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Colman, Howard

Mayo Clinic

University of Utah

Citations 3

Feasibility and conduct of INSIGhT, a platform trial of patients with glioblastoma using Bayesian adaptive randomization.
Lee, Eudocia Q. , Trippa, Lorenzo , Fell, Geoffrey, Rahman, Rifaquat , Arrillaga‐Romany, Isabel , Welch, Mary , Ahluwalia, Manmeet S. , Colman, Howard, Hepel, Jaroslaw T., Schiff, David , Lu‐Emerson, Christine , Reardon, David A. , Wen, Patrick Y. , Ahluwalia, Manmeet S , Fell, Geoffrey G. , Arrillaga‐Romany, Isabel , Drappatz, Jan , Galanis, Evanthia , Colman, Howard , Nabors, Burt , Kaley, Thomas , Chiocca, E Antonio , Ligon, Keith L , Alexander, Brian M. , Wen, Patrick Yung

Journal of Clinical Oncology | June 6, 2022 | Volume: 40 | Issue: 16_suppl | Pages: 2012-2012

10.1200/jco.2022.40.16_suppl.2012 Get It

2012 Background: Individualized Screening Trial of Innovative Glioblastoma Therapy (INSIGhT) trial is a phase II platform trial using response adaptive randomization and deep genomic profiling to more efficiently test experimental agents in MGMT unmethylated glioblastoma and potentially accelerate identification of novel therapies for phase III testing. We report on the feasibility and conduct of this approach. Methods: Tumor genotyping was performed prior to treatment assignment on eligible participants with newly diagnosed MGMT-unmethylated glioblastoma to identify biomarker signatures. Initial randomization was 1:1:1:1 between control (temozolomide) and 3 experimental arms (abemaciclib, CC-115, and neratinib). Subsequent randomization was adapted based on Bayesian estimation of biomarker-naïve and biomarker-specific probabilities of treatment impact on progression-free survival (PFS). Ineffective or toxic arms were discontinued by protocol amendment. The primary endpoint was overall survival (OS). Results: INSIGhT randomized 71 patients to the control arm, 73 patients to the abemaciclib arm, 12 patients to the CC-115 arm, and 81 patients to the neratinib arm between 2/9/2017 and 5/14/2021. Following the initial equal randomization period, early data were repeatedly analyzed during the study to capture early signals of treatment effects across the enrolled population or in specific biomarker subgroups. The results of these interim analyses influenced the randomization probability for future enrolled patients. In total, 77% of the participants were randomized before assessing their biomarker profile and 23% were biomarker randomized. The CC-115 arm opened and closed three times during the safety lead-in. The randomization probability to the CC-115 arm decreased based on poor early PFS results and the arm eventually closed after 12 patients due to toxicity. The randomization probability to the abemacicilb arm increased based on promising early PFS results. After the completion of accrual into the abemaciclib arm, the trial switched to block randomization to finish enrolling into the remaining neratinib and control arms. A total of 28 interim analyses and 32 randomization tables were created throughout the course of the trial with 4 adjustments (3 due to CC-115 closures and 1 due to completion of the abemaciclib arm). Biomarker association trends for neratinib and abemaciclib were similar to those seen in preclinical modeling of the trial. Conclusions: Relative to a standard randomization design, the adaptive platform design facilitated more efficient and economical testing of experimental arms by sharing a control arm, decreasing the probability of enrollment to potentially ineffective arms, and increasing the probability of enrollment to potentially effective arms. Additional future arms are planned on INSIGhT. Clinical trial information: NCT02977780.
Molecular predictors of outcome and response to bevacizumab (BEV) based on analysis of RTOG 0825, a phase III trial comparing chemoradiation (CRT) with and without BEV in patients with newly diagnosed glioblastoma (GBM).
Won, Minhee , Blumenthal, Deborah T. , Vogelbaum, Michael A. , Colman, Howard, Jenkins, Robert B. , Chakravarti, Arnab , Brown, Paul D. , Jaeckle, Kurt A. , Schiff, David , Dignam, James J., Atkins, James N., Brachman, David, Werner‐Wasik, Maria, Komaki, Ritsuko , Mehta, Minesh P. , Aldape, Kenneth , Sulman, Erik P. , Colman, Howard , Jeraj, Robert , Gilbert, Mark R. , Mehta, Minesh P

Journal of Clinical Oncology | February 24, 2017 | Volume: 31 | Issue: 18_suppl | Pages: LBA2010-LBA2010

10.1200/jco.2013.31.18_suppl.lba2010 Get It

LBA2010 Background: RTOG 0825 evaluated the addition of BEV to standard CRT in the treatment of GBM and included molecular stratification that assessed the degree of mesenchymal (MES) gene enrichment. We investigated the ability of the MES signature to predict response to BEV. Methods: Sufficient FFPE tissue for molecular analysis was available for 650 registered, eligible patients. TaqMan PCR was performed prospectively using the molecular stratifier on all patients and an expanded 43 member MES set on 234 cases. A subset of specimens was subjected to whole genome expression profiling (GEP). Predictive models were evaluated for their ability to predict survival (overall, OS, and progression-free, PFS) in the training cohort of the BEV arm after adjusting for prognostic factors and treatment arm. Unsupervised clustering of GEP data was used to identify molecular subsets and gene set enrichment analysis (GSEA) performed to evaluate for MES enrichment. Results: We observed a significant association between increasing MES signature and worse PFS and OS in the BEV arm (p=0.036 and p=0.032, respectively). Based on the association between high MES expression and poor outcome in the BEV arm, we sought to optimize a predictor using an expanded set of MES genes. Unbiased gene selection from a total of 43 genes followed by radial basis machine modeling identified a 10-gene predictor of outcome in the BEV arm (p<0.001/HR 4.04 for OS and p<0.001/HR 2.21 for PFS). To further support the association of MES enrichment and poor outcome in the BEV arm, we performed GEP. Unsupervised clustering identified a subtype of tumors with MES enrichment associated with the 10-gene predictor survival probability (p=0.0124, t-test). Ongoing studies will determine the extent to which this represents a predictive marker for BEV. Conclusions: We developed a 10-gene predictor specific to BEV treatment and suitable for FFPE that may serve to identify subsets of patients with newly diagnosed GBM who benefit from BEV. Supported by RTOG grant U10 CA21661, CCOP grant U10 CA37422, and Brain SPORE P50 CA127001 from the NCI and Genentech. Clinical trial information: NCT00884741.
RTOG 0825: Phase III double-blind placebo-controlled trial evaluating bevacizumab (Bev) in patients (Pts) with newly diagnosed glioblastoma (GBM).
Dignam, James J., Won, Minhee , Blumenthal, Deborah T. , Vogelbaum, Michael A. , Aldape, Kenneth , Colman, Howard, Chakravarti, Arnab , Brown, Paul D. , Jaeckle, Kurt A. , Schiff, David , Atkins, James N., Brachman, David, Werner‐Wasik, Maria, Komaki, Ritsuko , Mehta, Minesh P. , Gilbert, Mark R. , Colman, Howard , Jeraj, Robert , Armstrong, Terri S. , Wefel, Jeffrey S. , Sulman, Erik P. , Mehta, Minesh P

Journal of Clinical Oncology | February 24, 2017 | Volume: 31 | Issue: 18_suppl | Pages: 1-1

10.1200/jco.2013.31.18_suppl.1 Get It

1 Background: Chemoradiation (CRT) with temozolomide (TMZ/RT→TMZ) is the standard of care for newly diagnosed GBM. This trial determined if the addition of Bev to standard CRT improves survival (OS) or progression-free survival (PFS) in newly diagnosed GBM. Methods: This phase III trial was conducted by the RTOG, NCCTG, and ECOG. Neurologically stable pts > 18 yrs with KPS ≥ 60, and > 1cm3 tumor tissue block, were randomized to Arm 1: standard CRT + placebo or Arm 2: standard CRT plus Bev (10 mg/kg iv q 2wks). Experimental treatment began at wk 4 of radiation then thru 6-12 cycles of maintenance chemotherapy. Protocol specified co-primary endpoints were OS and PFS, with significance levels of .023 and .002, respectively. At progression, treatment was unblinded and pts allowed to crossover or continue Bev. Symptom, QOL and neurocognitive (NCF) testing was performed in the majority of pts. Secondary analyses evaluated impact of MGMT methylation (meth) and prognostic 9 gene signature status. Results: From 978 registered pts, 637 were randomized. Inadequate tissue (n=105) and blood on imaging (n=40) were key reasons for non-randomization. No difference was found between arms for OS (median 16.1 vs. 15.7 mo, p = 0.11). PFS was extended for Arm 2 (7.3 vs. 10.7 mo, p = 0.004). Pts with MGMT meth had superior OS (23.2 vs. 14.3 mo, p < 0.001) and PFS (14.1 vs. 8.2 mo, p < 0.001). Neither the 9 gene signature nor MGMT predicted selective benefit for Bev treatment, but best prognosis pts (MGMT meth, favorable 9-gene), had a worse survival trend with Bev (15.7 vs 25 mo p = 0.08). To date, 128 pts were unblinded on Arm 1 (salvage Bev in 86) and 87 pts on Arm 2 (continued Bev in 39). Increased grade ≥ 3 toxicity was seen with Bev, mostly neutropenia, hypertension, and DVT/PE. Conclusions: The addition of Bev for newly diagnosed GBM did not improve OS, did improve PFS but did not reach the significance criterion. MGMT and 9 gene profile did not identify selective benefit, but risk subset results suggested strongly against the upfront use of Bev in the best prognosis pts. Full interpretation of the PFS results incorporating symptom burden, QOL, and NCF is ongoing. Support: NCI U10 CA 21661, U10 CA37422, and Genentech. Clinical trial information: NCT00884741.