A Creatinine-CAR Composite Index (CCAR) Optimized by Machine Learning for Prognosis in Cancer Cachexia.

<p><b>BACKGROUND</b></p><p>Cancer cachexia is a multifactorial syndrome associated with poor prognosis and impaired quality of life in cancer patients. However, survival prediction in cancer cachexia remains difficult due to the lack of reliable biomarkers.</p><p><b>METHODS</b></p><p>This retrospective cohort study analysed data from 1,367 patients with cancer cachexia diagnosed according to the 2011 Fearon consensus, using the multicentre INSCOC database.

The cohort was divided into a training set (n = 959), an internal validation set (n = 408), and an independent external validation cohort (n = 284). The mean age of the entire cohort was 58.7 ± 10.9 years, and 39.4% were female.

LASSO regression identified creatinine (Cr) as a key predictor. The CCAR (Cr + CAR) index was then constructed using Cr and CAR within a random forest model.

Prognostic performance was assessed by Harrell's concordance index (C-index), time-dependent AUC, Kaplan-Meier analysis and multivariate Cox regression, with overall survival (OS) as the primary endpoint.</p><p><b>RESULTS</b></p><p>The CCAR index consistently outperformed conventional inflammation- and nutrition-related markers across all three cohorts. The C-index values for CCAR were 0.777 in the training cohort, 0.789 in the internal validation cohort, and 0.765 in the external validation cohort, compared with 0.627-0.660 for CAR ALONE.

Patients in the high-CCAR group had significantly worse OS than those in the low-CCAR group (log-rank p < 0.0001 for all cohorts). Multivariate Cox regression confirmed that CCAR was an independent prognostic factor for OS (HR 3.31, 95% CI 2.94-3.72 in the training set; HR 3.51, 95% CI 2.93-4.22 in the validation set; HR 3.21, 95% CI 2.55-4.03 in the external cohort; all p < 0.001).

A web-based calculator (https://heyangzhang.pythonanywhere.com) was developed for real-time CCAR computation and survival predictions.</p><p><b>CONCLUSION</b></p><p>The CCAR index provides a robust, easily accessible tool for predicting survival outcomes in cancer cachexia patients. The web-based CCAR calculator demonstrates significant clinical applicability and improves patient risk stratification, offering potential for guiding early interventions and personalized treatment strategies in clinical settings.</p>