Evidence map›Paper›PMID 42523589›Full record

SynthesisFrontiers in nutrition2026

Red and processed meat consumption and the risk of pancreatic cancer: a systematic review and dose-response meta-analysis.

Yina Lu, Minqi Gu, Yang Zhao, Liangze Ma, Yuchen Wei, Ziyang Liu, Yuying Wu, Xueru Fu, Jinliang Liang, Li Yang and 6 more

Abstract readSystematic Review
In one paragraph

Synthesis in Frontiers in nutrition, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

16 authors.

Yina Lu *Department of Biostatistics and Epidemiology, School of Public Health, Shenzhen University Medical School, Shenzhen, Guangdong, China.
Minqi Gu *Department of Biostatistics and Epidemiology, School of Public Health, Shenzhen University Medical School, Shenzhen, Guangdong, China.
Yang ZhaoDepartment of Biostatistics and Epidemiology, School of Public Health, Shenzhen University Medical School, Shenzhen, Guangdong, China.
Liangze MaDepartment of Biostatistics and Epidemiology, School of Public Health, Shenzhen University Medical School, Shenzhen, Guangdong, China.
Yuchen WeiDepartment of Biostatistics and Epidemiology, School of Public Health, Shenzhen University Medical School, Shenzhen, Guangdong, China.
Ziyang LiuDepartment of Biostatistics and Epidemiology, School of Public Health, Shenzhen University Medical School, Shenzhen, Guangdong, China.
Yuying WuDepartment of Biostatistics and Epidemiology, School of Public Health, Shenzhen University Medical School, Shenzhen, Guangdong, China.
Xueru FuDepartment of Biostatistics and Epidemiology, School of Public Health, Shenzhen University Medical School, Shenzhen, Guangdong, China.
Jinliang LiangDepartment of Biostatistics and Epidemiology, School of Public Health, Shenzhen University Medical School, Shenzhen, Guangdong, China.
Li YangDepartment of Biostatistics and Epidemiology, School of Public Health, Shenzhen University Medical School, Shenzhen, Guangdong, China.
Yaqin SuDepartment of Biostatistics and Epidemiology, School of Public Health, Shenzhen University Medical School, Shenzhen, Guangdong, China.
Taifeng ChenDepartment of Biostatistics and Epidemiology, School of Public Health, Shenzhen University Medical School, Shenzhen, Guangdong, China.
Dongdong ZhangDepartment of General Practice, The Affiliated Luohu Hospital of Shenzhen University Medical School, Shenzhen, China.
Fulan HuDepartment of Biostatistics and Epidemiology, School of Public Health, Shenzhen University Medical School, Shenzhen, Guangdong, China.
Dongsheng HuDepartment of Biostatistics and Epidemiology, School of Public Health, Shenzhen University Medical School, Shenzhen, Guangdong, China.
Ming ZhangDepartment of Biostatistics and Epidemiology, School of Public Health, Shenzhen University Medical School, Shenzhen, Guangdong, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Previous studies suggest red and processed meat consumption may increase the risk of pancreatic cancer (PC); however, there is no consensus regarding the associations. A systematic review and meta-analysis were therefore performed to explore the relationship between red and processed meats and PC risk. Methods: We searched PubMed, EMBASE, and Web of Science for articles up to April 13, 2026, using random-effects models to calculate relative risks (RRs) and 95% CIs, restricted cubic splines for dose-response relationship, and subgroup/meta-regression for heterogeneity. This systematic review was prospectively registered on PROSPERO (registration number: CRD42022384026; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=384026). Results: Sixteen articles with 1,959,527 participants and 8,856 PC cases were included. There was a 16% increased risk of PC found in the highest versus lowest red meat consumption levels (RR = 1.16, 95% CI: 1.02-1.31). A linear association was observed between red (P non-linear = 0.656) and processed meats (P non-linear = 0.857) and PC risk, with a 10% increase in the risk of PC for each additional 100 g/d of red meat consumption (RR = 1.10, 95% CI: 1.00-1.21). For processed meat products, no significant association with PC risk was found. Conclusion: This finding indicates that increased red meat consumption may elevate the PC risk; therefore, daily red meat intake is recommended to be controlled. No evidence links processed meat to PC risk.

Indexed as

dose–responsemeta-analysispancreatic cancerprocessed meatred meat

Identifiers

PMID42523589
PMCPMC13407104

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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.