Lauren E. Abrey

Medicine · Health Sciences

82h-index25.9kcitations343works0.02yr avg
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Research Topics

Glioma Diagnosis and Treatment(250), Brain Metastases and Treatment(122), CNS Lymphoma Diagnosis and Treatment(104), Lymphoma Diagnosis and Treatment(67), Radiomics and Machine Learning in Medical Imaging(50)

Publications335 total

Supplementary Data 1 from Depth of Radiographic Response and Time to Tumor Regrowth Predicts Overall Survival Following Anti-VEGF Therapy in Recurrent Glioblastoma
2025Open Access
Supplemental Figure S1 from Depth of Radiographic Response and Time to Tumor Regrowth Predicts Overall Survival Following Anti-VEGF Therapy in Recurrent Glioblastoma
2025Open Access
Supplemental Figure S2 from Depth of Radiographic Response and Time to Tumor Regrowth Predicts Overall Survival Following Anti-VEGF Therapy in Recurrent Glioblastoma
2025Open Access
NIMG-72. VOXEL-WISE, MULTIVARIABLE, COX PROPORTIONAL HAZARD STATISTICAL PARAMETER MAPPING TO INVESTIGATE THE INTERPLAY BETWEEN TUMOR LOCATION, PROGNOSTIC VARIABLES, AND EXPERIMENTAL TREATMENT IN A PHASE 3 TRIAL OF NEWLY-DIAGNOSED GLIOBLASTOMA TREATED WITH CHEMORADIATION WITH OR WITHOUT BEVACIZUMAB
Neuro-Oncology·2024Open Access
Supplementary Data 1 from Depth of radiographic response (DpR) and time to tumor regrowth (TTG) predicts overall survival following anti-VEGF therapy in recurrent glioblastoma
2024Open Access
Supplemental Figure S1 from Depth of radiographic response (DpR) and time to tumor regrowth (TTG) predicts overall survival following anti-VEGF therapy in recurrent glioblastoma
2024Open Access
Supplemental Figure S2 from Depth of radiographic response (DpR) and time to tumor regrowth (TTG) predicts overall survival following anti-VEGF therapy in recurrent glioblastoma
2024Open Access
Data from Depth of radiographic response (DpR) and time to tumor regrowth (TTG) predicts overall survival following anti-VEGF therapy in recurrent glioblastoma
2024Open Access
Supplemental Figure S2 from Depth of radiographic response (DpR) and time to tumor regrowth (TTG) predicts overall survival following anti-VEGF therapy in recurrent glioblastoma
2024Open Access
Supplementary Data 1 from Depth of radiographic response (DpR) and time to tumor regrowth (TTG) predicts overall survival following anti-VEGF therapy in recurrent glioblastoma
2024Open Access
Supplemental Figure S1 from Depth of radiographic response (DpR) and time to tumor regrowth (TTG) predicts overall survival following anti-VEGF therapy in recurrent glioblastoma
2024Open Access
Bevacizumab Alone and in Combination With Irinotecan in Recurrent Glioblastoma
Journal of Clinical Oncology·2023· 180 cited
Supplemental Figure S1 from Depth of Radiographic Response and Time to Tumor Regrowth Predicts Overall Survival Following Anti-VEGF Therapy in Recurrent Glioblastoma
2023Open Access
Supplemental Figure S2 from Depth of Radiographic Response and Time to Tumor Regrowth Predicts Overall Survival Following Anti-VEGF Therapy in Recurrent Glioblastoma
2023Open Access
Supplemental Figure S1 from Depth of Radiographic Response and Time to Tumor Regrowth Predicts Overall Survival Following Anti-VEGF Therapy in Recurrent Glioblastoma
2023Open Access
Data from Depth of Radiographic Response and Time to Tumor Regrowth Predicts Overall Survival Following Anti-VEGF Therapy in Recurrent Glioblastoma
2023Open Access
Supplementary Data 1 from Depth of Radiographic Response and Time to Tumor Regrowth Predicts Overall Survival Following Anti-VEGF Therapy in Recurrent Glioblastoma
2023Open Access
Supplementary Data 1 from Depth of Radiographic Response and Time to Tumor Regrowth Predicts Overall Survival Following Anti-VEGF Therapy in Recurrent Glioblastoma
2023Open Access
Data from Depth of Radiographic Response and Time to Tumor Regrowth Predicts Overall Survival Following Anti-VEGF Therapy in Recurrent Glioblastoma
2023Open Access
Supplemental Figure S2 from Depth of Radiographic Response and Time to Tumor Regrowth Predicts Overall Survival Following Anti-VEGF Therapy in Recurrent Glioblastoma
2023Open Access
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Frequent Co-authors

Lisa M. DeAngelis(29), Timothy F. Cloughesy(11), Michael D. Prados(11), Patrick Y. Wen(11), Joachim Yahalom(9), David Schiff(8), Denise D. Correa(8), Antonio Omuro(8), Fábio M. Iwamoto(8), Tracy T. Batchelor(7), Minesh P. Mehta(7), Kathleen R. Lamborn(7), Edward A. Neuwelt(6), Katherine S. Panageas(6), H. Ian Robins(6), Andrew B. Lassman(6), Nina A. Paleologos(5), Andrés J.M. Ferreri(5), Jeffrey J. Raizer(5), Mark R. Gilbert(5)