Understanding external controls and their importance to clinical trials for rare diseases
Typically, clinical trial participants are randomly split into two arms: treatment and placebo. The placebo group serves as the control arm and provides researchers a way to measure the effectiveness of the therapy. Placebo-controlled studies are the gold standard in clinical research because they provide the most direct comparison and surest way to determine whether a treatment is effective.
But in rare disease, the small number of people affected can make it difficult to fill both a treatment and control arm. That may lead to a delay in starting a trial and extending the time it takes to get new therapies to patients.
Increasingly, external controls are being used to supplement – and sometimes even replace – placebo arms in clinical trials. An external control is an arm of a clinical trial made up of people external to the study. The external control may be constructed with data from the placebo arm of past studies, natural history studies, electronic health records or a combination of data sets from multiple sources. The goal is to provide a well-matched control group to establish the treatment effect of the study medicine.
As leaders in precision genetic medicine, Sarepta is advancing scientifically rigorous approaches to incorporating external controls into clinical trials. “The unmet need in rare diseases is great – and in the case of progressive diseases, patients don’t have the luxury of time,” said Teji Singh, M.D., vice president and head of Clinical Development at Sarepta. “We’ve made incredible progress in genetic medicine science. Now we owe it to rare disease patients to do all we can to get these breakthroughs to more patients faster.”
Overcoming the numbers challenge
In all clinical trials, patients must meet strict inclusion criteria in order to participate. This helps create a group of participants who possess very similar, or homogeneous, characteristics. This then allows researchers to compare participants across trial arms, and within arms, to evaluate if the investigational therapy is effective.
But many rare diseases are complex, and these diseases can progress at varying rates in different people. This disease heterogeneity, as it’s known, can make it challenging to determine whether an investigational treatment is effective, even when comparing patients in a seemingly homogenous trial group.
In Duchenne muscular dystrophy, for example, one 8-year-old boy may have a different disease progression than another. It can be difficult to determine if a boy’s disease has stabilized because the investigational therapy is working or if it’s more a reflection of his natural disease progression. In the case of heterogeneous diseases, investigators add many layers of inclusion criteria in order to create as homogeneous group as possible. But in rare diseases, that specificity can make it hard to enroll trials and use a placebo arm, according to Craig McDonald, M.D., director, MDA Neuromuscular Disease Clinics at UC Davis Health.
“In rare disease trials, where the overall patient populations are smaller, it can be challenging just to enroll enough patients to give the trial some amount of statistical power,” he explained. “When you look at further identifying a homogenous group of patients for the treatment arm, and then a homogenous placebo arm on top of that, the patient pool can get very, very small. And that’s where external controls can provide a viable addition.”
Building apples-to-apples comparisons
At Sarepta, one approach used by our clinical development team is a rigorous and highly sophisticated statistical analysis known as propensity score weighting to ensure the external control is closely matched to people in our clinical trials. Propensity score weighting is a statistical methodology that allows clinical development specialists to examine multiple variables (such as age, time on steroid treatment and baseline scores on key functional measures) in order to identify similarities and differences within the trial population, and then account for them in the trial results. This analysis helps develop a very closely matched patient group so that clinical results are clear and validated.
External controls are already common in cancer clinical trials, and over the past two decades, there have been 45 U.S. FDA approvals with external control data in their benefit/risk assessment.1 In accepting the external control data, the FDA cited the rare nature of the disease being addressed, ethical concerns regarding use of placebo, seriousness of the condition and high unmet medical need.
In the case of Duchenne, several recent studies substantiate the validity of external controls as a reliable comparator in Duchenne trials. For example, in 2021, the Collaborative Trajectory Analysis Project (cTAP), a global research coalition focused on Duchenne muscular dystrophy, shared results indicating that both real world data and natural history data are highly comparable to data from patients treated with placebo in multiple recent clinical trials.2
“Placebo trials will always be the foundation for clinical trials, but the research shows that there is a place for external controls in rare disease trials,” Singh said. “At Sarepta, our goal is to shorten the time from lab to patient, and we are committed to pursuing every scientifically sound opportunity to do that.”
1. Jahanshahi, M., Gregg, K., Davis, G. et al. The Use of External Controls in FDA Regulatory Decision Making. Ther Innov Regul Sci 55, 1019–1035 (2021).
2. Muntoni F, Signorovitch J, Sajeev G, Goemans N, Wong B, Tian C, Mercuri E, Done N, Wong H, Moss J, Yao Z, Ward SJ, Manzur A, Servais L, Niks EH, Straub V, de Groot IJ, McDonald C; North Star Clinical Network, PRO-DMD-01 Study, The Association Française contre les Myopathies (AFM), The DMD Italian Group, and The Collaborative Trajectory Analysis Project (cTAP). Real-world and natural history data for drug evaluation in Duchenne muscular dystrophy: suitability of the North Star Ambulatory Assessment for comparisons with external controls. Neuromuscul Disord. 2022 Apr;32(4):271-283.