Impact of cancer diagnoses on the outcomes of patients with COVID-19: a systematic review and meta-analysis

Abstract

Background The COVID-19 has caused significant mortality and morbidity across the globe. Patients with cancer are especially vulnerable given their immunocompromised state. We aimed to determine the proportion of COVID-19 patients with cancer, their severity and mortality outcomes through a systematic review and meta-analysis (MA). Methods Systematic review was performed through online databases, PubMed, Medline and Google Scholar, with keywords listed in the Methods section (1 November 2019-31 December 2020). Studies with clinical outcomes of at least 10 COVID-19 patients and at least one with a diagnosis of cancer were included. The studies for MA were assessed with PRISMA guidelines and appraised with Newcastle-Ottawa Scale. The data were pooled using a random-effects model using STATA software. The main outcomes were planned before data collection, including proportion of patients with cancer among COVID-19 populations, relative risk (RR) of severe outcomes and death of patients with cancer compared with general COVID-19 patients. Results We identified 57 case series (63 413 patients), with 230 patients with cancer with individual patient data (IPD). We found that the pooled proportion of cancer among COVID-19 patients was 0.04 (95% CI 0.03 to 0.05, I 2 =97.69%, p<0.001). The pooled RR of death was 1.44 (95% CI 1.19 to 1.76) between patients with cancer and the general population with COVID-19 infection. The pooled RR of severe outcome was 1.49 (95% CI 1.18 to 1.87) between cancer and general COVID-19 patients. The presence of lung cancer and stage IV cancer did not result in significantly increased RR of severe outcome. Among the available IPD, only age and gender were associated with severe outcomes. Conclusion Patients with cancer were at a higher risk of severe and death outcomes from COVID-19 infection as compared with general COVID-19 populations. Limitations of this study include publication bias. A collaborative effort is required for a more complete database.