TyG-WHtR Predicts Incident Type 2 Diabetes in NAFLD: A 12-Year Prospective Cohort Study

A 12-year prospective cohort study of 2,370 Japanese patients with nonalcoholic fatty liver disease (NAFLD) evaluates the predictive ability of twelve metabolic composite indices for incident type 2 diabetes mellitus. The dataset, authored by Nan’nan Chen and last updated in 2026, likely contains patient-level clinical and outcome data used to calculate indices like TyG-WC, TyG-WHtR, and VAI. Results indicate the TyG-WHtR index had the highest predictive accuracy for diabetes onset in this population.

Use Cases

• Comparing predictive performance of metabolic composite indices for type 2 diabetes based on hazard ratios and AUC values.
• Developing risk stratification tools for NAFLD patients based on the TyG-WHtR index and its optimal cut-off of 4.54.
• Conducting subgroup analyses to assess the consistency of predictor associations across patient demographics.
• Validating linear associations between metabolic indices and diabetes risk using restricted cubic spline regression methods.

Strengths

• Prospective cohort design with a 12-year follow-up period provides longitudinal data.
• Analysis includes 2,370 NAFLD patients, a substantial sample size for a clinical study.
• Evaluates twelve distinct metabolic composite indices, allowing for comparative performance assessment.
• Results include specific hazard ratios, confidence intervals, and AUC values for model validation.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment for large-scale ML tasks.
• The dataset is very small (15.8 KB), suggesting it may contain only summary results or a limited subset of the full study data.

Provenance

Source

figshare

Collection Method

Secondary analysis of a prospective Japanese cohort study.

Time Range

12-year prospective study (specific years not provided).

Freshness

Last updated 2026-05-01 04:16:26; freshness should be verified.

Geography

Japanese cohort.