Unlocking the Potential of External Control Arms in Real-World Evidence (RWE)

When RCT (gold standard) cannot be used due to ethical or feasibility issues, an external arm can be used. External control arms, otherwise known as synthetic control arms, are based on real-world data (RWD) from electronic medical records, medical claims, wearable devices, patient registries, etc. They are being used for primary drug/device approval or label expansion and even for decisions on clinical trials. Patients in an externally controlled trial are not part of the same randomized study as the group receiving the investigational agent, i.e., there is no concurrently randomized control group.

You used an external control arm:

• When RCTs are unethical, impractical, and imbalance
• Can be used in rare diseases, Significant unmet medical needs, Under-represented populations, pediatrics, etc.

They can be

• Concurrent control: Patient treated during the same time period suggesting a comparable standard of care
• Historical Control: Retrospective data is used as a comparator

Advantages of external control arm:

• High rate of treatment cross over
• No challenges with recruitment
• Accelerated approval process
• Increased probability of approval
• Increased efficiency and reduced trial expenses

Considerations while employing external control arm:

• Data quality: Selection of appropriate data sources and data quality in terms of completeness and validation is of utmost importance to provide acceptable evidence. Additionally, ICH guidelines on ethical, legal, and regulatory standards should be employed. Because incorporating clinical trial data with RWD would mean addressing informed consent, patient data protection, etc.
• Bias/Confounding: Bayesian methods can be used to minimize bias or confounding. Even sensitivity analyses can be used to evaluate the robustness of results. propensity scores, Inverse probability weighting, and Marginal structural models can be used to minimize confounding/selection bias. Unmeasured or unknown confounders are always present.
• Small sample size: Important in rare diseases or pediatrics as enough sample size is needed to detect rare adverse events. However, balancing out a stringent set of inclusion/exclusion criteria and biases may be necessary to evaluate in a small sample size.
• Randomization: Using RWD, treatment allocation cannot be randomized. Because several factors (sociodemographic and clinical characteristics, insurance status, prescriber preference, etc.) play role in a patient receiving treatment medicine. Hence, an external control arm with RWD should be structured to address this challenge.  timeline for evidence generation, and availability of appropriate and sufficiently high-quality data sources. During trial design to maintain randomization, other options such as N:1 randomization ratios should be utilized

Reference:

ICH Harmonized Guideline: Choice of Control Group and Related Issues in Clinical Trials E10. 2000.

FDA Guidance. E10 Choice of Control Group and Related Issues in Clinical Trials. 2001