Evaluation of Differences in Trial and Non-Trial Patients and Leveraging of External Data for More Efficient Clinical Trial Designs in Newly Diagnosed Glioblastoma

Glioblastoma (GBM) is an aggressive primary central nervous system tumor, and it is the most common primary malignant brain tumor in adults. There is a critical need for better therapies, as GBM continues to be associated with a dismal prognosis despite maximal therapy with surgery, radiation therapy and chemotherapy (Stupp et al. 2005). While there have been some improvements in understanding the molecular pathways underlying GBM, there have been very few advances in the treatment of GBM in the last two decades.

In glioblastoma, the current clinical trial landscape is felt to be suboptimal for the development of new therapies, and there is a significant need for both better therapies and for a better system for testing and developing such therapies (Vanderbeek et al. 2018, Neuro-Oncology). Given these issues, glioblastoma has a dismal success rate in resource-intensive, time-consuming phase III trials with only one successful trial in the last several decades. Many failures in drug development in glioblastoma have been attributed to the overestimation of the treatment effect in early phase studies.

I. Trial Effects

While most oncologists believe that patients with cancer who enroll in clinical trials have better outcomes (Peppercorn et al. 2004), scant evidence exists on whether there is an effect of trial participation itself on outcome (i.e. a trial effect) (Unger et al. 2014). Of note, the largest limitation in the reviewed studies was inconsistent and insufficient strategies to control for potential confounders. There are broad efforts to improve clinical trial participation in GBM (Lee et al. 2019), but better understanding of patient characteristics, tumor-related factors and clinical outcomes among clinical trial and non-trial patients is important to provide insight into steps to increase this.

II. Incorporating External Data into Trial Designs
While early phase randomized controlled trials have been suggested as a possible solution, they require larger sample sizes, longer enrollment periods, and discourage patients who do not want to be randomized to a control arm (Vanderbeek et al. 2019, Neuro-Oncology). There is increasing interest in using data from outside of clinical trials to replace or support controls within trials. The methodological development underpinning these "external control arms" is unclear, however. The rationale for this project is to develop an external control arm for clinical trials of newly diagnosed GBM and test the viability of such an approach given GBM-specific details such as endpoint variability in progression-free survival (PFS), overall survival (OS), and relevant prognostic factors.

This research can have a tremendous impact in the field of neuro-oncology. It will allow us to explore a type of trial design that could significantly accelerate the progress in glioblastoma to find more effective therapies faster and more efficiently. It will also help clinicians better understand how to interpret and contextualize clinical trials by comparing clinical trial patients with non-trial patients.