Evidence map›Paper›PMID 37138277›Full record

ArticleJournal of translational medicine2023

Assessing temporal differences in the predictive power of baseline TyG-related parameters for future diabetes: an analysis using time-dependent receiver operating characteristics.

Maobin Kuang, Ruijuan Yang, Xin Huang, Chao Wang, Guotai Sheng, Guobo Xie, Yang Zou

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Article in Journal of translational medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 49 papers, 1 of them a synthesis that pooled it.

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49citing papers in PubMed, 1 pooled it
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1 · What the graph read from it

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3 · Its place in the literature

Who cites it

49 citing papers in PubMed, 1 synthesis or guideline pooled it.

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  5. Association between the triglycerideZhong nan da xue xue bao. Yi xue ban = Journal of Central South University. Medical sciences · 2026
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5 · Who and what money

Authors and funding

7 authors.

Maobin KuangMedical College of Nanchang University, Nanchang, 330006, Jiangxi, China.
Ruijuan YangMedical College of Nanchang University, Nanchang, 330006, Jiangxi, China.
Xin HuangMedical College of Nanchang University, Nanchang, 330006, Jiangxi, China.
Chao WangMedical College of Nanchang University, Nanchang, 330006, Jiangxi, China.
Guotai ShengDepartment of Cardiology, Jiangxi Provincial People's Hospital, The First Affiliated Hospital of Nanchang Medical College, Nanchang, 330006, Jiangxi, China.
Guobo XieDepartment of Cardiology, Jiangxi Provincial People's Hospital, The First Affiliated Hospital of Nanchang Medical College, Nanchang, 330006, Jiangxi, China. xgb19810830@163.com.
Yang ZouJiangxi Cardiovascular Research Institute, Jiangxi Provincial People's Hospital, The First Affiliated Hospital of Nanchang Medical College, Nanchang, 330006, Jiangxi, China. jxyxyzy@163.com.ORCID 0000-0002-9373-928X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIt is known that measuring the triglyceride glucose (TyG) index and TyG-related parameters [triglyceride glucose-body mass index (TyG-BMI), triglyceride glucose-waist circumference (TyG-WC), and triglyceride glucose-waist to height ratio (TyG-WHtR)] can predict diabetes; this study aimed to compare the predictive value of the baseline TyG index and TyG-related parameters for the onset of diabetes at different future periods.

methodsWe conducted a longitudinal cohort study involving 15,464 Japanese people who had undergone health physical examinations. The subject's TyG index and TyG-related parameters were measured at the first physical examination, and diabetes was defined according to the American Diabetes Association criteria. Multivariate Cox regression models and time-dependent receiver operating characteristic (ROC) curves were constructed to examine and compare the risk assessment/predictive value of the TyG index and TyG-related parameters for the onset of diabetes in different future periods.

resultsThe mean follow-up period of the current study cohort was 6.13 years, with a maximum of 13 years, and the incidence density of diabetes was 39.88/10,000 person-years. In multivariate Cox regression models with standardized hazard ratios (HRs), we found that both the TyG index and TyG-related parameters were significantly and positively associated with diabetes risk and that the TyG-related parameters were stronger in assessing diabetes risk than the TyG index, with TyG-WC being the best parameter (HR per SD increase: 1.70, 95% CI 1.46, 1.97). In addition, TyG-WC also showed the highest predictive accuracy in time-dependent ROC analysis for diabetes occurring in the short-term (2-6 years), while TyG-WHtR had the highest predictive accuracy and the most stable predictive threshold for predicting the onset of diabetes in the medium- to long-term (6-12 years).

conclusionsThese results suggest that the TyG index combined with BMI, WC, and WHtR can further improve its ability to assess/predict the risk of diabetes in different future periods, where TyG-WC was not only the best parameter for assessing diabetes risk but also the best risk marker for predicting future diabetes in the short-term, while TyG-WHtR may be more suitable for predicting future diabetes in the medium- to long-term.

Indexed as

Diabetes Mellitus, Type 2GlucoseBody Mass IndexHumansLongitudinal StudiesRisk FactorsROC CurveTriglyceridesGlucoseTriglyceridesDiabetesPredictionTime-dependent ROC analysisTyG indexTyG-related parameters

Identifiers

PMID37138277
PMCPMC10158224

What Socratic holds

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LicenceCC BY
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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 Socratic graph.