Evidence map›Paper›PMID 40453535›Full record

ArticleEClinicalMedicine2025

Determinants of SARS-CoV-2 outcomes in patients with cancer vs controls without cancer: a multivariable meta-analysis with genomic imputation.

Mark T K Cheng, James S Morris, Syed F H Shah, Abraham Tolley, José Chen-Xu, Nihal Sogandji, Long H Fong, Anushka Irodi, Justine T N Chan, Kimia Kamelian and 12 more

Abstract read
In one paragraph

Article in EClinicalMedicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

22 authors.

Mark T K ChengUniversity of Cambridge School of Clinical Medicine, Addenbrooke's Hospital NHS Foundation Trust, Hills Road, Cambridge, UK, CB2 0QQ.
James S MorrisUniversity of Cambridge School of Clinical Medicine, Addenbrooke's Hospital NHS Foundation Trust, Hills Road, Cambridge, UK, CB2 0QQ.
Syed F H ShahJohn Radcliffe Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, UK.
Abraham TolleyUniversity of Cambridge School of Clinical Medicine, Addenbrooke's Hospital NHS Foundation Trust, Hills Road, Cambridge, UK, CB2 0QQ.
José Chen-XuNational School of Public Health, NOVA University of Lisbon, Portugal.
Nihal SogandjiUniversity of Cambridge School of Clinical Medicine, Addenbrooke's Hospital NHS Foundation Trust, Hills Road, Cambridge, UK, CB2 0QQ.
Long H FongDepartment of Health Policy, London School of Economics and Political Science, London, WC2A 2AE, UK.
Anushka IrodiUniversity of Cambridge School of Clinical Medicine, Addenbrooke's Hospital NHS Foundation Trust, Hills Road, Cambridge, UK, CB2 0QQ.
Justine T N ChanUniversity of Cambridge School of Clinical Medicine, Addenbrooke's Hospital NHS Foundation Trust, Hills Road, Cambridge, UK, CB2 0QQ.
Kimia KamelianCambridge Institute of Therapeutic Immunology & Infectious Disease (CITIID), Department of Medicine, University of Cambridge, Cambridge, UK.
Benjamin L SieversCambridge Institute of Therapeutic Immunology & Infectious Disease (CITIID), Department of Medicine, University of Cambridge, Cambridge, UK.
Shazia SarelaDepartment of Medicine, University College London (UCL), London, UK.
Margaret K HoDepartment of Medicine, Queen Mary Hospital, Hong Kong.
Abigail BurnUniversity of Cambridge School of Clinical Medicine, Addenbrooke's Hospital NHS Foundation Trust, Hills Road, Cambridge, UK, CB2 0QQ.
Anita PatelUniversity of Cambridge School of Clinical Medicine, Addenbrooke's Hospital NHS Foundation Trust, Hills Road, Cambridge, UK, CB2 0QQ.
Ghislaine D MboloSchool of Medicine, University of Liverpool, Liverpool, UK.
Muhammad HasanLeeds School of Medicine, University of Leeds, Leeds, UK.
Abdulbasit O FehintolaCollege of Medicine, University of Ibadan, Ibadan, Nigeria.
Chan C YinLi Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region of China.
Enti SpataBiometrics, Respiratory and Immunology, Research and Development, AstraZeneca, Cambridge, UK.
Ravindra K GuptaCambridge Institute of Therapeutic Immunology & Infectious Disease (CITIID), Department of Medicine, University of Cambridge, Cambridge, UK.
David M FavaraMRC-Laboratory of Molecular Biology, Cambridge, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: SARS-CoV-2 is known to impact patients with cancer adversely. Previous meta-analyses have lacked clarity on the recency of cancer diagnosis, anti-cancer treatment durations, and SARS-CoV-2 specific variants of concern (VOC). This study aimed to compare SARS-CoV-2 multivariable-adjusted clinical outcomes between patients with cancer and those without cancer, identifying key risk factors spanning pre- and post-Omicron periods. Methods: In this systematic review and meta-analysis, we identified from Medline, Embase, Cochrane Central, and the WHO COVID-19 Research Database prospective and retrospective case-control studies and cohort studies published from 1st January 2019 to 22nd November 2024. We included case-control and cohort studies comparing at least 10 patients with active cancer (diagnosed or treated within three years prior to SARS-CoV-2 infection) to controls without cancer using multivariable analyses. Exclusion criteria included lack of clarity about active/inactive status of cancer, lack of a control group without cancer, lack of multivariate analysis comparing outcomes of interest in patients with active cancer vs patients without cancer, case reports or case series, and SARS-CoV-2 diagnosis not confirmed via laboratory testing. Outcomes measured were SARS-CoV-2 infection severity (WHO ordinal scale) and mortality differences by tumour type, treatment, and VOC (using sequencing data from NCBI Genbank and GISAID). A random-effects meta-analysis model was applied. The systematic review was PRISMA compliant and was registered with PROSPERO, CRD420234454524. Findings: Of 35,501 studies initially identified, 30 met eligibility criteria and were included in the meta-analysis, comprising 281,270 patients with cancer and 18,876,411 controls. Using the Agency for Healthcare Research and Quality (AHRQ) risk of bias standards, 21 studies were rated good, one study rated was fair, and eight studies were rated poor. We found higher mortality odds ratios (OR) in patients with cancer infected with SARS-CoV-2: 1·40 (95% CI: 1·12-1·73, I Interpretation: This comprehensive meta-analysis indicates that patients with active cancer with SARS-CoV-2 have a higher risk of mortality and hospitalisation than those without cancer. The risk of death was comparable between active solid and haematological tumours. SARS-CoV-2 severity and mortality risks were higher with thoracic, colorectal, or any metastatic cancers. Additionally, differences were noted in mortality risks across VOCs, diverging from VOC-associated mortality patterns in the general population. However, the strict three-year cutoff used to define active cancer excludes studies that used broader cancer criteria (i.e., any history of cancer), which may limit generalisability. Further limitations include varied definitions of disease severity, retrospective data collection, incomplete vaccination or lineage data, and significant between-study heterogeneity, potentially influencing these findings. Funding: Cancer Research UK; UK Research and Innovation.

Indexed as

CancerCOVID-19HospitalisationIntensive careMeta-analysisMortalitySARS-CoV-2SeveritySystematic review

Identifiers

PMID40453535
PMCPMC12123352

What OpenQuestion holds

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Registered trials

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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.