Real-world data (RWD) has proven to be a pivotal tool in understanding patient treatment and outcomes in routine clinical practice. Furthermore, it also provides valuable insights in those circumstances, like rare oncology indications, when randomized controlled trials are either infeasible or unethical. In these cases, RWD can be used to develop external controls for single-arm clinical trials to provide valuable benchmark results on potential comparator drug effectiveness.
In an article published in Clinical and Translational Science in collaboration with Merck KGgA, Aetion scientists Trisha Prince and Adina Estrin outline the lessons learned from conducting a real-world external control cohort study to provide benchmark data for a single-arm clinical trial of a tepotinib – a treatment for non-small cell lung cancer (NSCLC) for patients harboring mesenchymal epithelial transition exon 14 (METex14) skipping alterations. This blog will outline this study’s methods, challenges, and key takeaways.
Methods Used
As biomarker-specific NSCLC is categorized as a rare disease, data for this study were limited. To address this study design challenge, three separate sources of electronic medical records were selected and pooled to form the study dataset. From this pooled dataset, external controls were selected to descriptively contextualize the results from the clinical trial of the NSCLC treatment.
Challenges
Real-world external control cohort studies in the field of oncology are valuable, specifically when the clinical trial is non-randomized and only includes a single treatment arm, but studies like these present several challenges. For instance, in this study, many of the data elements that are most valuable for oncology disease assessments were not collected by the electronic health records or missing for a majority of patients. Additionally, when the clinical trial eligibility criteria were applied, the small sample size was further reduced, resulting in potential bias related to patient selection. Despite this, mitigating methods like careful study design and propensity score methodologies were applied to account for the potential bias in selection criteria and the lack of randomization.
Lessons Learned for Future Studies
While conducting an external control cohort study was not without its challenges, there are several insights that can be applied to future research in the areas of oncology and rare diseases. To start, this study’s key findings underscore the importance of carefully establishing a transparent protocol and statistical analysis plan to most effectively achieve comparability between clinical trial patients and external controls. From there, this study highlighted the importance of fit-for-purpose data selection when multiple data sources need to be pooled. Finally, anticipating the challenges associated with these studies – for instance, combatting data missingness by working with data providers early and often to fully understand the completeness of data elements needed for the external control study – can help mitigate many of these obstacles in future studies.
To learn more about our oncology efforts here at Aetion, or to speak with one of our experts, contact us here.