Synthetic Controls: Unlocking the Promise of Historical and Real-World Data
In place of collecting data from patients recruited for a trial who have been assigned to the control or standard-ofcare arm, a synthetic control creates a comparator arm using either real-world datasets such as electronic health records or previous clinical trials. The synthetic control offers a practical, effective way to leverage real-world evidence and has been applied in regulatory approvals.
Our customer is a specialized biopharmaceutical company, developing novel oncology therapies. Their breakthrough therapy had the potential to be first-in-class for a rare and aggressive hematological cancer and had shown great potential in earlier clinical trials. In areas of high unmet need, it is critical to bring vital new medicines to patients faster, yet conventional development pathways involving multiple stages can be slow, expensive and inefficient.
In many breakthrough treatment areas, where the patient population is small, or there is overwhelming evidence of efficacy at Phase 2, it has become common for drugs to be approved based on a pivotal single arm trial – however, this is not always optimal. With this in mind, our customer planned a registration pathway based on a single arm registrational study with a comparison to a synthetic control.
“THE SYNTHETIC CONTROL OFFERS A PRACTICAL, EFFECTIVE WAY TO LEVERAGE REAL-WORLD EVIDENCE AND HAS BEEN APPLIED IN REGULATORY APPROVALS”
Creating a synthetic control requires advanced statistical expertise to effectively distribute the baseline characteristics between the synthetic control arm and the arm receiving the experimental treatment.
The client acquired databases from two leading cancer centers and planned to combine it with data from two earlier clinical trials to form a retrospective trial as a comparison to one of their single arm pivotal trials.
They approached Cytel to help identify the best statistical and analytical methods and deliver the analysis based on the acquired real-world data.
The solution comprised:
Data Cleaning and Curation
Combine datasets from the two purchased oncology databases and the two prior clinical trials for the retrospective analysis
Clean and standardize data to prepare it for analysis
Address missing and inconsistent data issues
Analyses for Pivotal Trial
Summarize the data from the cleaned and pooled retrospective dataset
Divide single arm trial data and retrospective dataset into six groups (by refractory category and ECOG status) and perform a weighted average
Propensity score matching with bootstrap confidence intervals to equalize the groups and examine the average treatment effect
Increasingly complex propensity score matching using AIPWCC estimators for survival analysis producing Kaplan-Meier type graphs adjusted for covariates
Analysis for Regulatory Responses and Health Economic Insights
Create different analyses over the course of several months to respond to EMA regulatory requests
Examine numbers of post-refractory treatments to inform health economic insights
Produce specific analyses to respond to requests from regulatory agencies
The Cytel Advantage
As a pioneer in evidence generation, with deep expertise in advanced analytical solutions, Cytel is uniquely equipped to unlock the value from increasingly complex data. Life sciences companies count on Cytel to deliver exceptional insight, minimize trial risk and accelerate the development of promising new medicines that improve human life. Cytel provides data-focused clinical research services and software solutions for the design and analysis of clinical trials, including industry standards East®, StatXact®, and LogXact®. With operations across North America, Europe, and India, Cytel employs 900 professionals, with strong talent in biostatistics, programming, data science, and data management.