Journal of Neuro-Oncology

, Volume 134, Issue 2, pp 423–431 | Cite as

Elderly patients with newly diagnosed glioblastoma: can preoperative imaging descriptors improve the predictive power of a survival model?

  • Mina Park
  • Seung-Koo Lee
  • Jong Hee Chang
  • Seok-Gu Kang
  • Eui Hyun Kim
  • Se Hoon Kim
  • Mi Kyung Song
  • Bo Gyoung Ma
  • Sung Soo AhnEmail author
Clinical Study


The purpose of this study was to identify independent prognostic factors among preoperative imaging features in elderly glioblastoma patients and to evaluate whether these imaging features, in addition to clinical features, could enhance the predictive power of survival models. This retrospective study included 108 patients ≥65 years of age with newly diagnosed glioblastoma. Preoperative clinical features (age and KPS), postoperative clinical features (extent of surgery and postoperative treatment), and preoperative MRI features were assessed. Univariate and multivariate cox proportional hazards regression analyses for overall survival were performed. The integrated area under the receiver operating characteristic curve (iAUC) was calculated to evaluate the added value of imaging features in the survival model. External validation was independently performed with 40 additional patients ≥65 years of age with newly diagnosed glioblastoma. Eloquent area involvement, multifocality, and ependymal involvement on preoperative MRI as well as clinical features including age, preoperative KPS, extent of resection, and postoperative treatment were significantly associated with overall survival on univariate Cox regression. On multivariate analysis, extent of resection and ependymal involvement were independently associated with overall survival and preoperative KPS showed borderline significance. The model with both preoperative clinical and imaging features showed improved prediction of overall survival compared to the model with preoperative clinical features (iAUC, 0.670 vs. 0.600, difference 0.066, 95% CI 0.021–0.121). Analysis of the validation set yielded similar results (iAUC, 0.790 vs. 0.670, difference 0.123, 95% CI 0.021–0.260), externally validating this observation. Preoperative imaging features, including eloquent area involvement, multifocality, and ependymal involvement, in addition to clinical features, can improve the predictive power for overall survival in elderly glioblastoma patients.


Glioblastoma Magnetic resonance imaging Survival analysis Aged Prognosis 



This research was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT & Future Planning (2014R1A1A1002716).

Compliance with ethical standards

Conflict of interest

None of the authors has a financial or personal relationship that could inappropriately influence the contents of this paper.

Supplementary material

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Supplementary material 1 (DOCX 21 KB)
11060_2017_2544_MOESM2_ESM.tif (478 kb)
Supplementary material 2 (TIF 478 KB)
11060_2017_2544_MOESM3_ESM.tif (463 kb)
Supplementary material 3 (TIF 463 KB)


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© Springer Science+Business Media, LLC 2017

Authors and Affiliations

  1. 1.Department of Radiology, Research Institute of Radiological ScienceYonsei University College of MedicineSeoulSouth Korea
  2. 2.Department of Radiology, Konkuk University Medical CenterKonkuk University School of MedicineSeoulSouth Korea
  3. 3.Department of NeurosurgeryYonsei University College of MedicineSeoulSouth Korea
  4. 4.Department of PathologyYonsei University College of MedicineSeoulSouth Korea
  5. 5.Biostatistics Collaboration Unit, Department of Research AffairsYonsei University College of MedicineSeoulSouth Korea

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