makeitmeta / samples /Outcome-Predictors.txt
Arkadiusz Czerwiński
feat: initial changes
0d3e7f2
From: https://pubs.rsna.org/doi/10.1148/radiol.14131691
Outcome Prediction in Patients with Glioblastoma by Using Imaging, Clinical, and Genomic Biomarkers: Focus on the Nonenhancing Component of the Tumor
Rajan Jain1 , Laila M. Poisson, David Gutman, Lisa Scarpace, Scott N. Hwang, Chad A. Holder, Max Wintermark, Arvind Rao, Rivka R. Colen2, Justin Kirby, John Freymann, C. Carl Jaffe, Tom Mikkelsen, Adam Flanders
Author Affiliations
Published Online:Mar 17 2014https://doi.org/10.1148/radiol.14131691
Abstract
In the current study, we focused on the role of the nonenhancing region (NER) of glioblastomas and showed that there are imaging phenotypic features related specifically to the NER—most notably the NER crossing the midline and relative cerebral blood volume of NER, which provide important prognostic information; these are complementary to clinical and genomic features and can improve models of patient prognosis.
Purpose
To correlate patient survival with morphologic imaging features and hemodynamic parameters obtained from the nonenhancing region (NER) of glioblastoma (GBM), along with clinical and genomic markers.
Materials and Methods
An institutional review board waiver was obtained for this HIPAA-compliant retrospective study. Forty-five patients with GBM underwent baseline imaging with contrast material–enhanced magnetic resonance (MR) imaging and dynamic susceptibility contrast-enhanced T2*-weighted perfusion MR imaging. Molecular and clinical predictors of survival were obtained. Single and multivariable models of overall survival (OS) and progression-free survival (PFS) were explored with Kaplan-Meier estimates, Cox regression, and random survival forests.
Results
Worsening OS (log-rank test, P = .0103) and PFS (log-rank test, P = .0223) were associated with increasing relative cerebral blood volume of NER (rCBVNER), which was higher with deep white matter involvement (t test, P = .0482) and poor NER margin definition (t test, P = .0147). NER crossing the midline was the only morphologic feature of NER associated with poor survival (log-rank test, P = .0125). Preoperative Karnofsky performance score (KPS) and resection extent (n = 30) were clinically significant OS predictors (log-rank test, P = .0176 and P = .0038, respectively). No genomic alterations were associated with survival, except patients with high rCBVNER and wild-type epidermal growth factor receptor (EGFR) mutation had significantly poor survival (log-rank test, P = .0306; area under the receiver operating characteristic curve = 0.62). Combining resection extent with rCBVNER marginally improved prognostic ability (permutation, P = .084). Random forest models of presurgical predictors indicated rCBVNER as the top predictor; also important were KPS, age at diagnosis, and NER crossing the midline. A multivariable model containing rCBVNER, age at diagnosis, and KPS can be used to group patients with more than 1 year of difference in observed median survival (0.49–1.79 years).
Conclusion
Patients with high rCBVNER and NER crossing the midline and those with high rCBVNER and wild-type EGFR mutation showed poor survival. In multivariable survival models, however, rCBVNER provided unique prognostic information that went above and beyond the assessment of all NER imaging features, as well as clinical and genomic features.
© RSNA, 2014
Online supplemental material is available for this article.
Article History
Received August 16, 2013; revision requested September 18; revision received December 20; accepted January 10, 2014; final version accepted January 20.
Published online: Mar 17 2014
Published in print: Aug 2014