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Rapid real‐world data analysis of patients with cancer, with and without COVID‐19, across distinct health systems
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 patie...
Autores principales: | , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8209944/ https://www.ncbi.nlm.nih.gov/pubmed/34014037 http://dx.doi.org/10.1002/cnr2.1388 |
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author | Hwang, Clara Izano, Monika A. Thompson, Michael A. Gadgeel, Shirish M. Weese, James L. Mikkelsen, Tom Schrag, Andrew Teka, Mahder Walters, Sheetal Wolf, Frank M. Hirsch, Jonathan Rivera, Donna R. Kluetz, Paul G. Singh, Harpreet Brown, Thomas D. |
author_facet | Hwang, Clara Izano, Monika A. Thompson, Michael A. Gadgeel, Shirish M. Weese, James L. Mikkelsen, Tom Schrag, Andrew Teka, Mahder Walters, Sheetal Wolf, Frank M. Hirsch, Jonathan Rivera, Donna R. Kluetz, Paul G. Singh, Harpreet Brown, Thomas D. |
author_sort | Hwang, Clara |
collection | PubMed |
description | 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 <$30 000. Patients with COVID‐19 living in lower‐income areas and NHB patients were at greatest risk for hospitalization from pneumonia, fluid and electrolyte disorders, cough, respiratory failure, and acute renal failure and were more likely to receive hydroxychloroquine. All‐cause mortality, hospital admission, and invasive respiratory support were more frequent among patients with cancer and COVID‐19. Male sex, increasing age, living in zip codes with median household income <$30 000, history of pulmonary circulation disorders, and recent treatment with immune checkpoint inhibitors or chemotherapy were associated with greater odds of all‐cause mortality in multivariable logistic regression models. CONCLUSION: RWD can be rapidly leveraged to understand urgent healthcare challenges. Patients with cancer are more vulnerable to COVID‐19 effects, especially in the setting of active cancer and comorbidities, with additional risk observed in NHB patients and those living in zip codes with median household income <$30 000. |
format | Online Article Text |
id | pubmed-8209944 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-82099442021-06-21 Rapid real‐world data analysis of patients with cancer, with and without COVID‐19, across distinct health systems Hwang, Clara Izano, Monika A. Thompson, Michael A. Gadgeel, Shirish M. Weese, James L. Mikkelsen, Tom Schrag, Andrew Teka, Mahder Walters, Sheetal Wolf, Frank M. Hirsch, Jonathan Rivera, Donna R. Kluetz, Paul G. Singh, Harpreet Brown, Thomas D. Cancer Rep (Hoboken) Original Articles 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 <$30 000. Patients with COVID‐19 living in lower‐income areas and NHB patients were at greatest risk for hospitalization from pneumonia, fluid and electrolyte disorders, cough, respiratory failure, and acute renal failure and were more likely to receive hydroxychloroquine. All‐cause mortality, hospital admission, and invasive respiratory support were more frequent among patients with cancer and COVID‐19. Male sex, increasing age, living in zip codes with median household income <$30 000, history of pulmonary circulation disorders, and recent treatment with immune checkpoint inhibitors or chemotherapy were associated with greater odds of all‐cause mortality in multivariable logistic regression models. CONCLUSION: RWD can be rapidly leveraged to understand urgent healthcare challenges. Patients with cancer are more vulnerable to COVID‐19 effects, especially in the setting of active cancer and comorbidities, with additional risk observed in NHB patients and those living in zip codes with median household income <$30 000. John Wiley and Sons Inc. 2021-05-20 /pmc/articles/PMC8209944/ /pubmed/34014037 http://dx.doi.org/10.1002/cnr2.1388 Text en © 2021 The Authors. Cancer Reports published by Wiley Periodicals LLC. This article has been contributed to by US Government employees and their work is in the public domain in the USA. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Articles Hwang, Clara Izano, Monika A. Thompson, Michael A. Gadgeel, Shirish M. Weese, James L. Mikkelsen, Tom Schrag, Andrew Teka, Mahder Walters, Sheetal Wolf, Frank M. Hirsch, Jonathan Rivera, Donna R. Kluetz, Paul G. Singh, Harpreet Brown, Thomas D. Rapid real‐world data analysis of patients with cancer, with and without COVID‐19, across distinct health systems |
title | Rapid real‐world data analysis of patients with cancer, with and without COVID‐19, across distinct health systems |
title_full | Rapid real‐world data analysis of patients with cancer, with and without COVID‐19, across distinct health systems |
title_fullStr | Rapid real‐world data analysis of patients with cancer, with and without COVID‐19, across distinct health systems |
title_full_unstemmed | Rapid real‐world data analysis of patients with cancer, with and without COVID‐19, across distinct health systems |
title_short | Rapid real‐world data analysis of patients with cancer, with and without COVID‐19, across distinct health systems |
title_sort | rapid real‐world data analysis of patients with cancer, with and without covid‐19, across distinct health systems |
topic | Original Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8209944/ https://www.ncbi.nlm.nih.gov/pubmed/34014037 http://dx.doi.org/10.1002/cnr2.1388 |
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