A cardiometabolic risk phenotype index integrating insulin resistance, systemic inflammation, and psychological burden for mortality risk stratification in metabolic dysfunction-associated steatotic liver disease: an exploratory longitudinal analysis of a nationally representative cohort.

Abstract

Background: Metabolic dysfunction-associated steatotic liver disease (MASLD) is being increasingly recognized as a systemic cardiometabolic disorder rather than a liver-limited condition. However, the combined association of insulin resistance, systemic inflammation, and depressive symptoms with mortality remains unclear. Therefore, we developed an insulin resistance-systemic inflammation-psychological burden (ISP) index to evaluate its associations with all-cause mortality (ACM) and cardiovascular mortality (CVM).

Methods: We analyzed data from 3,187 adults with MASLD in the 2005-2018 National Health and Nutrition Examination Survey. A random forest model based on mean decrease in accuracy was used to select representative markers from six insulin resistance surrogates and five systemic inflammation indices, which were combined with the PHQ-9 score to construct the ISP index. Weighted Kaplan-Meier and Cox analyses, restricted cubic splines, subgroup and sensitivity analyses, and interpretable machine learning with 5-fold cross-validation were performed.

Results: During a median 8.25-year follow-up, 382 deaths occurred, including 114 cardiovascular deaths. The metabolic score for insulin resistance (METS-IR) and systemic inflammation response index (SIRI) were selected and combined with the PHQ-9 score to construct the ISP index. In fully adjusted Cox models, the highest ISP tertile was associated with higher risks of both ACM (HR = 1.63, 95% CI: 1.12-2.38) and CVM (HR = 2.88, 95% CI: 1.36‒6.10) compared with the lowest tertile. Eight ISP-based machine-learning models were internally evaluated using 5-fold cross-validation, with the GBM model yielding 10-year AUCs of 0.869 for ACM and 0.883 for CVM. SHAP analysis of the GBM model revealed that the ISP index ranked second in feature importance after age.

Conclusions: The ISP index was positively associated with the risks of ACM and CVM among individuals with MASLD. However, because the ISP index was constructed and internally evaluated within the same sample, its apparent predictive performance may be optimistic owing to overfitting. Therefore, the ISP index requires external validation in larger, independent prospective cohorts.