SynthesisFrontiers in oncology2025
Diagnostic performance of the triglyceride-glucose index in predicting occurrence of cancer: a meta-analysis.
Synthesis in Frontiers in oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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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.
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.
Who cites it
2 citing papers in PubMed.
- Association Between Triglyceride-Glucose Index and Risk of Cancer: A Systematic Review and Meta-Analysis.Journal of personalized medicine · 2026Review
- Gender-specific associations of metabolic and circadian syndromes with melanoma risk: insights from NHANES 2007-2018.Scientific reports · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: This meta-analysis aimed to evaluate the diagnostic performance of the triglyceride-glucose (TyG) index in predicting cancer occurrence. Method: A comprehensive literature search was conducted in Embase, Medline, Cochrane Library, and Google Scholar from inception to July 2024. Observational studies reporting the diagnostic efficacy of the TyG index in predicting cancer occurrence using ROC curve analysis were included. Pooled sensitivity, specificity, and area under the summary receiver operating characteristic (SROC) curve were calculated using a bivariate random-effects model. Results: Eleven studies with 46,658 participants were included. Patients with cancer had a significantly higher TyG index than those without cancer (mean difference: 0.34, 95% CI: 0.23-0.45). The pooled sensitivity and specificity of the TyG index for predicting cancer occurrence were 0.68 (95% CI: 0.62-0.74) and 0.65 (95% CI: 0.54-0.74), respectively. The area under the SROC curve was 0.72 (95% CI: 0.68-0.75), indicating good discriminatory ability. Subgroup analysis of female participants yielded similar results, with an AUC of 0.73 (95% CI: 0.69-0.77). Conclusion: The TyG index demonstrates good discriminatory ability and may have potential as an adjunct screening tool to help identify individuals at a higher risk of developing cancer. However, this should be interpreted alongside other established risk factors, as many confounding factors (including cancer type, genetic predisposition, and other malignancy risk factors) must be considered. Further research is needed to establish optimal cut-off values, which likely vary across different cancer types, and to investigate their diagnostic accuracy in diverse populations. Systematic review registration: https://www.crd.york.ac.uk/prospero/, identifier CRD42024573712.
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Registered trials
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 Socratic graph.