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

Nutrients. 2018 Jun 13;10(6):765. doi: 10.3390/nu10060765.


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.

Keywords: Geriatric Nutritional Risk Index (GNRI); Glasgow prognostic score (GPS); controlling nutritional (CONUT) score; neutrophil–lymphocyte ratio (NLR); platelet–lymphocyte ratio (PLR); prognosis; soft tissue sarcomas (STS).

Publication types

  • Comparative Study
  • Validation Study

MeSH terms

  • Age Factors
  • Aged
  • Female
  • Geriatric Assessment*
  • Humans
  • Kaplan-Meier Estimate
  • Logistic Models
  • Male
  • Middle Aged
  • Multivariate Analysis
  • Neoplasm Staging
  • Nutrition Assessment*
  • Nutritional Status*
  • Predictive Value of Tests
  • Proportional Hazards Models
  • Reproducibility of Results
  • Retrospective Studies
  • Risk Factors
  • Sarcoma / diagnosis*
  • Sarcoma / mortality
  • Sarcoma / pathology
  • Sarcoma / physiopathology
  • Sex Factors
  • Soft Tissue Neoplasms / diagnosis*
  • Soft Tissue Neoplasms / mortality
  • Soft Tissue Neoplasms / pathology
  • Soft Tissue Neoplasms / physiopathology
  • Time Factors