Aikaterini Kotrotsou1,2, Ahmed Elakkad1, Jia Sun3, Ginu A Thomas1, Dongni Yang4, Srishti Abrol1, Wei Wei3, Jeffrey S Weinberg5, Ali S Bakhtiari1, Moritz F Kircher6, Markus M Luedi1,7, John F de Groot8, Raymond Sawaya5, Ashok J Kumar1, Pascal O Zinn5,9,10, Rivka R Colen11,12. 1. Department of Diagnostic Radiology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA. 2. Department of Cancer Systems Imaging, The University of Texas MD Anderson Cancer Center, 1881 East Road, Houston, 77054, TX, USA. 3. Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA. 4. Department of Diagnostic Interventional and Imaging, The University of Texas Health Science Center, Houston, TX, USA. 5. Department of Neurosurgery, The University of Texas MD Anderson Cancer Center, Houston, TX, USA. 6. Department of Radiology, Memorial Sloan-Kettering Cancer Center, New York, NY, USA. 7. Department of Anesthesiology, Bern University Hospital Inselspital, University of Bern, Bern, Switzerland. 8. Department of Neuro-Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA. 9. Department of Neurosurgery, Baylor College of Medicine, Houston, TX, USA. 10. Department of Cancer Biology, Division of Basic Science Research, The University of Texas MD Anderson Cancer Center, Houston, TX, USA. 11. Department of Diagnostic Radiology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA. rcolen@mdanderson.org. 12. Department of Cancer Systems Imaging, The University of Texas MD Anderson Cancer Center, 1881 East Road, Houston, 77054, TX, USA. rcolen@mdanderson.org.
Abstract
INTRODUCTION: The aim of the present study is to assess whether postoperative residual non-enhancing volume (PRNV) is correlated and predictive of overall survival (OS) in glioblastoma (GBM) patients. METHODS: We retrospectively analyzed a total 134 GBM patients obtained from The University of Texas MD Anderson Cancer Center (training cohort, n = 97) and The Cancer Genome Atlas (validation cohort, n = 37). All patients had undergone postoperative magnetic resonance imaging immediately after surgery. We evaluated the survival outcomes with regard to PRNV. The role of possible prognostic factors that may affect survival after resection, including age, sex, preoperative Karnofsky performance status, postoperative nodular enhancement, surgically induced enhancement, and postoperative necrosis, was investigated using univariate and multivariate Cox proportional hazards regression analyses. Additionally, a recursive partitioning analysis (RPA) was used to identify prognostic groups. RESULTS: Our analyses revealed that a high PRNV (HR 1.051; p-corrected = 0.046) and old age (HR 1.031; p-corrected = 0.006) were independent predictors of overall survival. This trend was also observed in the validation cohort (higher PRNV: HR 1.127, p-corrected = 0.002; older age: HR 1.034, p-corrected = 0.022). RPA analysis identified two prognostic risk groups: low-risk group (PRNV < 70.2 cm3; n = 55) and high-risk group (PRNV ≥ 70.2 cm3; n = 42). GBM patients with low PRNV had a significant survival benefit (5.6 months; p = 0.0037). CONCLUSION: Our results demonstrate that high PRNV is associated with poor OS. Such results could be of great importance in a clinical setting, particularly in the postoperative management and monitoring of therapy.
INTRODUCTION: The aim of the present study is to assess whether postoperative residual non-enhancing volume (PRNV) is correlated and predictive of overall survival (OS) in glioblastoma (GBM) patients. METHODS: We retrospectively analyzed a total 134 GBM patients obtained from The University of Texas MD Anderson Cancer Center (training cohort, n = 97) and The Cancer Genome Atlas (validation cohort, n = 37). All patients had undergone postoperative magnetic resonance imaging immediately after surgery. We evaluated the survival outcomes with regard to PRNV. The role of possible prognostic factors that may affect survival after resection, including age, sex, preoperative Karnofsky performance status, postoperative nodular enhancement, surgically induced enhancement, and postoperative necrosis, was investigated using univariate and multivariate Cox proportional hazards regression analyses. Additionally, a recursive partitioning analysis (RPA) was used to identify prognostic groups. RESULTS: Our analyses revealed that a high PRNV (HR 1.051; p-corrected = 0.046) and old age (HR 1.031; p-corrected = 0.006) were independent predictors of overall survival. This trend was also observed in the validation cohort (higher PRNV: HR 1.127, p-corrected = 0.002; older age: HR 1.034, p-corrected = 0.022). RPA analysis identified two prognostic risk groups: low-risk group (PRNV < 70.2 cm3; n = 55) and high-risk group (PRNV ≥ 70.2 cm3; n = 42). GBM patients with low PRNV had a significant survival benefit (5.6 months; p = 0.0037). CONCLUSION: Our results demonstrate that high PRNV is associated with poor OS. Such results could be of great importance in a clinical setting, particularly in the postoperative management and monitoring of therapy.
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