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 PMID:29899304  

Validation of Different Nutritional Assessment Tools in Predicting Prognosis of Patients with Soft Tissue Spindle-Cell Sarcomas.

Hiromi Sasaki | Satoshi Nagano | Setsuro Komiya | Noboru Taniguchi | Takao Setoguchi
Nutrients | 2018

Predicting outcomes in patients with soft tissue sarcoma (STS) is challenging. To improve these predictions, we retrospectively analyzed common nutritional assessment systems, including Glasgow prognostic score (GPS), Geriatric Nutritional Risk Index (GNRI), neutrophil⁻lymphocyte ratio (NLR), platelet⁻lymphocyte ratio (PLR), and controlling nutritional (CONUT) score against outcomes in 103 patients with STS, of whom 15 (14.6%) died within 1 year of diagnosis. GPS, GNRI, NLR, PLR, and CONUT scores significantly differed between patients who died within one year and patients who lived longer. Binomial logistic regression analysis showed that male sex, older age at diagnosis, higher GPS, higher stage, and unresectable STS were risk factors for death within a year of diagnosis. Overall survival was evaluated by Cox proportional hazards models, which correlated higher NLR, higher PLR, larger maximum diameter of tumor, higher stage, and unresectable STS with poor prognosis. We next examined prognostic factors in the 93 patients with resectable STS, and found male sex, higher GPS, and higher stage were correlated with poor prognosis in these patients. Our findings suggest that GPS, NLR, and PLR are simple predictors of outcome in patients with STS. Nutritional therapies might improve their GPS and prognosis.

Pubmed ID: 29899304

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FISHER (tool)

RRID:SCR_009181

THIS RESOURCE IS NO LONGER IN SERVICE, documented on February 1st, 2022. Software application for genetic analysis of classical biometric traits like blood pressure or height that are caused by a combination of polygenic inheritance and complex environmental forces. (entry from Genetic Analysis Software)

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