E9 Statistical Principles for Clinical Trials: The Foundation of Regulatory Success
Since its release in 1998, the International Council for Harmonisation (ICH) E9 guidance on Statistical Principles for Clinical Trials has provided a globally recognized framework for clinical trial design and analysis. For medical device manufacturers, understanding and applying these principles is essential to meet FDA expectations, streamline regulatory review, and build a clear evidentiary foundation for safety and effectiveness.
Why E9 Matters for Medical Device Trials
Medical device trials can, and generally do, have special aspects that are different from pharmaceutical studies. They face unique challenges, including learning curve effects as operators gain proficiency, iterative device changes, patient-specific performance differences, and the necessity for long-term follow-up to evaluate durability.
ICH E9 offers a structured framework to address these issues, ensuring trials are designed, analyzed, and reported with the rigor required for Class II and III device submissions.
Key benefits of the following E9 principles include:
Regulatory alignment with FDA statistical expectations
Transparent trial design with well-defined objectives and endpoints
Adequate statistical power to demonstrate clinically meaningful effects
Methodological rigor that minimizes bias and improves interpretability
Core E9 Principles and Their Relevance to Medical Devices
Trial Design and Planning
E9 emphasizes planning trials to yield reliable evidence of treatment effects. For device trials, this includes strategies to mitigate operator learning effects, account for potential device modifications, and capture long-term safety data. Creative designs, such as those that include adaptive and Bayesian approaches, can help address these challenges while preserving statistical integrity.
Confirmatory vs. Exploratory Trials
The FDA typically bases approval decisions on confirmatory trials with predefined hypotheses and endpoints. While exploratory studies can generate important insights during early development, confirmatory studies must adhere to strict statistical standards to support regulatory decisions. BSC® routinely designs confirmatory trials for high-risk devices, including IDE and PMA studies, ensuring alignment with FDA review criteria.
Statistical Analysis Plan (SAP)
A detailed SAP is essential. For medical device studies, important aspects of the SAP should detail the following:
Clear definitions of analysis populations (intent-to-treat, per-protocol, safety)
Handling of device-related events, malfunctions, and withdrawals
Pre-specified subgroup analyses (e.g., operator experience, anatomical subgroups)
Approaches for missing data and intercurrent events
Well-prepared SAPs minimize FDA queries and streamline submission timelines.
Sample Size Determination
Clinical trials require assumptions for effect size, dropout rates, and device failure rates, among other criteria. Sponsors should plan for FDA reviewers to require, and potentially question, sample size calculations or justifications, making early statistical input critical. Creative trial designs, including Adaptive and Bayesian sample size re-estimation, can improve efficiency while maintaining validity—an approach BSC® has successfully implemented throughout our longstanding history.
Blinding
Blinding is more challenging for devices due to their physical nature. Sham controls may raise ethical or practical concerns, and operator blinding can be difficult. BSC® develops innovative statistical adjustments and trial procedures to minimize bias when full blinding is not feasible.
Primary and Secondary Endpoints
ICH E9 emphasizes defining one primary endpoint closely aligned with the device’s intended benefit, supported by a limited set of clinically relevant secondary endpoints. For device trials, primary variables often include functional performance metrics, validated patient-reported outcomes, or long-term safety measures.
Statistical Analysis Methods
Medical device data often requires specialized analyses, such as:
Time-to-event models for device longevity
Repeated measures for longitudinal performance
Non-inferiority designs when comparing a new device to an established standard
Composite endpoints to capture multiple clinically relevant outcomes
BSC® incorporates and tailors these methods to meet FDA expectations while addressing the real-world complexity of device performance.
Ready to Strengthen Your FDA Submission?
If you’re planning a clinical trial for a Class II or III device, BSC® can help align your study design and analysis with ICH E9 principles and FDA expectations.
Schedule a consultation today to ensure your next study generates the regulatory-grade evidence you need.
References
International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use (ICH). (1998). ICH harmonised tripartite guideline: Statistical principles for clinical trials E9. U.S. Food and Drug Administration.
European Medicines Agency. (2020). ICH E9(R1) addendum on estimands and sensitivity analysis in clinical trials to the guideline on statistical principles for clinical trials (EMA/CHMP/ICH/436221/2017) https://www.ema.europa.eu/en/documents/scientific-guideline/ich-e9-r1-addendum-estimands-and-sensitivity-analysis-clinical-trials-guideline-statistical-principles-clinical-trials-step-5_en.pdf