Evidence map›Paper›PMID 40080514›Full record

ArticlePloS one2025

Association of red and processed meat consumption with cancer incidence and mortality: An umbrella review protocol.

Ying Li, Shuping Yang, Chenyu Yu, Mei Wu, Sibin Huang, Yong Diao, Xunxun Wu, Huiyong Yang, Zhenyu Ma

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Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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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

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3 · Its place in the literature

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4 · The record

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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

9 authors.

Ying LiSchool of Medicine, Huaqiao University, Quanzhou, Fujian, China.ORCID 0009-0005-3813-1676
Shuping YangSchool of Medicine, Huaqiao University, Quanzhou, Fujian, China.
Chenyu YuSchool of Medicine, Huaqiao University, Quanzhou, Fujian, China.
Mei WuSchool of Medicine, Huaqiao University, Quanzhou, Fujian, China.
Sibin HuangSchool of Medicine, Huaqiao University, Quanzhou, Fujian, China.
Yong DiaoSchool of Medicine, Huaqiao University, Quanzhou, Fujian, China.
Xunxun WuSchool of Medicine, Huaqiao University, Quanzhou, Fujian, China.
Huiyong YangSchool of Medicine, Huaqiao University, Quanzhou, Fujian, China.ORCID 0009-0009-0743-6038
Zhenyu MaCheeloo College of Medicine, Shandong University, Jinan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMany meta-analyses have reported the associations between red and processed meat consumption and cancer outcomes, but few have assessed the credibility of the evidence. In addition, the results of dose-effect analyses of the association between red and processed meat consumption and cancer outcomes were inconsistently reported in different articles. Here we propose a protocol for an umbrella review (UR) that be designed to assess these associations and explore the potential dose-response relationships.

methodsWe will independently search five electronic databases and two registers from inception to July 2024 for systematic reviews with meta-analysis concerning the associations of red and processed meat consumption with cancer incidence and mortality. We will conduct the statistical analysis between August 2024 and December 2024. Also, an up-to-date search for additional primary studies of cancer outcomes that were not included in previously published meta-analyses will be conducted. The main outcomes will include the incidence and mortality of any cancer related to red and processed meat exposure. A series of unique associations will be created based on the cancer outcome, exposure, and clinical or population setting. For each association, we will update the meta-analysis by combining studies included in prior meta-analyses and new studies that were not included in prior meta-analyses, and re-perform the meta-analysis using the random-effects models. According to the credibility of the evidence assessment, all associations with a P value of ≤  0.05 will be categorized as convincing, highly suggestive, suggestive, or weak evidence. All analyses will be performed in R (version 4.2.3).

resultsThe results of this UR are planned to be submitted to a peer-reviewed journal.

conclusionThe main aim of protocol publication is to get feed back from the reviewers to develop a standard protocol before its publication and after publication, it should guide this protocol to take up similar research by any researcher(s) by following meticulously this standard protocol. REGISTRATION: PROSPERO CRD42023414550.

Indexed as

Meat ProductsNeoplasmsRed MeatHumansIncidenceMeta-Analysis as TopicSystematic Reviews as Topic

Identifiers

PMID40080514
PMCPMC11906087

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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.