Development and internal validation of a routine metabolic screening model for current hyperuricemia among gas station workers in Guangxi, China: a cross-sectional study

Abstract

Abstract Background Serum uric acid (SUA) measurement is the direct basis for identifying current hyperuricemia (HUA). We developed a non-SUA screening model for situations in which routine occupational health information is already available but a contemporaneous SUA result is temporarily unavailable, delayed, or requires separate testing. Methods This cross-sectional study included 894 workers from 11 gas stations and related operational sites in Nanning, Guangxi, China. Current HUA was defined as same-examination SUA > 420 µmol/L in both sexes. Twelve prespecified non-SUA candidate variables were considered; total cholesterol was excluded because of high redundancy and multicollinearity with LDL-C, leaving 11 candidates for least absolute shrinkage and selection operator (LASSO) screening. Internal validation used 100 repetitions of site-grouped five-fold cross-validation. Model performance was assessed using out-of-fold (OOF) predictions, discrimination, calibration, decision curve analysis, candidate screening thresholds, and bootstrap optimism correction. Results Among 894 participants, 169 (18.9%) had current HUA. Sex, waist circumference, triglycerides (TG), systolic blood pressure (SBP), and fasting blood glucose (FBG) met the prespecified selection-stability threshold and comprised the final model. The mean area under the receiver operating characteristic curve (AUC) across repeated site-grouped cross-validation was 0.858 (SD 0.004), and the pooled OOF AUC was 0.866 (95% CI, 0.838–0.893). The pooled OOF Brier score was 0.108, the calibration intercept was − 0.064 (95% CI, -0.322 to 0.192), and the calibration slope was 0.920 (95% CI, 0.791–1.077). At a 10% candidate probability threshold, sensitivity was 92.9%, specificity was 64.6%, and the negative predictive value was 97.5%. Conclusions The five-variable model estimates the probability of current HUA and may support prioritization of confirmatory SUA testing when a contemporaneous SUA result is unavailable. It does not replace direct SUA measurement or predict future incident HUA. Independent external validation is required before broader implementation.

The authors' abstract, as published at the source. BMC Public Health, 2026 · DOI ↗