A Prospective and Nutrition-Related Nomogram Model for Prognosis in Colorectal Cancer Survival: A Multicenter Cohort Study in China

Abstract

BackgroundColorectal cancer (CRC) is a common malignancy with high incidence of malnutrition. Increasing evidence showed that nutritional status could be a prognostic indicator of cancer survival. However, there were few prognostic models involving nutrition-related indicators in CRC. This study aimed to develop a nutrition-related prognostic model for CRC survival.MethodsThis multicenter retrospectively primary cohort data included 1,373 CRC patients, and the external validation cohort enrolled other 108 CRC patients. LASSO and multivariate regression analyses were used to select prognostic indicators and develop the nomogram. We performed C-index, calibration curves, and DCA to assess the discrimination, calibration, and applicability. Finally, the indicators of the nomogram model were used as adjustment factors. Multivariate Cox survival analyses were performed to investigate the benefit of the Patient-Generated Subjective Global Assessment (PG-SGA) and Global Leadership Initiative on Malnutrition (GLIM) malnutrition criteria to CRC prognosis.ResultsFive prognostic indicators (TNM stage, radical resection, reduced food intake, activities and function decline, and low albumin) were chosen to develop the nomogram. C-index of the nomogram was 0.74 (95% CI 0.72-0.77) and 0.72 (95% CI 0.62-0.81) in the primary cohort and validation cohort, which were higher than other models. Calibration plots and DCA showed that the nomogram model has a good consistency and clinical benefit in predicting CRC survival. Multivariate Cox survival analysis suggested moderate (P<0.05, HR 1.32, 95% CI 1.002-1.75) and severe malnutrition (P<0.001, HR 1.69, 95% CI 1.27-2.25) were associated with worse overall survival (OS) in CRC using the PG-SGA criteria. However, there was no prognostic significance in GLIM criteria (all P>0.05). Finally, stratified analysis suggested that malnourished CRC patients with low albumin synergistically increased the death risk of CRC OS both in PG-SGA and GLIM. (P for interaction = 0.007 and 0.004, respectively)ConclusionThis study established a prospective model to predict the OS in CRC patients using nutrition-related indicators. Moreover, we also found that PG-SGA had a better prognostic and predictive efficiency in CRC than GLIM. These findings grant further verification.