Rapid real‐world data analysis of patients with cancer, with and without COVID‐19, across distinct health systems

Autor: Clara Hwang, Monika A. Izano, Michael A. Thompson, Shirish M. Gadgeel, James L. Weese, Tom Mikkelsen, Andrew Schrag, Mahder Teka, Sheetal Walters, Frank M. Wolf, Jonathan Hirsch, Donna R. Rivera, Paul G. Kluetz, Harpreet Singh, Thomas D. Brown
Jazyk: angličtina
Rok vydání: 2021
Předmět:
Zdroj: Cancer Reports, Vol 4, Iss 5, Pp n/a-n/a (2021)
Druh dokumentu: article
ISSN: 2573-8348
DOI: 10.1002/cnr2.1388
Popis: Abstract Background The understanding of the impact of COVID‐19 in patients with cancer is evolving, with need for rapid analysis. Aims This study aims to compare the clinical and demographic characteristics of patients with cancer (with and without COVID‐19) and characterize the clinical outcomes of patients with COVID‐19 and cancer. Methods and Results Real‐world data (RWD) from two health systems were used to identify 146 702 adults diagnosed with cancer between 2015 and 2020; 1267 COVID‐19 cases were identified between February 1 and July 30, 2020. Demographic, clinical, and socioeconomic characteristics were extracted. Incidence of all‐cause mortality, hospitalizations, and invasive respiratory support was assessed between February 1 and August 14, 2020. Among patients with cancer, patients with COVID‐19 were more likely to be Non‐Hispanic black (NHB), have active cancer, have comorbidities, and/or live in zip codes with median household income
Databáze: Directory of Open Access Journals