ArticleSupportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer2021
A novel model with nutrition-related parameters for predicting overall survival of cancer patients.
Article in Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.
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Who cites it
5 citing papers in PubMed, 1 synthesis or guideline pooled it, 3 citations in OpenAlex.
- Association of patient-generated subjective global assessment (PG-SGA) scores with survival outcomes in cancer patients: A systematic review and meta-analysis.Asia Pacific journal of clinical nutrition · 2026Pooled it
- A nutrition-focused model for predicting postoperative complications in locally advanced gastric cancer after neoadjuvant chemotherapy: a retrospective cohort study.BMC gastroenterology · 2026Article
- Improve the quality of end-of-life in cancer patients using social representations of nutrition.Frontiers in oncology · 2024Article
- ncRNAs-mediated high expression of TICRR promotes tumor cell proliferation and migration and is correlated with poor prognosis and tumor immune infiltration of hepatocellular carcinoma.Molecular therapy. Nucleic acids · 2022Article
- Creation and Validation of a Survival Nomogram Based on Immune-Nutritional Indexes for Colorectal Cancer Patients.Journal of oncology · 2022Article
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Authors and funding
12 authors at 7 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundIncreasing evidence indicates that nutritional status could influence the survival of cancer patients. This study aims to develop and validate a nomogram with nutrition-related parameters for predicting the overall survival of cancer patients. PATIENTS AND
methodsA total of 8749 patients from the multicentre cohort study in China were included as the primary cohort to develop the nomogram, and 696 of these patients were recruited as a validation cohort. Patients' nutritional status were assessed using the PG-SGA. LASSO regression models and Cox regression analysis were used for factor selection and nomogram development. The nomogram was then evaluated for its effectiveness in discrimination, calibration, and clinical usefulness by the C-index, calibration curves, and decision curve analysis. Kaplan-Meier survival curves were used to compare the survival rate.
resultsSeven independent prognostic factors were identified and integrated into the nomogram. The C-index was 0.73 (95% CI, 0.72 to 0.74) and 0.77 (95% CI, 0.74 to 0.81) for the primary cohort and validation cohort, which were both higher than 0.59 (95% CI, 0.58 to 0.61) of the TNM staging system. DCA demonstrated that the nomogram was higher than the TNM staging system and the TNM staging system combined with PG-SGA. Significantly median overall survival differences were found by stratifying patients into different risk groups (score < 18.5 and ≥ 18.5) for each TNM category (all Ps < 0.001).
conclusionOur study screened out seven independent prognostic factors and successfully generated an easy-to-use nomogram, and validated and shown a better predictive validity for the overall survival of cancer patients.
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