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Treatment Effect Reanalysis of the Randomized Individual Screening Trial of Innovative Glioblastoma Therapy in Newly
Tulika Rudra Gupta1,2, Mei-Yin C Polley3, Robert Redd1
1Department of Data Sciences, Dana-Farber Cancer Institute, Boston, MA.
Purpose:
Integrating external control data into clinical trial designs and analyses has the potential to accelerate drug development processes. We reanalyzed the three experimental arms of the Individual Screening Trial of Innovative Glioblastoma Therapy (INSIGhT), a randomized phase II platform trial in newly diagnosed O6-methylguanine-DNA methyltransferase-unmethylated glioblastoma (ClinicalTrials.gov identifier: NCT02977780). To evaluate the validity of using external data sets, we compared treatment effect estimates based on internal INSIGhT control data and matched external control data.
Methods:
The three experimental arms of INSIGhT (abemaciclib [n = 72], neratinib [n = 80], and CC-115 [n = 12]) did not improve survival compared with internal controls (standard chemoradiation [n = 70]). We derived external control patient-level data from multiple real-world and clinical trial data sets. We applied propensity score matching and Cox proportional hazards models to estimate treatment effects with external controls. Additionally, using this glioblastoma (GBM) data collection, we specified simulation scenarios to evaluate trial designs that integrate external controls.
Results:
After matching to external controls, no survival benefit was observed for patients receiving abemaciclib (hazard ratio [HR], 1.00 [95% CI, 0.75 to 1.34]), neratinib (HR, 0.93 [95% CI, 0.70 to 1.24]), or CC-115 (HR, 0.88 [95% CI, 0.41 to 1.88]). Simulations, together with the INSIGhT data and a collection of GBM data sets, allowed us to examine efficiencies and risks of clinical trial designs that leverage external control data.
Conclusion:
The use of carefully matched external controls, to replace or augment the internal controls of INSIGhT, produced treatment effect estimates that were similar to previously published analyses. Single-arm trial designs and hybrid randomized designs incorporating propensity score-matched external control data evaluated treatment effects in the early-phase testing of experimental therapies in newly diagnosed GBM. The validity of this approach and risks of bias depended on the availability of comprehensive and accurate data on all potential confounders, in the absence of unmeasured confounding.
Insights
Using external control data in glioblastoma (GBM) trials, like the INSIGhT study, yielded similar survival estimates to internal controls. This approach, using propensity score matching, shows potential for accelerating drug development but requires comprehensive data to avoid bias.
Area of Science:
- Oncology
- Clinical Trial Design
- Biostatistics
Background:
- External control data can accelerate drug development.
- The Individual Screening Trial of Innovative Glioblastoma Therapy (INSIGhT) evaluated novel therapies in newly diagnosed glioblastoma (GBM).
- O6-methylguanine-DNA methyltransferase (MGMT)-unmethylated GBM is a specific subtype studied.
Purpose of the Study:
- To evaluate the validity of integrating external control data into clinical trial designs.
- To compare treatment effect estimates using internal versus matched external control data in the INSIGhT trial.
- To assess efficiencies and risks of trial designs leveraging external control data through simulations.
Main Methods:
- Reanalyzed three experimental arms of the INSIGhT trial (abemaciclib, neratinib, CC-115).
- Derived external control patient-level data from real-world and clinical trial sources.
- Applied propensity score matching and Cox proportional hazards models; conducted simulations for trial designs.
Main Results:
- No survival benefit observed for abemaciclib, neratinib, or CC-115 when compared to matched external controls.
- Hazard ratios (HR) for abemaciclib, neratinib, and CC-115 were 1.00, 0.93, and 0.88, respectively.
- Simulations examined the efficiencies and risks associated with integrating external control data.
Conclusions:
- Carefully matched external controls produced treatment effect estimates similar to internal controls in the INSIGhT GBM trial.
- Single-arm and hybrid randomized designs incorporating external controls can evaluate experimental therapies.
- The validity of using external controls depends on comprehensive data for confounders and absence of unmeasured confounding.
