National Cancer Institute, Lausanne University Hospital, Brown University, University of Texas, Advanced Research and Cancer Group, LLC, Vanderbilt University, UNC Chapel Hill, Dana-Farber Cancer Institute, Northwestern University, University of Washington, Broad Institute, Advocate Aurora Health, Karmanos Cancer Institute, Mount Sinai, Lifespan Cancer Institute, University of Michigan, Albert Einstein College of Medicine, Cleveland Clinic, Mayo Clinic, Columbia University, Rhode Island Hospital, Virtua Health, Wayne State University, Stanford University, Fred Hutchinson Cancer Institute,

The study was funded by: American Cancer Society and Hope Foundation for Cancer Research, The National Cancer Institute, The National Human Genome Research Institute, Vanderbilt Institute for Clinical and Translational Research. Pages 2-6 of the full text available here show the conflict-of-interest statements by the authors.

Raw data availability: The authors state -- “The dataset analyzed for the primary and secondary hypotheses will be made immediately available upon request; requests should be sent to contact@ccc19.org.“

Featured image credit: Coronavirus Illustration by Gerd Altmann on Pixabay Free for commercial use