ArticleCancer reports (Hoboken, N.J.)2024
A Prognostic Model Based on Nutritional Indexes for Patients With Pan-Cancer: A Real-World Cohort Study.
Article in Cancer reports (Hoboken, N.J.), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Reply to L Zhang et al.Advances in nutrition (Bethesda, Md.) · 2026Article
- Lumbar centroid level subcutaneous fat volume increased performance of prognostic predictive model in digestive system cancers: a real-world cohort study.Journal of gastrointestinal oncology · 2025Article
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Authors and funding
16 authors.
Funding
Abstract
backgroundThe aim was to identify the nutritional indexes, construct a prognostic model, and develop a nomogram for predicting individual survival probability in pan-cancers.
methodsNutritional indicators, clinicopathological characteristics, and previous major treatment details of the patients were collected. The enrolled patients were randomly divided into training and validation cohorts. Least absolute shrinkage and selection operator (Lasso) regression cross-validation was used to determine the variables to include in the cox regression model. The training cohort was used to build the prediction model, and the validation cohort was used to further verify the discrimination, calibration, and clinical effectiveness of the model.
resultsA total of 2020 patients were included. The median OS was 56.50 months (95% CI, 50.36-62.65 months). In the training cohort of 1425 patients, through Lasso regression cross-validation, 13 characteristics were included in the model. Cox proportional hazards model was developed and visualized as a nomogram. The C-indexes of the model for predicting 1-, 3-, 5-, and 10-year OS were 0.848, 0.826, 0.814, and 0.799 in the training cohort and 0.851, 0.819, 0.814, and 0.801 in the validation cohort. The model showed great calibration in the two cohorts. Patients with a score of less than 274.29 had a better prognosis (training cohort: HR, 6.932; 95% CI, 5.723-8.397; log-rank p < 0.001; validation cohort: HR, 8.429; 95% CI, 6.180-11.497; log-rank p < 0.001).
conclusionThe prognostic model based on the nutritional indexes of pan-cancer can divide patients into different survival risk groups and performed well in the validation cohort.
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