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Published on: September 20, 2019
[Multination clinical trials: what is the relevance and what are the lessons from across-country differences?]
Insights
Multinational clinical trials require large patient populations due to effective cardiovascular treatments. Interpreting country-specific results demands cautious methodology and biological plausibility to avoid errors.
Area of Science:
- Cardiovascular medicine
- Clinical trial methodology
Background:
- Evidence-based treatments have reduced cardiovascular events, necessitating large patient cohorts for research.
- Multinational studies are now essential for robust clinical trial outcomes.
Purpose of the Study:
- To highlight the challenges in interpreting country-specific results from multinational cardiovascular studies.
- To emphasize the need for cautious interpretation of subgroup analyses in clinical trials.
Main Methods:
- Discussion of methodologies for analyzing data from large-scale, multinational clinical trials.
- Emphasis on the importance of biological plausibility and external validation for observed differences.
Main Results:
- Differences in trial results across countries are common in cardiovascular research.
- Inappropriate interpretation of these differences can lead to erroneous conclusions and flawed regulatory decisions.
Conclusions:
- Interpreting country-specific variations in multinational trials requires rigorous statistical methods and biological rationale.
- Further research and cross-study validation are crucial for reliable interpretation of clinical trial data.
Abstract:
In the cardiovascular area, the rate of occurrence of relevant clinical events decreased over the last decades due to the large adoption of evidence-based treatments. This implies that large numbers of patients are needed to provide reliable answers to research open questions. Therefore, the conduction of multinational large-scale studies became necessary. In this setting, it is not infrequent to find relevant differences in the trial results across countries. The interpretation of these differences should be extremely cautious to avoid the well known mistakes related to subgroup analyses. To believe in differences, it is necessary to adopt appropriate methodologies in the analysis of data but, even more important, to find a biological plausibility that can explain the observed difference. A further confirmation from other studies can also help in the interpretation. In the literature there are some examples of such differences that, in some cases, produced erroneous interpretations of the results of a trial, and also induced regulatory authorities to take decisions based on these differences.
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