The Predictive Power of the Cystatin C-Creatinine Score in Assessing Frailty

Abstract

Background: As the global population ages, identifying reliable biomarkers to predict frailty and mortality is critical for early intervention. This study aims to construct a valuable biomarker and evaluate its predictive performance in assessing frailty and all-cause mortality. Methods: Data from 3613 participants in the Health and Retirement Study (HRS) were used to construct the nomogram and main analysis, whereas data from the National Health and Nutrition Examination Survey were used to validate the robustness of the model. LASSO regression identified key biomarkers, and a nomogram was used to construct the score. The frailty index (FI) and all-cause mortality were used as the outcomes, and the score's predictive ability was evaluated using ROC curves, C-index and decision curve analysis. Subgroup analyses were conducted to assess the score's consistency across age, sex and clinical conditions. Results: Sixteen haematological markers were selected through LASSO regression. The nomogram demonstrated that a scoring model based on cystatin C and creatinine can achieve optimal predictive performance. The Cystatin C-Creatinine Score demonstrated strong predictive power for frailty (AUC = 0.687) and all-cause mortality (AUC = 0.733). Logistic regression analysis showed a significant association between higher Cystatin C-Creatinine Scores and increased frailty risk, with participants in the high-risk group having an OR of 1.48 (95% CI: 1.35–1.62, p < 0.001) compared to the low-risk group. Cox proportional hazards models also indicated that higher scores were associated with increased mortality risk (HR = 3.34, 95% CI: 1.75–6.38, p < 0.001 for the high-risk group). In the validation set, the AUC values of the Cystatin C-Creatinine Score for predicting frailty and all-cause mortality reached 0.701 and 0.713, respectively. Conclusion: Our findings support the use of the Cystatin C-Creatinine Score as a practical and effective tool for identifying individuals at higher risk of frailty and mortality.