TY - JOUR
T1 - The Prognostic Impact of Nutritional Status on Postoperative Outcomes in Glioblastoma
AU - Huq, Sakibul
AU - Khalafallah, Adham M.
AU - Botros, David
AU - Oliveira, Leonardo A.P.
AU - White, Taija
AU - Dux, Hayden
AU - Jimenez, Adrian E.
AU - Mukherjee, Debraj
N1 - Funding Information:
Conflict of interest statement: This publication was made possible by the Johns Hopkins Institute for Clinical and Translational Research, which is funded in part by grant number UL1TR003098 from the National Center for Advancing Translational Sciences , a component of the National Institutes of Health, and NIH Roadmap for Medical Research. Its contents are solely the responsibility of the authors and do not necessarily represent the official view of the Johns Hopkins Institute for Clinical and Translational Research, National Center for Advancing Translational Sciences, or National Institutes of Health.
Publisher Copyright:
© 2020 Elsevier Inc.
PY - 2021/2
Y1 - 2021/2
N2 - 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.
AB - 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.
KW - Brain tumor
KW - Glioblastoma
KW - Malnutrition
KW - Nutrition
KW - Oncology
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U2 - 10.1016/j.wneu.2020.11.033
DO - 10.1016/j.wneu.2020.11.033
M3 - Article
C2 - 33197633
AN - SCOPUS:85097762202
VL - 146
SP - e865-e875
JO - World Neurosurgery
JF - World Neurosurgery
SN - 1878-8750
ER -