Assessment of Regional Variability in COVID-19 Outcomes among Patients with Cancer in the United States

Jessica E. Hawley, Tianyi Sun, David D. Chism, Narjust Duma, Julie C. Fu, Na Tosha N. Gatson, Sanjay Mishra, Ryan H. Nguyen, Sonya A. Reid, Oscar K. Serrano, Sunny R.K. Singh, Neeta K. Venepalli, Ziad Bakouny, Babar Bashir, Mehmet A. Bilen, Paolo F. Caimi, Toni K. Choueiri, Scott J. Dawsey, Leslie A. Fecher, Daniel B. FloraChristopher R. Friese, Michael J. Glover, Cyndi J. Gonzalez, Sharad Goyal, Thorvardur R. Halfdanarson, Dawn L. Hershman, Hina Khan, Chris Labaki, Mark A. Lewis, Rana R. McKay, Ian Messing, Nathan A. Pennell, Matthew Puc, Deepak Ravindranathan, Terence D. Rhodes, Andrea V. Rivera, John Roller, Gary K. Schwartz, Sumit A. Shah, Justin A. Shaya, Mitrianna Streckfuss, Michael A. Thompson, Elizabeth M. Wulff-Burchfield, Zhuoer Xie, Peter Paul Yu, Jeremy L. Warner, Dimpy P. Shah, Benjamin French, Clara Hwang

Research output: Contribution to journalArticlepeer-review

Abstract

Importance: The COVID-19 pandemic has had a distinct spatiotemporal pattern in the United States. Patients with cancer are at higher risk of severe complications from COVID-19, but it is not well known whether COVID-19 outcomes in this patient population were associated with geography. Objective: To quantify spatiotemporal variation in COVID-19 outcomes among patients with cancer. Design, Setting, and Participants: This registry-based retrospective cohort study included patients with a historical diagnosis of invasive malignant neoplasm and laboratory-confirmed SARS-CoV-2 infection between March and November 2020. Data were collected from cancer care delivery centers in the United States. Exposures: Patient residence was categorized into 9 US census divisions. Cancer center characteristics included academic or community classification, rural-urban continuum code (RUCC), and social vulnerability index. Main Outcomes and Measures: The primary outcome was 30-day all-cause mortality. The secondary composite outcome consisted of receipt of mechanical ventilation, intensive care unit admission, and all-cause death. Multilevel mixed-effects models estimated associations of center-level and census division-level exposures with outcomes after adjustment for patient-level risk factors and quantified variation in adjusted outcomes across centers, census divisions, and calendar time. Results: Data for 4749 patients (median [IQR] age, 66 [56-76] years; 2439 [51.4%] female individuals, 1079 [22.7%] non-Hispanic Black individuals, and 690 [14.5%] Hispanic individuals) were reported from 83 centers in the Northeast (1564 patients [32.9%]), Midwest (1638 [34.5%]), South (894 [18.8%]), and West (653 [13.8%]). After adjustment for patient characteristics, including month of COVID-19 diagnosis, estimated 30-day mortality rates ranged from 5.2% to 26.6% across centers. Patients from centers located in metropolitan areas with population less than 250000 (RUCC 3) had lower odds of 30-day mortality compared with patients from centers in metropolitan areas with population at least 1 million (RUCC 1) (adjusted odds ratio [aOR], 0.31; 95% CI, 0.11-0.84). The type of center was not significantly associated with primary or secondary outcomes. There were no statistically significant differences in outcome rates across the 9 census divisions, but adjusted mortality rates significantly improved over time (eg, September to November vs March to May: aOR, 0.32; 95% CI, 0.17-0.58). Conclusions and Relevance: In this registry-based cohort study, significant differences in COVID-19 outcomes across US census divisions were not observed. However, substantial heterogeneity in COVID-19 outcomes across cancer care delivery centers was found. Attention to implementing standardized guidelines for the care of patients with cancer and COVID-19 could improve outcomes for these vulnerable patients..

Original languageEnglish (US)
Article numbere2142046
JournalJAMA network open
Volume5
Issue number1
DOIs
StatePublished - Jan 4 2022
Externally publishedYes

ASJC Scopus subject areas

  • Medicine(all)

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