Evidence map›Paper›PMID 33875976›Full record

SynthesisJNCI cancer spectrum2021

A Systematic Review and Meta-Analysis of Cancer Patients Affected by a Novel Coronavirus.

Bhanu Prasad Venkatesulu, Viveksandeep Thoguluva Chandrasekar, Prashanth Girdhar, Pragati Advani, Amrish Sharma, Thiraviyam Elumalai, Cheng En Hsieh, Hagar I Elghazawy, Vivek Verma, Sunil Krishnan

Open access · goldAbstract readMeta-AnalysisSystematic Review
PubMed Full text at PMC Publisher
In one paragraph

Synthesis in JNCI cancer spectrum, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 90 papers, 16 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
90citing papers in PubMed, 16 pooled it
8.8field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

90 citing papers in PubMed, 16 syntheses or guidelines pooled it, 123 citations in OpenAlex.

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30 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors at 9 institutions in 5 countries.

Bhanu Prasad VenkatesuluDepartment of Internal Medicine, Henry Ford Hospital, Detroit, MI, USA.ORCID 0000-0003-2541-2055
Viveksandeep Thoguluva ChandrasekarDepartment of Gastroenterology and Hepatology, University of Kansas Medical Center, Kansas City, KS, USA.
Prashanth GirdharDepartment of Radiation Oncology, All India Institute of Medical Sciences, New Delhi, India.
Pragati AdvaniRadiation Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Institutes of Health, National Cancer Institute, Bethesda, MD, USA.
Amrish SharmaDepartment of Experimental Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Thiraviyam ElumalaiDepartment of Clinical Oncology, The Christie NHS Foundation Trust, Manchester, UK.ORCID 0000-0003-4281-9826
Cheng En HsiehDepartment of Radiation Oncology, Institute for Radiological Research, Chang Gung Memorial Hospital at Linkou and Chang Gung University, Taoyuan City, Taiwan.ORCID 0000-0002-2038-4537
Hagar I ElghazawyDepartment of Clinical Oncology, Faculty of Medicine, Ain Shams University, Abbaseya, Cairo, Egypt.ORCID 0000-0001-6839-4147
Vivek VermaDepartment of Radiation Oncology, Allegheny General Hospital, Pittsburgh, PA, USA.ORCID 0000-0002-5863-6023
Sunil KrishnanDepartment of Radiation Oncology, Mayo Clinic Florida, Jacksonville, FL, USA.ORCID 0000-0002-1340-4771
The University of Texas MD Anderson Cancer Center · USAin Shams University · EGAllegheny General Hospital · USAll India Institute of Medical Sciences · INLoyola University Chicago · USNational Institutes of Health · USThe Christie NHS Foundation Trust · GBUniversity of Kansas Medical Center · USWinnMed · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCancer patients with coronavirus disease 2019 (COVID-19) have been reported to have double the case fatality rate of the general population.

methodsA 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.

resultsThis 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.

conclusionCancer 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.

Indexed as

AgedCerebrovascular DisordersCOVID-19Databases, FactualFemaleHospital MortalityHumansLiver DiseasesLung DiseasesMaleMetabolic DiseasesMiddle AgedNeoplasmsPandemicsRenal Insufficiency, ChronicSARS-CoV-2

Identifiers

PMID33875976
PMCPMC7928783
OpenAlexW3155510325

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.