Evidence map›Paper›PMID 42500127›Full record

ArticleFrontiers in endocrinology2026

Association of four non-insulin-based insulin resistance surrogate markers with colorectal cancer risk: a large-scale prospective cohort study using the UK Biobank.

Ye Ding, Jie Wang, Nan Wang, Jinyu Zhu, Xiaoxiao Wang, Peibei Duan

Abstract read
In one paragraph

Article in Frontiers in endocrinology, 2026. 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

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

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3 · Its place in the literature

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0 citing papers in PubMed.

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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

6 authors.

Ye Ding *School of Nursing, Nanjing University of Chinese Medicine, Nanjing, China.
Jie Wang *Department of Endocrinology, Jiangsu Province Hospital of Chinese Medicine, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, China.
Nan WangSchool of Nursing, Nanjing University of Chinese Medicine, Nanjing, China.
Jinyu ZhuSchool of Nursing, Nanjing University of Chinese Medicine, Nanjing, China.
Xiaoxiao WangClinical Research Institute, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, China.
Peibei DuanSchool of Nursing, Nanjing University of Chinese Medicine, Nanjing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Colorectal cancer (CRC) remains a persistent global health challenge, with a rising incidence strongly linked to metabolic dysfunction. Insulin resistance (IR), a hallmark of metabolic dysregulation, is a well-established driver of tumorigenesis and cancer progression. However, the relative predictive value of distinct non-insulin-based surrogate markers of IR for CRC risk assessment remains poorly defined. Methods: This prospective study analyzed data from 385,206 participants in the UK Biobank. Non-insulin-based surrogate markers evaluated included the TyG index, TyG-BMI, the TG/HDL-C ratio, and METS-IR. Cox proportional hazards models estimated hazard ratios (HRs) and 95% confidence intervals (CIs) for incident CRC. Restricted cubic splines (RCS) assessed dose-response relationships. Incremental predictive value and clinical utility were evaluated via C-index increments and decision curve analysis (DCA). Robustness was verified through extensive subgroup and sensitivity analyses. Results: Over a median follow-up of 13.8 years, 5,175 incident CRC cases were documented. All four IR surrogates were independently and positively associated with CRC risk (all Conclusions: Elevated non-insulin-based IR surrogates are robust predictors of CRC risk. The BMI-integrated indices, METS-IR and TyG-BMI, demonstrated superior risk stratification performance. These low-cost, readily available tools may facilitate the early identification of high-risk individuals and inform evidence-based primary prevention strategies.

Indexed as

BiomarkersColorectal NeoplasmsInsulin ResistanceAgedBiological Specimen BanksBody Mass IndexFemaleHumansMaleMiddle AgedProspective StudiesRisk AssessmentRisk FactorsUK BiobankUnited KingdomBiomarkerscolorectal cancerdecision curve analysisinsulin resistanceMETS-IRrisk predictionsurrogate markersTyG-BMI

Identifiers

PMID42500127
PMCPMC13395652

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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.