Individualized Screening Trial of Innovative Glioblastoma Therapy (INSIGhT): A Bayesian Adaptive Platform Trial to Develop Precision Medicines for Patients With Glioblastoma

Author:

Alexander Brian M.12,Trippa Lorenzo1,Gaffey Sarah1,Arrillaga-Romany Isabel C.3,Lee Eudocia Q.1,Rinne Mikael L.24,Ahluwalia Manmeet S.5,Colman Howard6,Fell Geoffrey1,Galanis Evanthia7,de Groot John8,Drappatz Jan9,Lassman Andrew B.10,Meredith David M.12,Nabors L. Burt11,Santagata Sandro12,Schiff David12,Welch Mary R.10,Ligon Keith L.12,Wen Patrick Y.1

Affiliation:

1. Dana-Farber Cancer Institute, Boston, MA

2. Brigham and Women’s Hospital, Boston, MA

3. Massachusetts General Hospital, Boston, MA

4. Novartis Institutes for Biomedical Research, Boston, MA

5. Cleveland Clinic, Cleveland, OH

6. Huntsman Cancer Institute, Salt Lake City, UT

7. Mayo Clinic, Rochester, MN

8. MD Anderson Cancer Center, Houston, TX

9. University of Pittsburgh Medical Center, Pittsburgh, PA

10. Columbia University Medical Center, New York, NY

11. University of Alabama at Birmingham, Birmingham, AL

12. University of Virginia Health System, Charlottesville, VA

Abstract

PURPOSE Adequately prioritizing the numerous therapies and biomarkers available in late-stage testing for patients with glioblastoma (GBM) requires an efficient clinical testing platform. We developed and implemented INSIGhT (Individualized Screening Trial of Innovative Glioblastoma Therapy) as a novel adaptive platform trial (APT) to develop precision medicine approaches in GBM. METHODS INSIGhT compares experimental arms with a common control of standard concurrent temozolomide and radiation therapy followed by adjuvant temozolomide. The primary end point is overall survival. Patients with newly diagnosed unmethylated GBM who are IDH R132H mutation negative and with genomic data available for biomarker grouping are eligible. At the initiation of INSIGhT, three experimental arms (neratinib, abemaciclib, and CC-115), each with a proposed genomic biomarker, are tested simultaneously. Initial randomization is equal across arms. As the trial progresses, randomization probabilities adapt on the basis of accumulating results using Bayesian estimation of the biomarker-specific probability of treatment impact on progression-free survival. Treatment arms may drop because of low probability of treatment impact on overall survival, and new arms may be added. Detailed information on the statistical model and randomization algorithm is provided to stimulate discussion on trial design choices more generally and provide an example for other investigators developing APTs. CONCLUSION INSIGhT (NCT02977780) is an ongoing novel biomarker-based, Bayesian APT for patients with newly diagnosed unmethylated GBM. Our goal is to dramatically shorten trial execution timelines while increasing scientific power of results and biomarker discovery using adaptive randomization. We anticipate that trial execution efficiency will also be improved by using the APT format, which allows for the collaborative addition of new experimental arms while retaining the overall trial structure.

Publisher

American Society of Clinical Oncology (ASCO)

Subject

Cancer Research,Oncology

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