In a recent study published in Life, researchers performed a systematic review and meta-analysis following the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines. This 17-item checklist facilitates the preparation and robust reporting of a systematic review.
Cancer Research eBook
First, the researchers identified the prognostic predictors of adult patients with hematologic malignancies and coronavirus disease 2019 (COVID-19). Additionally, they examined the effect of anticancer treatments on mortality among these patients.
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections are common in all cancer patients because they have weakened immunity due to treatment-related side effects. Studies have shown that those with hematologic malignancies are most vulnerable to developing severe COVID-19-related morbidities. Moreover, some cancer patients receiving immune checkpoint inhibitors require immunosuppressive drugs, which promote severe COVID-19.
Yet, data on COVID-19-related mortality in cancer patients receiving anticancer treatment is conflicting. Also, there is a shortage of meta-analyses specific to patients with hematologic malignancies up to 2022. Thus, it is critical to aggregate more data and obtain more accurate estimates of COVID-19-related risks in these patients.
About the study
In the present study, researchers performed a systematic review and meta-analysis of published literature to measure the impact of anticancer treatment on patients with COVID-19 and hematologic malignancies.
Two independent investigators performed a literature search of electronic databases (e.g., PubMed) up to September 2022 using keywords “coronavirus”, “SARS-CoV-2”, “2019-nCoV”, and “COVID-19”. Additional keywords used were “leukemia”, “lymphoma”, “hematologic malignancy”, “survival”, “death”, and “mortality”.
They extracted relevant data from all studies reporting data on adult patients of COVID-19 and hematologic malignancies, e.g., type of anticancer therapy. They contacted the original author for further data if needed. Furthermore, the researchers identified studies from the bibliographies of the retrieved articles. They used the Newcastle–Ottawa Scale to assess the quality of studies for meta-analyses. Studies with ≥7 stars and less than three stars were considered high and poor quality, respectively.
Lastly, the team used random-effects or fixed-effects models to estimate the overall mean effect sizes. They chose the fixed effects model for studies with I2 of less than 40%, a heterogeneity assessment statistic. An I2 of 0–40% indicated little, and 75 to 100% indicated considerable heterogeneity.
The primary outcome of this systemic review was the death risk among patients with COVID-19 and hematologic malignancies presented as a risk ratio (RR) with a 95% confidence interval (CI). The team also performed subgroup analyses to compare the mortality risk among males and females receiving and not receiving anticancer treatment.
After screening 13,931 articles, the researchers included 12 publications in the final meta-analysis. Most studies were of moderate to high quality and assigned six to nine stars. These studies, published between 2020 and 2022, covered 1200 patients from nine countries with COVID-19 and hematologic malignancies. The study population comprised 712 males, with an average of ~63 years. Seven, three, and two studies included patients with primary diagnoses of leukemia, leukemia and lymphoma, and only lymphoma, respectively.
In the anticancer and non-anticancer treatment groups, 234/618 and 160/516 patients died, respectively. The overall mortality rate was 32.8%, with an inter-group risk difference (RD) of 0.14 (95% CI). Anticancer therapies increased the mortality risk in patients with hematologic malignancies and COVID-19, more in females than males (RDs 0.57 vs. 0.28). Despite high heterogeneity, I2 = 76%, the pooled overall mortality estimates of the study were mostly from inpatient services. However, the researchers observed no heterogeneity in the male and female results, with I2 = 0%.
The pooled RD for mortality for the cancer patients not receiving and receiving immunosuppressive therapy was close to pooled RD for chemotherapy recipients. This finding suggested that immunosuppressive therapy exerted a similar effect as chemotherapy on the study cohort.
The current meta-analysis included multiple studies on patients with all types of cancers and receiving different anti-cancer treatments. Its findings were consistent with previous studies and showed that, among patients with COVID-19 and hematologic malignancies, those receiving anticancer therapy had a higher mortality risk, irrespective of sex.
These results could help devise guidelines for managing COVID-19 in patients with hematologic malignancies. Patients should be informed about COVID-19 symptoms, trained in hygiene practices, and guided on how to use personal protective equipment whenever they visit the hospital. Most importantly, these patients should still receive curative cancer treatment.
- Lin, W. et al. (2023) "Anticancer Therapy and Mortality of Adult Patients with Hematologic Malignancy and COVID-19: A Systematic Review and Meta-Analysis", Life, 13(2), p. 381. doi: 10.3390/life13020381. https://www.mdpi.com/2075-1729/13/2/381
Posted in: Medical Science News | Medical Research News | Disease/Infection News
Tags: Cancer, Cancer Treatment, Chemotherapy, Coronavirus, Coronavirus Disease COVID-19, covid-19, Drugs, Hospital, Hygiene, immunity, Leukemia, Lymphoma, Mortality, Personal Protective Equipment, Respiratory, SARS, SARS-CoV-2, Severe Acute Respiratory, Severe Acute Respiratory Syndrome, Syndrome
Neha is a digital marketing professional based in Gurugram, India. She has a Master’s degree from the University of Rajasthan with a specialization in Biotechnology in 2008. She has experience in pre-clinical research as part of her research project in The Department of Toxicology at the prestigious Central Drug Research Institute (CDRI), Lucknow, India. She also holds a certification in C++ programming.
Source: Read Full Article