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Assessment of treatment response to dendritic cell vaccine in patients with glioblastoma using a multiparametric MRI-based prediction model.
de Godoy, Laiz Laura; Chawla, Sanjeev; Brem, Steven; Wang, Sumei; O'Rourke, Donald M; Nasrallah, MacLean P; Desai, Arati; Loevner, Laurie A; Liau, Linda M; Mohan, Suyash.
Afiliação
  • de Godoy LL; Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA.
  • Chawla S; Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA. Sanjeev.Chawla@pennmedicine.upenn.edu.
  • Brem S; Department of Neurosurgery, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA.
  • Wang S; Abramson Cancer Center, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA.
  • O'Rourke DM; Glioblastoma Translational Center of Excellence, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA.
  • Nasrallah MP; Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA.
  • Desai A; Department of Neurosurgery, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA.
  • Loevner LA; Abramson Cancer Center, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA.
  • Liau LM; Glioblastoma Translational Center of Excellence, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA.
  • Mohan S; Glioblastoma Translational Center of Excellence, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA.
J Neurooncol ; 163(1): 173-183, 2023 May.
Article em En | MEDLINE | ID: mdl-37129737
ABSTRACT

PURPOSE:

Autologous tumor lysate-loaded dendritic cell vaccine (DCVax-L) is a promising treatment modality for glioblastomas. The purpose of this study was to investigate the potential utility of multiparametric MRI-based prediction model in evaluating treatment response in glioblastoma patients treated with DCVax-L.

METHODS:

Seventeen glioblastoma patients treated with standard-of-care therapy + DCVax-L were included. When tumor progression (TP) was suspected and repeat surgery was being contemplated, we sought to ascertain the number of cases correctly classified as TP + mixed response or pseudoprogression (PsP) from multiparametric MRI-based prediction model using histopathology/mRANO criteria as ground truth. Multiparametric MRI model consisted of predictive probabilities (PP) of tumor progression computed from diffusion and perfusion MRI-derived parameters. A comparison of overall survival (OS) was performed between patients treated with standard-of-care therapy + DCVax-L and standard-of-care therapy alone (external controls). Additionally, Kaplan-Meier analyses were performed to compare OS between two groups of patients using PsP, Ki-67, and MGMT promoter methylation status as stratification variables.

RESULTS:

Multiparametric MRI model correctly predicted TP + mixed response in 72.7% of cases (8/11) and PsP in 83.3% (5/6) with an overall concordance rate of 76.5% with final diagnosis as determined by histopathology/mRANO criteria. There was a significant concordant correlation coefficient between PP values and histopathology/mRANO criteria (r = 0.54; p = 0.026). DCVax-L-treated patients had significantly prolonged OS than those treated with standard-of-care therapy (22.38 ± 12.8 vs. 13.8 ± 9.5 months, p = 0.040). Additionally, glioblastomas with PsP, MGMT promoter methylation status, and Ki-67 values below median had longer OS than their counterparts.

CONCLUSION:

Multiparametric MRI-based prediction model can assess treatment response to DCVax-L in patients with glioblastoma.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Neoplasias Encefálicas / Vacinas / Glioblastoma / Imageamento por Ressonância Magnética Multiparamétrica Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Neoplasias Encefálicas / Vacinas / Glioblastoma / Imageamento por Ressonância Magnética Multiparamétrica Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Ano de publicação: 2023 Tipo de documento: Article