ArticleThe Journal of international medical research2026
Multivariate adaptive regression spline modeling for estimating carotid artery plaque thickness in Chinese men with type 2 diabetes.
Article in The Journal of international medical research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
ObjectiveThe incidence of type 2 diabetes continues to increase worldwide, with cardiovascular disease as the leading cause of mortality in this population. Carotid artery plaque thickness serves as a non-invasive marker of atherosclerosis. This study applied multivariate adaptive regression spline analysis to estimate artery plaque thickness using routinely available clinical data in Chinese men with type 2 diabetes.MethodsIn this retrospective cross-sectional study, 648 male patients with type 2 diabetes were analyzed using demographic and biochemical data. Multiple linear regression analysis served as a benchmark comparison. Model performance was evaluated using repeated train-test splits, with hyperparameter tuning conducted exclusively on training data, followed by bootstrap-corrected internal validation. An estimation equation was constructed based on basis functions derived from multivariate adaptive regression spline analysis.ResultsMean participant age was 63.16 ± 11.78 years, mean diabetes duration was 12.26 ± 7.15 years, mean glycosylated hemoglobin level was 7.76 ± 1.66%, and mean artery plaque thickness was 0.943 ± 0.38 mm. Multivariate adaptive regression spline demonstrated lower prediction errors than multiple linear regression across multiple metrics. Five key predictors were identified, including age, diabetes duration, low-density lipoprotein cholesterol level, microalbumin-to-creatinine ratio, and diastolic blood pressure, each with clinically meaningful threshold effects.ConclusionsA multivariate adaptive regression spline-based equation incorporating five routinely available clinical variables was developed for estimating arterial plaque thickness. Although multivariate adaptive regression spline outperformed multiple linear regression, the model's modest explanatory power (R
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