Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Meta-Analysis
. 2023 Oct;23(6):1945-1959.
doi: 10.1007/s10238-023-01004-5. Epub 2023 Feb 16.

Mortality of COVID-19 in patients with hematological malignancies versus solid tumors: a systematic literature review and meta-analysis

Affiliations
Meta-Analysis

Mortality of COVID-19 in patients with hematological malignancies versus solid tumors: a systematic literature review and meta-analysis

Nicole Hardy et al. Clin Exp Med. 2023 Oct.

Abstract

Cancer patients are more vulnerable to COVID-19 compared to the general population, but it remains unclear which types of cancer have the highest risk of COVID-19-related mortality. This study examines mortality rates for those with hematological malignancies (Hem) versus solid tumors (Tumor). PubMed and Embase were systematically searched for relevant articles using Nested Knowledge software (Nested Knowledge, St Paul, MN). Articles were eligible for inclusion if they reported mortality for Hem or Tumor patients with COVID-19. Articles were excluded if they were not published in English, non-clinical studies, had insufficient population/outcomes reporting, or were irrelevant. Baseline characteristics collected included age, sex, and comorbidities. Primary outcomes were all-cause and COVID-19-related in-hospital mortality. Secondary outcomes included rates of invasive mechanical ventilation (IMV) and intensive care unit (ICU) admission. Effect sizes from each study were computed as logarithmically transformed odds ratios (ORs) with random-effects, Mantel-Haenszel weighting. The between-study variance component of random-effects models was computed using restricted effects maximum likelihood estimation, and 95% confidence intervals (CIs) around pooled effect sizes were calculated using Hartung-Knapp adjustments. In total, 12,057 patients were included in the analysis, with 2,714 (22.5%) patients in the Hem group and 9,343 (77.5%) patients in the Tumor group. The overall unadjusted odds of all-cause mortality were 1.64 times higher in the Hem group compared to the Tumor group (95% CI: 1.30-2.09). This finding was consistent with multivariable models presented in moderate- and high-quality cohort studies, suggestive of a causal effect of cancer type on in-hospital mortality. Additionally, the Hem group had increased odds of COVID-19-related mortality compared to the Tumor group (OR = 1.86 [95% CI: 1.38-2.49]). There was no significant difference in odds of IMV or ICU admission between cancer groups (OR = 1.13 [95% CI: 0.64-2.00] and OR = 1.59 [95% CI: 0.95-2.66], respectively). Cancer is a serious comorbidity associated with severe outcomes in COVID-19 patients, with especially alarming mortality rates in patients with hematological malignancies, which are typically higher compared to patients with solid tumors. A meta-analysis of individual patient data is needed to better assess the impact of specific cancer types on patient outcomes and to identify optimal treatment strategies.

Keywords: COVID-19; Cancer; Leukemia; Lymphoma; Mortality; Tumor.

PubMed Disclaimer

Conflict of interest statement

JMP is employed by and holds equity in Superior Medical Experts and Nested Knowledge. AM is employed by Superior Medical Experts. NH is employed by and holds equity in Nested Knowledge. KK has ownership interest in Nested Knowledge, Inc. JT, RT, and PO are employed by Nested Knowledge.

Figures

Fig. 1
Fig. 1
PRISMA diagram of search results and included studies automatically generated by the AutoLit platform
Fig. 2
Fig. 2
Forest plot of comparisons of all-cause mortality between groups
Fig. 3
Fig. 3
Forest plot of comparisons of COVID-19-related mortality between groups
Fig. 4
Fig. 4
Forest plot of comparisons of IMV treatment between groups
Fig. 5
Fig. 5
Forest plot of comparisons of ICU admission rates between groups

Similar articles

Cited by

References

    1. COVID-19 dashboard by the center for systems science and engineering (CSSE) at Johns Hopkins University. In. Coronavirus resource center: Johns Hopkins University & Medicine. 2020
    1. Singh AK, Gillies CL, Singh R, Singh A, Chudasama Y, Coles B, Seidu S, Zaccardi F, Davies MJ, Khunti K. Prevalence of co-morbidities and their association with mortality in patients with COVID-19: a systematic review and meta-analysis. Diabetes Obes Metab. 1915;22(10):2020. - PMC - PubMed
    1. Dessie ZG, Zewotir T. Mortality-related risk factors of COVID-19: a systematic review and meta-analysis of 42 studies and 423,117 patients. BMC Infect Dis. 2021;21(1):855. doi: 10.1186/s12879-021-06536-3. - DOI - PMC - PubMed
    1. Izcovich A, Ragusa MA, Tortosa F, Lavena Marzio MA, Agnoletti C, Bengolea A, Ceirano A, Espinosa F, Saavedra E, Sanguine V, Tassara A, Cid C, Catalano HN, Agarwal A, Foroutan F, Rada G. Prognostic factors for severity and mortality in patients infected with COVID-19: a systematic review. PLoS ONE. 2020;15(11):e0241955. doi: 10.1371/journal.pone.0241955. - DOI - PMC - PubMed
    1. Parohan M, Yaghoubi S, Seraji A, Javanbakht MH, Sarraf P, Djalali M. Risk factors for mortality in patients with Coronavirus disease 2019 (COVID-19) infection: a systematic review and meta-analysis of observational studies. Aging Male. 2020;23(5):1416. doi: 10.1080/13685538.2020.1774748. - DOI - PubMed