Dataset Information

Multimodal imaging patterns predict survival in recurrent glioblastoma patients treated with bevacizumab.

ABSTRACT:

Background

Bevacizumab is a humanized antibody against vascular endothelial growth factor approved for treatment of recurrent glioblastoma. There is a need to discover imaging biomarkers that can aid in the selection of patients who will likely derive the most survival benefit from bevacizumab.

Methods

The aim of the study was to examine if pre- and posttherapy multimodal MRI features could predict progression-free survival and overall survival (OS) for patients with recurrent glioblastoma treated with bevacizumab. The patient population included 84 patients in a training cohort and 42 patients in a testing cohort, separated based on pretherapy imaging date. Tumor volumes of interest were segmented from contrast-enhanced T1-weighted and fluid attenuated inversion recovery images and were used to derive volumetric, shape, texture, parametric, and histogram features. A total of 2293 pretherapy and 9811 posttherapy features were used to generate the model.

Results

Using standard radiographic assessment criteria, the hazard ratio for predicting OS was 3.38 (P < .001). The hazard ratios for pre- and posttherapy features predicting OS were 5.10 (P < .001) and 3.64 (P < .005) for the training and testing cohorts, respectively.

Conclusion

With the use of machine learning techniques to analyze imaging features derived from pre- and posttherapy multimodal MRI, we were able to develop a predictive model for patient OS that could potentially assist clinical decision making.

SUBMITTER: Chang K

PROVIDER: S-EPMC6693191 | biostudies-literature | 2016 Dec

REPOSITORIES: biostudies-literature

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Publications

Multimodal imaging patterns predict survival in recurrent glioblastoma patients treated with bevacizumab.

Chang Ken K Zhang Biqi B Guo Xiaotao X Zong Min M Rahman Rifaquat R Sanchez David D Winder Nicolette N Reardon David A DA Zhao Binsheng B Wen Patrick Y PY Huang Raymond Y RY

Neuro-oncology 20160504 12

<h4>Background</h4>Bevacizumab is a humanized antibody against vascular endothelial growth factor approved for treatment of recurrent glioblastoma. There is a need to discover imaging biomarkers that can aid in the selection of patients who will likely derive the most survival benefit from bevacizumab.<h4>Methods</h4>The aim of the study was to examine if pre- and posttherapy multimodal MRI features could predict progression-free survival and overall survival (OS) for patients with recurrent gli ...[more]

PMID: 27257279

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Project description:BackgroundAnti-angiogenic therapy with bevacizumab is the most widely used treatment option for recurrent glioblastoma, but therapeutic response varies substantially and effective biomarkers for patient selection are not available. To this end, we determine whether novel quantitative radiomic strategies on the basis of MRI have the potential to noninvasively stratify survival and progression in this patient population.MethodsIn an initial cohort of 126 patients, we identified a distinct set of features representative of the radiographic phenotype on baseline (pretreatment) MRI. These selected features were evaluated on a second cohort of 165 patients from the multicenter BRAIN trial with prospectively acquired clinical and imaging data. Features were evaluated in terms of prognostic value for overall survival (OS), progression-free survival (PFS), and progression within 3, 6, and 9 months using baseline imaging and first follow-up imaging at 6 weeks posttreatment initiation.ResultsMultivariable analysis of features derived at baseline imaging resulted in significant stratification of OS (hazard ratio [HR] = 2.5; log-rank P = 0.001) and PFS (HR = 4.5; log-rank P = 2.1 × 10-5) in validation data. These stratifications were stronger compared with clinical or volumetric covariates (permutation test false discovery rate [FDR] <0.05). Univariable analysis of a prognostic textural heterogeneity feature (information correlation) derived from postcontrast T1-weighted imaging revealed significantly higher scores for patients who progressed within 3 months (Wilcoxon test P = 8.8 × 10-8). Generally, features derived from postcontrast T1-weighted imaging yielded higher prognostic power compared with precontrast enhancing T2-weighted imaging.ConclusionRadiomics provides prognostic value for survival and progression in patients with recurrent glioblastoma receiving bevacizumab treatment. These results could lead to the development of quantitative pretreatment biomarkers to predict benefit from bevacizumab using standard of care imaging.

Project description:Background and aimsThis retrospective review of patients with recurrent glioblastoma treated at the Preston Robert Tisch Brain Tumor Center investigated treatment patterns, survival, and safety with bevacizumab in a real-world setting.MethodsAdult patients with glioblastoma who initiated bevacizumab at disease progression between January 1, 2009, and May 14, 2012, were included. A Kaplan-Meier estimator was used to describe overall survival (OS), progression-free survival (PFS), and time to greater than or equal to 20% reduction in Karnofsky Performance Status (KPS). The effect of baseline demographic and clinical factors on survival was examined using a Cox proportional hazards model. Adverse event (AE) data were collected.ResultsSeventy-four patients, with a median age of 59 years, were included in this cohort. Between bevacizumab initiation and first failure, defined as the first disease progression after bevacizumab initiation, biweekly bevacizumab and bevacizumab/irinotecan were the most frequently prescribed regimens. Median duration of bevacizumab treatment until failure was 6.4 months (range, 0.5-58.7). Median OS and PFS from bevacizumab initiation were 11.1 months (95% confidence interval [CI], 7.3-13.4) and 6.4 months (95% CI, 3.9-8.5), respectively. Median time to greater than or equal to 20% reduction in KPS was 29.3 months (95% CI, 13.8-∞). Lack of corticosteroid usage at the start of bevacizumab therapy was associated with both longer OS and PFS, with a median OS of 13.2 months (95% CI, 8.6-16.6) in patients who did not initially require corticosteroids versus 7.2 months (95% CI, 4.8-12.5) in those who did (P = 0.0382, log-rank), while median PFS values were 8.6 months (95% CI, 4.6-9.7) and 3.7 months (95% CI, 2.7-6.6), respectively (P = 0.0243, log-rank). Treatment failure occurred in 70 patients; 47 of whom received salvage therapy, and most frequently bevacizumab/carboplatin (7/47; 14.9%). Thirteen patients (18%) experienced a grade 3 AE of special interest for bevacizumab.ConclusionsTreatment patterns and outcomes for patients with recurrent glioblastoma receiving bevacizumab in a real-world setting were comparable with those reported in prospective clinical trials.

Dataset Information

Multimodal imaging patterns predict survival in recurrent glioblastoma patients treated with bevacizumab.

Background

Methods

Results

Conclusion

Publications

Multimodal imaging patterns predict survival in recurrent glioblastoma patients treated with bevacizumab.

Similar Datasets

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