Adaptive global innovative learning environment for glioblastoma: GBM AGILE

GBM AGILE Network

Research output: Contribution to journalReview article

22 Citations (Scopus)

Abstract

Glioblastoma (GBM) is a deadly disease with few effective therapies. Although much has been learned about the molecular characteristics of the disease, this knowledge has not been translated into clinical improvements for patients. At the same time, many new therapies are being developed. Many of these therapies have potential biomarkers to identify responders. The result is an enormous amount of testable clinical questions that must be answered efficiently. The GBM Adaptive Global Innovative Learning Environment (GBM AGILE) is a novel, multi-arm, platform trial designed to address these challenges. It is the result of the collective work of over 130 oncologists, statisticians, pathologists, neurosurgeons, imagers, and translational and basic scientists from around the world. GBM AGILE is composed of two stages. The first stage is a Bayesian adaptively randomized screening stage to identify effective therapies based on impact on overall survival compared with a common control. This stage also finds the population in which the therapy shows the most promise based on clinical indication and biomarker status. Highly effective therapies transition in an inferentially seamless manner in the identified population to a second confirmatory stage. The second stage uses fixed randomization to confirm the findings from the first stage to support registration. Therapeutic arms with biomarkers May be added to the trial over time, while others complete testing. The design of GBM AGILE enables rapid clinical testing of new therapies and biomarkers to speed highly effective therapies to clinical practice.

Original languageEnglish (US)
Pages (from-to)737-743
Number of pages7
JournalClinical Cancer Research
Volume24
Issue number4
DOIs
StatePublished - Feb 15 2018

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Glioblastoma
Learning
Biomarkers
Therapeutics
Random Allocation
Population
Survival

ASJC Scopus subject areas

  • Oncology
  • Cancer Research

Cite this

Adaptive global innovative learning environment for glioblastoma : GBM AGILE. / GBM AGILE Network.

In: Clinical Cancer Research, Vol. 24, No. 4, 15.02.2018, p. 737-743.

Research output: Contribution to journalReview article

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abstract = "Glioblastoma (GBM) is a deadly disease with few effective therapies. Although much has been learned about the molecular characteristics of the disease, this knowledge has not been translated into clinical improvements for patients. At the same time, many new therapies are being developed. Many of these therapies have potential biomarkers to identify responders. The result is an enormous amount of testable clinical questions that must be answered efficiently. The GBM Adaptive Global Innovative Learning Environment (GBM AGILE) is a novel, multi-arm, platform trial designed to address these challenges. It is the result of the collective work of over 130 oncologists, statisticians, pathologists, neurosurgeons, imagers, and translational and basic scientists from around the world. GBM AGILE is composed of two stages. The first stage is a Bayesian adaptively randomized screening stage to identify effective therapies based on impact on overall survival compared with a common control. This stage also finds the population in which the therapy shows the most promise based on clinical indication and biomarker status. Highly effective therapies transition in an inferentially seamless manner in the identified population to a second confirmatory stage. The second stage uses fixed randomization to confirm the findings from the first stage to support registration. Therapeutic arms with biomarkers May be added to the trial over time, while others complete testing. The design of GBM AGILE enables rapid clinical testing of new therapies and biomarkers to speed highly effective therapies to clinical practice.",
author = "{GBM AGILE Network} and Alexander, {Brian M.} and Sujuan Ba and Berger, {Mitchel S.} and Berry, {Donald A.} and Cavenee, {Webster K.} and Chang, {Susan M.} and Cloughesy, {Timothy F.} and Tao Jiang and Mustafa Khasraw and Wenbin Li and Robert Mittman and Poste, {George H.} and Wen, {Patrick Y.} and {Alfred Yung}, {W. K.} and Barker, {Anna D.} and {David Adelson}, P. and Alexander, {Brian M.} and Joe Alper and Arnold, {Michelle M.} and Arons, {David F.} and Ashley, {David N.} and Sujuan Ba and Barker, {Anna D.} and Berger, {Mitchel S.} and Berry, {Donald A.} and Boxerman, {Jerrold L.} and Brat, {Daniel J.} and Brennan, {Cameron W.} and Michael Buckland and Kenneth Buetow and Meredith Buxton and Cantley, {Lewis C.} and Cavenee, {Webster K.} and Chang, {Susan M.} and Ling Chen and Lynda Chin and {Antonio Chiocca}, E. and Cloughesy, {Timothy F.} and Cohen, {Darrel P.} and Howard Colman and Carolyn Compton and Jason Connor and {James-Neil Cooper}, Laurence and Vladimir Coric and Costello, {Joseph F.} and {De Groot}, {John F.} and Jayesh Desai and Giulio Draetta and Ellingson, {Benjamin M.} and Evanthia Galanis",
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