Independently validated sex-specific nomograms for predicting survival in patients with newly diagnosed glioblastoma: NRG Oncology RTOG 0525 and 0825

J Neurooncol. 2021 Dec;155(3):363-372. doi: 10.1007/s11060-021-03886-5. Epub 2021 Nov 10.

Abstract

Background/purpose: Glioblastoma (GBM) is the most common primary malignant brain tumor. Sex has been shown to be an important prognostic factor for GBM. The purpose of this study was to develop and independently validate sex-specific nomograms for estimation of individualized GBM survival probabilities using data from 2 independent NRG Oncology clinical trials.

Methods: This analysis included information on 752 (NRG/RTOG 0525) and 599 (NRG/RTOG 0825) patients with newly diagnosed GBM. The Cox proportional hazard models by sex were developed using NRG/RTOG 0525 and significant variables were identified using a backward selection procedure. The final selected models by sex were then independently validated using NRG/RTOG 0825.

Results: Final nomograms were built by sex. Age at diagnosis, KPS, MGMT promoter methylation and location of tumor were common significant predictors of survival for both sexes. For both sexes, tumors in the frontal lobes had significantly better survival than tumors of multiple sites. Extent of resection, and use of corticosteroids were significant predictors of survival for males.

Conclusions: A sex specific nomogram that assesses individualized survival probabilities (6-, 12- and 24-months) for patients with GBM could be more useful than estimation of overall survival as there are factors that differ between males and females. A user friendly online application can be found here- https://npatilshinyappcalculator.shinyapps.io/SexDifferencesInGBM/ .

Keywords: Glioblastoma; Nomogram; Sex differences; Survival.

MeSH terms

  • Brain Neoplasms* / diagnosis
  • Brain Neoplasms* / genetics
  • Brain Neoplasms* / therapy
  • Female
  • Glioblastoma* / diagnosis
  • Glioblastoma* / genetics
  • Glioblastoma* / therapy
  • Humans
  • Male
  • Nomograms
  • Prognosis
  • Promoter Regions, Genetic
  • Proportional Hazards Models