Purpose: This study aimed to describe the demographic and clinical characteristics of cancer patients with COVID-19, exploring factors associated with adverse outcomes.
Patients and methods: This retrospective cohort study methodically extracted and curated data from electronic medical records (EMRs) of numerous healthcare institutions on cancer patients diagnosed with a confirmed SARS-CoV-2 infection between May 2020 and August 2021, to identify risk factors linked to extended hospitalization and mortality. The retrieved information encompassed the patients' demographic and clinical characteristics, including the incidence of prolonged hospitalization, acute complications, and COVID-19-related mortality.
Results: A total of 1446 cancer patients with COVID-19 were identified (mean [Standard deviation] age, 59.2 [14.3] years). Most patients were female (913 [63.1%]), non-white (646 [44.7%]), with non-metastatic (818 [56.6%]) solid tumors (1318 [91.1%]), and undergoing chemotherapy (647 [44.7%]). The rate of extended hospitalization due to COVID-19 was 46% (n = 665), which was significantly impacted by age (p = 0.012), sex (p = 0.003), race and ethnicity (p = 0.049), the presence of two or more comorbidities (p = 0.006), hematologic malignancies (p = 0.013), metastatic disease (p = 0.002), and a performance status ≥ 2 (p = 0.001). The COVID-19-related mortality rate was 18.9% (n = 273), and metastatic disease (<0.001), performance status ≥2 (<0.001), extended hospitalization (p = 0.028), renal failure (p = 0.029), respiratory failure (p < 0.001), sepsis (p = 0.004), and shock (p = 0.040) significantly and negatively influenced survival.
Conclusion: The rate of extended hospitalization and COVID-19-specific death in cancer patients was notably high and could be influenced by comorbidities, cancer treatment status, and clinical fragility. These observations may aid in developing risk counseling strategies regarding COVID-19 in individuals diagnosed with cancer.
Copyright: © 2023 da Silva et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.