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Predictors of mortality in hospitalized African American COVID-19 patients with cancer

  • 0Department of Medicine and Cancer Center, College of Medicine, Howard University, Washington, DC, USA.
Translational Cancer Research +

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April 15, 2024

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April 15, 2024

View abstract on PubMed

Summary

This summary is machine-generated.

COVID-19 cancer patients face higher mortality. A significant drop in albumin levels during hospitalization predicts death in these patients, highlighting a key marker for monitoring outcomes.

Area Of Science

  • Oncology
  • Infectious Diseases
  • Public Health

Background

  • Coronavirus disease 2019 (COVID-19) impacts patients differently based on health status.
  • The effect of COVID-19 on African Americans with cancer is not well understood.
  • This study investigates mortality markers in COVID-19 patients with cancer.

Purpose Of The Study

  • To identify demographic, clinical, and laboratory markers associated with mortality in COVID-19 patients with cancer.
  • To compare outcomes between COVID-19 patients with and without cancer.
  • To analyze predictors of mortality in cancer patients with COVID-19.

Main Methods

  • Retrospective review of COVID-19 hospitalized patients from Dec 2019 to Oct 2021.
  • Extracted clinical, treatment, lab, and pathological data for cancer patients (cases) and cancer-free patients (controls).
  • Conducted univariable and multivariable analyses using SPSS software.

Main Results

  • COVID-19 patients with cancer (n=49) had higher mortality (20.4%) than those without (n=463, 8.9%).
  • Cancer patients were older (mean age 70.6 vs 56.3 years) with longer hospital stays.
  • A significant reduction in albumin levels from admission to day 5 was associated with mortality in cancer patients (P<0.001).

Conclusions

  • Albumin levels show an inverse relationship with clinical outcomes in COVID-19 cancer patients.
  • Decreased albumin during hospitalization is a potential predictor of mortality in COVID-19 cancer patients.
  • Further research is needed to validate these findings and identify additional predictors.

Keywords:

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