Scientific Reports (Sep 2024)

Comprehensive analysis of the prognostic value of pre-treatment nutritional indicators in elderly rectal cancer patients

  • Jianjian Qiu,
  • Yilin Yu,
  • Zhiping Wang,
  • Liang Hong,
  • Lingdong Shao,
  • Junxin Wu

DOI
https://doi.org/10.1038/s41598-024-73123-2
Journal volume & issue
Vol. 14, no. 1
pp. 1 – 15

Abstract

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Abstract Nutritional status assessment has been deemed essential in treating elderly cancer patients. This study aims to investigate and compare the prognostic value and clinical utility of pre-treatment nutritional indicators in elderly rectal cancer (RC) patients. We retrospectively collected data from 361 elderly rectal cancer patients. The optimal cut-off values for pre-treatment nutritional indicators were calculated using ROC curve analysis. Univariate and multivariate Cox analyses were conducted to identify independent prognostic nutritional indicators. The predictive performance and clinical utility of these independent nutritional indicators was evaluated using time-dependent ROC. Multivariate analyses showed that body mass index (BMI), prognostic nutritional index (PNI), geriatric nutrition risk index (GNRI), and platelet-albumin ratio (PAR) independently predicted overall survival and progression-free survival in elderly RC patients (all p < 0.05), except for advanced lung cancer inflammation index (ALI). According to the nomogram model, the pre-treatment nutritional prognosis score was calculated and the patients were risk stratified. The KM curve showed that the survival of the high-risk group was significantly worse than that of the low-moderate risk group. Time-dependent ROC indicated that novel nutritional prognostic indicator (NNPI) had the best predictive ability compared with the independent prognostic nutritional indicator. Subgroup analysis also showed that NNPI had prognostic value across different clinical factors and had significant clinical utility. In elderly RC patients, BMI, PNI, GNRI, PAR, and NNPI serve as objective assessment tools for nutrition-related mortality risk. Identifying elderly patients at higher nutritional risk can guide early clinical nutritional interventions and improve patient outcomes.

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