Abstract Background Cancer patients with coronavirus disease 2019 (COVID-19) have been reported to have double the case fatality rate of the general population. Methods A systematic search of PubMed, Embase, and Cochrane Central was done for studies on cancer patients with COVID-19. Pooled proportions were calculated for categorical variables. Odds ratio (OR) and forest plots (random-effects model) were constructed for both primary and secondary outcomes. Results This systematic review of 38 studies and meta-analysis of 181 323 patients from 26 studies included 23 736 cancer patients. Our meta-analysis shows that cancer patients with COVID-19 have a higher likelihood of death (n = 165 980, OR = 2.54, 95% confidence interval [CI] = 1.47 to 4.42), which was largely driven by mortality among patients in China. Cancer patients were more likely to be intubated. Among cancer subtypes, the mortality was highest in hematological malignancies (n = 878, OR = 2.39, 95% CI = 1.17 to 4.87) followed by lung cancer (n = 646, OR = 1.83, 95% CI = 1.00 to 3.37). There was no association between receipt of a particular type of oncologic therapy and mortality. Our study showed that cancer patients affected by COVID-19 are a decade older than the normal population and have a higher proportion of comorbidities. There was insufficient data to assess the association of COVID-19–directed therapy and survival outcomes in cancer patients. Conclusion Cancer patients with COVID-19 disease are at increased risk of mortality and morbidity. A more nuanced understanding of the interaction between cancer-directed therapies and COVID-19–directed therapies is needed. This will require uniform prospective recording of data, possibly in multi-institutional registry databases.
【초록키워드】 COVID-19, coronavirus disease, Meta-analysis, therapy, Mortality, Hematological malignancy, Cancer, Comorbidities, systematic review, outcome, lung cancer, China, survival, morbidity, Patient, Cancer patients, death, General population, disease, association, Interaction, cancer patient, forest plot, Subtypes, Older, 95% CI, 95% confidence interval, increased risk, Secondary outcomes, Fatality rate, random-effects model, likelihood, Result, highest, affected, proportion, reported, calculated, driven by, patients with COVID-19, variables, with COVID-19, 【제목키워드】 review, novel,