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Updated: Apr 3, 2026
In Silico Clinical Trials for Cardiovascular Disease
Published on: May 27, 2022
Statistical challenges in a regulatory review of cardiovascular and CNS clinical trials
H M James Hung1, Sue-Jane Wang2, Peiling Yang1
1a Division of Biometrics I, Office of Biostatistics , Office of Translational Sciences, Center for Drug Evaluation and Research, Food and Drug Administration , Silver Spring , Maryland , USA.
Insights
Statistical challenges in cardiovascular (CV) and central nervous system (CNS) trials, including missing data and endpoint selection, are common. Adaptive designs and group sequential designs (GSDs) are increasingly used, presenting new statistical hurdles.
Area of Science:
- Clinical Trials Statistics
- Regulatory Science
- Pharmaceutical Development
Background:
- Cardiovascular (CV) and central nervous system (CNS) clinical trials face unique statistical challenges.
- These challenges stem from disease characteristics, endpoints, trial duration, and size.
- Schizophrenia trials suffer from missing data; Alzheimer's trials struggle with endpoint differentiation; CV trials face large sample sizes due to low event rates.
Purpose of the Study:
- To identify and discuss statistical challenges in regulatory reviews of large CV and CNS clinical trials.
- To highlight common and distinct problems encountered in these trial types.
- To share insights gained from regulatory application reviews regarding statistical methodologies.
Main Methods:
- Review of statistical challenges encountered during regulatory review of CV and CNS clinical trials.
- Analysis of common and distinct problems related to trial design, endpoints, and data.
- Examination of the increasing use and associated challenges of adaptive and group sequential designs (GSDs).
Main Results:
- Significant statistical issues exist in CV and CNS trials, impacting trial design and interpretation.
- Missing data in schizophrenia trials and endpoint selection in Alzheimer's trials are critical concerns.
- Large sample sizes in CV trials and the complexities of adaptive designs present ongoing challenges.
Conclusions:
- Adaptive designs and group sequential designs (GSDs) are increasingly prevalent in CV and CNS drug development.
- New statistical challenges arise with the implementation of advanced adaptive designs.
- Addressing these statistical complexities is crucial for efficient and effective clinical trial evaluation and drug approval.
Abstract:
There are several challenging statistical problems identified in the regulatory review of large cardiovascular (CV) clinical outcome trials and central nervous system (CNS) trials. The problems can be common or distinct due to disease characteristics and the differences in trial design elements such as endpoints, trial duration, and trial size. In schizophrenia trials, heavy missing data is a big problem. In Alzheimer trials, the endpoints for assessing symptoms and the endpoints for assessing disease progression are essentially the same; it is difficult to construct a good trial design to evaluate a test drug for its ability to slow the disease progression. In CV trials, reliance on a composite endpoint with low event rate makes the trial size so large that it is infeasible to study multiple doses necessary to find the right dose for study patients. These are just a few typical problems. In the past decade, adaptive designs were increasingly used in these disease areas and some challenges occur with respect to that use. Based on our review experiences, group sequential designs (GSDs) have borne many successful stories in CV trials and are also increasingly used for developing treatments targeting CNS diseases. There is also a growing trend of using more advanced unblinded adaptive designs for producing efficacy evidence. Many statistical challenges with these kinds of adaptive designs have been identified through our experiences with the review of regulatory applications and are shared in this article.
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