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The Association Between Accelerated Biological Aging as Measured by KDMAge and PhenoAge and Digestive System Cancer
Wei Yue Li1, Huan Zhang1, Song Bo Li1
1State Key Laboratory of Holistic Integrative Management of Gastrointestinal Cancers, National Clinical Research Center for Digestive Diseases, Department of Gastroenterology & Hepatology, Xijing Hospital, The Fourth Military Medical University, Xi'an, Shaanxi Province, China.
Objectives:
Digestive system cancer (DSC) continues to pose a significant global health challenge, and cost-effective biomarkers for its early detection remain scarce. We aimed to evaluate the potential of two biological aging indicators, namely the Klemera-Doubal method age (KDMAge) and the phenotypic age (PhenoAge), for predicting DSC risk.
Methods:
Using the National Health and Nutrition Examination Survey (NHANES) dataset (1999-2018), biological age acceleration for KDMAge and PhenoAge was calculated as residuals from linear regression models of each biological age on chronological age. Accelerated aging was defined as positive residuals. Their associations with DSC risk were evaluated using weighted logistic regression and restricted cubic spline (RCS) analysis. Predictive performance was assessed via area under the receiver operating characteristic curve (AUROC), and robustness was examined using propensity score matching (PSM) analysis.
Results:
A significant positive linear association was observed between KDMAge acceleration and DSC risk (odds ratio 1.59, 95% confidence interval 1.05-2.39, p = 0.027). While PhenoAge acceleration showed a U-shaped nonlinear relationship (p = 0.0197), with minimal risk at -2.95. Both indices showed moderate predictive accuracy (AUROC: KDMAge 0.683 and PhenoAge 0.682). PSM analysis confirmed the robustness of the nonlinear relationship between PhenoAge acceleration and DSC, although the linear trend of KDMAge was attenuated after matching.
Conclusion:
There was a significant association between accelerated biological aging, as assessed by KDMAge acceleration and PhenoAge acceleration, and DSC risk. Given the cross-sectional study design, causal inference is precluded; however, both indices may be used to develop novel risk assessment tools and guide future research on interventional strategies.
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