Based on currently available data, most of national health authorities and consensus expert groups have written guidelines for the management of cancer patients in the context of COVID. However, the preparation of these guidelines was limited by the scarcity of solid epidemiological data. For example, the experts were uncomfortable to formulate precise guidelines on which anti-cancer treatment should be interrupted or replaced, on which patients, and how to adapt supportive drug prescriptions.
Retrospective inclusion of n=200 cancer patients hospitalized for COVID and n=400 matched (based on age, gender, and comorbidity) non-cancer patients hospitalized for COVID. Two analyses will be performed (after the inclusion of n=100 and n=200 patients with cancer). A logistic modeling of the odds ratio of death associated to the exposition factor (i.e. cancer) and adjusted for the matching parameters (age, gender, comorbidities) will be proposed.
We will then look for the factors (related to the patients, the cancer or the treatment) that modify the odds radio.
The data generated will help the medical and scientific community to evaluate the increasing risk of cancer patients infected by SARS-CoV-2 compared to the non-cancer population, to identify patients at higher risk of severe infection, but also the anticancer treatments associated with an increased risk of severe infections.
These data will contribute to guide the future recommendations concerning cancer patient's care in the context of the COVID-19 pandemic. There is a real risk that the SARS-CoV epidemic, or other respiratory viruses epidemic, will become recurrent in the future. Thus, it is of crucial importance for now and for the future to know which are the major factors associated with severe infections
|Clinical Study Identifier||NCT04457570|
|Sponsor||Hospices Civils de Lyon|
|Last Modified on||12 July 2020|
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