Preoperative peripheral blood lymphocyte subsets integrated with geriatric nutritional risk index for prognostic assessment in elderly colorectal carcinoma patients.

[BACKGROUND] Prognosis in elderly colorectal cancer (CRC) patients is generally poor, predominantly attributable to the interrelated phenomena of immunosenescence and malnutrition. Current prognostic assessment tools typically evaluate nutritional and immune status in isolation, potentially overlooking the synergistic effects of these interconnected factors on patient outcomes. Therefore, this investigation aims to establish a comprehensive immuno-nutritional biomarker, integrating lymphocyte subset profiles and the Geriatric Nutritional Risk Index (GNRI), to prognosticate postoperative outcomes in elderly CRC patients.

[METHODS] A retrospective cohort of 201 elderly CRC patients undergoing curative resection at our institution between October 2018 and July 2020 was analyzed. Immunological and nutritional parameters were selected via least absolute shrinkage and selection operator (LASSO) regression to formulate a novel composite biomarker, designated as lymphocyte subsets-GNRI (LS-GNRI). Survival analyses employing Kaplan-Meier estimators and Cox proportional hazards models assessed the correlation of LS-GNRI with overall survival (OS) and disease-free survival (DFS). A prognostic nomogram integrating LS-GNRI and variables identified through multivariate Cox regression was constructed, with predictive accuracy and practicality evaluated via area under the curve (AUC), calibration plots (CAL), decision curve analysis (DCA), and clinical impact curves (CIC).

[RESULTS] Results indicated that the LS-GNRI biomarker demonstrated independent prognostic significance for elderly CRC patients [hazard ratio (HR): 0.323, 95% confidence interval (CI): 0.217-0.480, P<0.001]. Patients with elevated LS-GNRI exhibited significantly improved OS and DFS, with AUCs for 1-, 3-, and 5-year survival predictions of 0.763, 0.82, and 0.753, respectively. The nomogram incorporating LS-GNRI, age, carcinoembryonic antigen (CEA), tumor staging, gene and gene exhibited high predictive performance (AUC: 0.872, 95% CI: 0.807-0.936) and demonstrated clinical utility.

[CONCLUSIONS] In conclusion, LS-GNRI constitutes a robust composite biomarker for postoperative prognostication in elderly CRC patients. Furthermore, a prognostic nomogram incorporating LS-GNRI, patient age, CEA levels, tumor staging, gene and gene enhances the accuracy of survival prognostication in elderly individuals diagnosed with CRC.