Journal
WORLD NEUROSURGERY
Volume 146, Issue -, Pages E865-E875Publisher
ELSEVIER SCIENCE INC
DOI: 10.1016/j.wneu.2020.11.033
Keywords
Brain tumor; Glioblastoma; Malnutrition; Nutrition; Oncology
Categories
Funding
- National Center for Advancing Translational Sciences, a component of the National Institutes of Health [UL1TR003098]
- NIH Roadmap for Medical Research
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The study found that nutritional status assessed by PNI predicts postoperative survival in glioblastoma patients, suggesting the importance of nutritional assessment in brain tumor management.
OBJECTIVE: The clinical impact and optimal method of assessing nutritional status (NS) have not been rigorously examined in glioblastoma. We investigated the relationship between NS and postoperative survival (PS) in glioblastoma using 4 nutritional indices and identified which index best modeled PS. METHODS: NS was retrospectively assessed for patients with glioblastoma undergoing surgery at our institution from 2007 to 2019 using the albumin level, albumin/globulin ratio (AGR), nutritional risk index (NRI), and prognostic nutritional index (PNI). Optimal cut points for each index were identified using maximally selected rank statistics and previously established criteria. The predictive value of each index on PS was determined using Cox proportional hazards models adjusted for prognostic variables. The best-performing model was identified using the Akaike Information Criterion. RESULTS: Our analysis included 242 patients (64% male) with a mean age of 57.6 years, Karnofsky Performance Status of 77.6, 5-factor modified frailty index of 0.59, albumin level of 4.2 g/dL, AGR of 1.9, NRI of 105.6, and PNI of 47.4. Median PS after index and repeat surgery was 12.7 and 7.8 months, respectively. On multivariable analysis, low albumin level (hazard ratio [HR], 2.09; 95% confidence interval [CI], 1.52-2.89; P < 0.001), mild NRI (HR, 1.61; 95% CI, 1.04-2.49; P = 0.032), moderate/severe NRI (HR, 2.51; 95% CI, 1.64-3.85; P < 0.001), and low PNI (HR, 2.51; 95% CI, 1.78-3.53; P < 0.001), but not low AGR (HR, 1.17; 95% CI, 0.89-1.54; P = 0.270), predicted decreased PS. PNI had the lowest Akaike Information Criterion. CONCLUSIONS: NS predicts PS in glioblastoma. PNI may provide the best model for assessing NS. NS is an important modifiable aspect of brain tumor management that warrants increased attention.
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