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Published on: September 27, 2024
A perioperative immunonutritional nomogram for survival prediction beyond tumor-node-metastasis classification in
Satoru Furuhashi1,2, Minoru Esaki1, Satoshi Nara1
1Department of Hepatobiliary and Pancreatic Surgery, National Cancer Center Hospital, Tsukiji, Chuo-ku, Tokyo, 104-0045, Japan.
Background:
This multicenter retrospective study aimed to develop and validate a prognostic nomogram incorporating preoperative immunonutritional indices and postoperative pathological factors to predict overall survival (OS) in patients with ampullary adenocarcinoma (AAC) undergoing pancreaticoduodenectomy.
Methods:
We analyzed 102 AAC patients treated at the National Cancer Center Hospital, randomly divided into a pilot (n = 71) and an internal validation cohort (n = 31). Candidate variables were screened using univariate Cox regression (P < .20) and variance inflation factor analysis. A multivariable Cox model was constructed using age, platelet-to-lymphocyte ratio, prognostic nutritional index, lymphatic invasion, and nodal status. The model was visualized as a nomogram to estimate 3- and 5-year OS. Performance was evaluated using the concordance index (C-index), time-dependent receiver operating characteristic curves, and Kaplan-Meier analysis. An independent cohort from Hamamatsu University School of Medicine (n = 25) was used for exploratory external validation.
Results:
The nomogram showed higher area under the curves (AUCs) than tumor-node-metastasis (TNM) classification, with AUCs of 0.742 and 0.792 for 3- and 5-year OS (vs. 0.615 and 0.648 for TNM). The mean C-index was 0.713 in internal validation. Kaplan-Meier analysis demonstrated risk stratification, with a trend toward worse OS in the high-risk group (P = .090). A similar separation was observed in the external cohort. T stage was not a significant predictor.
Conclusions:
This nomogram integrating immunonutritional and pathological factors may improve OS prediction beyond TNM staging in AAC and provide a practical tool for perioperative risk stratification.
