ArticleFrontiers in nutrition2025
A prognostic nutritional index-based nomogram for predicting postoperative survival in stages I-III rectal cancer patients.
Article in Frontiers in nutrition, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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3 citing papers in PubMed.
- Predictive value of NRI, NLR, PLR and LMR for therapeutic efficacy and prognosis in advanced rectal cancer patients treated with PD-1/PD-L1 immunotherapy.Frontiers in surgery · 2026Article
- Association between the prognostic nutritional index and early mortality of AML patients after allogeneic HSCT: a retrospective cohort analysis.Frontiers in oncology · 2026Article
- Association of preoperative prognostic nutritional index with postoperative delirium after gastric cancer surgery.Frontiers in nutrition · 2026Article
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Authors and funding
6 authors.
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Abstract
Introduction: Rectal cancer (RC) is a common malignancy of the digestive system with both high incidence and mortality. Its prognosis is influenced by multiple factors, with nutritional status playing a pivotal role. However, current prognostic models rarely incorporate this factor. Methods: To address this gap, we have developed a novel prognostic nomogram. The newly constructed Prognostic Nutritional Index (PNI)-incorporated nomogram incorporates preoperative pathological tumor-node-metastasis (pTNM) stage, preoperative PNI, preoperative serum carcinoembryonic antigen (CEA) levels, intraoperative blood loss (IBL), and postoperative serum CEA levels. Results: Our analysis showed that preoperative PNI ≤ 47.15, preoperative CEA > 14.13 ng/mL, IBL > 130 mL, postoperative CEA > 4.8 ng/mL, and advanced pTNM stage were independent risk factors for poor survival in patients with stage I-III rectal cancer. Compared with the non-PNI nomograms (combining preoperative CEA, postoperative CEA, pTNM and IBL, but without PNI) and the conventional pTNM staging models, the C-index of the PNI-incorporated nomogram is 0.721, compared to 0.710 for non-PNI nomograms and 0.636 for pTNM staging models, demonstrating improved predictive performance. Furthermore, the PNI-incorporated nomogram achieved AUC values of 0.855, 0.759, and 0.717 for 1, 3, and 5 year overall survival prediction, respectively, in the training set, and 0.952, 0.682, and 0.658 for the corresponding time points in the validation set. Conclusion: This model significantly improves existing prognostic methods and provides clinicians with a more comprehensive and clinically applicable tool for predicting outcomes in patients with RC.
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