TyG-ABSI en TyG-WWI als metabole risicomarkers voor sterfte — multi-cohortobservatiestudie
Een multi-cohortobservatiestudie onder meer dan 37.000 volwassenen van 50 jaar en ouder onderzocht de voorspellende waarde van TyG-gerelateerde indices (combinaties van triglyceriden, glucose en anthropometrie) voor all-cause sterfte binnen het cardiorenale-metabole (CKM)-kader. TyG-ABSI en TyG-WWI toonden de sterkste en meest consistente associaties met sterfte over verschillende internationale cohorts, maar toevoeging aan bestaande klinische voorspellingsmodellen leverde slechts een minimaal verbeterde discriminatie op. De bevindingen suggereren dat deze indices vooral bruikbaar zijn als laagdrempelige, interpretable risicomarkers in plaats van als standalone voorspellingsinstrumenten voor de dagelijkse klinische praktijk.
Abstract (original)
Insulin resistance, adiposity, kidney dysfunction, and cardiovascular disease are closely interconnected in middle-aged and older adults and are central to the cardiovascular-kidney-metabolic (CKM) framework. Triglyceride-glucose (TyG)-related indices combine routine lipid, glucose, and anthropometric information, but their cross-population consistency and incremental prognostic value for mortality-risk assessment remain uncertain. We analyzed harmonized participant-level data from National Health and Nutrition Examination Survey (NHANES), English Longitudinal Study of Ageing (ELSA), China Health and Retirement Longitudinal Study (CHARLS), and Health and Retirement Study (HRS), with HRS used as a sensitivity cohort. Eligible participants were aged ≥ 50 years, had follow-up beyond baseline, available mortality status, and complete data for 7 TyG-related indices. Cohort-specific Cox models estimated associations of standardized TyG, TyG-body mass index, TyG-waist circumference, TyG-waist-to-height ratio, TyG-weight-adjusted waist index (WWI), TyG-a body shape index (ABSI), and TyG-body roundness index with all-cause mortality. Nonlinearity, proportional-hazards assumptions, sensitivity analyses, NHANES heart disease mortality, incremental prediction, and survival machine learning with external validation were further assessed. The primary analytic sample included 21,044 NHANES participants, 5454 ELSA participants, and 11,157 CHARLS participants, among whom 5566, 116, and 1393 deaths occurred during follow-up, respectively. The HRS sensitivity cohort included 4103 participants and 484 deaths. In fully adjusted Cox models, all 7 TyG-related indices were associated with higher all-cause mortality in NHANES, with the strongest associations observed for TyG-ABSI (hazard ratio [HR] 1.159, 95% confidence interval [CI] 1.115-1.205) and TyG-WWI (HR 1.155, 95% CI 1.113-1.199). In CHARLS, TyG-ABSI was positively associated with mortality (HR 1.088, 95% CI 1.029-1.151), whereas estimates in ELSA were imprecise. In HRS sensitivity analyses, TyG-WWI and TyG-ABSI remained positively associated with mortality. Adding TyG-related indices to a clinical Cox prediction framework produced only minimal absolute gains in discrimination. The final TyG-ABSI extreme gradient boosting survival model yielded 5-year time-dependent area under the curves of 0.808 in the NHANES internal test set and 0.760 in CHARLS. A research-use web calculator was developed for 5-year and 8-year mortality-risk estimation. TyG-ABSI and TyG-WWI were the most consistent TyG-related body shape markers of all-cause mortality across international aging cohorts. Although TyG-ABSI supported externally validated survival prediction, its incremental predictive value beyond established clinical and CKM variables was limited. These findings suggest that TyG-related body shape indices may serve primarily as interpretable, low-cost CKM risk markers rather than standalone prediction tools.
Dit artikel is een samenvatting van een publicatie in Medicine. Voor het volledige artikel, alle details en referenties verwijzen wij u naar de oorspronkelijke bron.
Lees het volledige artikelDOI: 10.1097/MD.0000000000051089
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