Understanding the Heterogeneity of the Patients Populations by Subgroup Analyses from the Past Trials to Improve Future Study Design
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*Yunfan Deng, FDA      Daphne T.Y. Lin, FDA/CDER     


Subgroup analyses are generally regarded with suspicion because they are less reliable than analyses based on the overall population. However, the common underlying assumption in most clinical trials is that the investigating agents would be equally efficacious in all kinds of patients without considering the possible heterogeneity in drug efficacy. Is this the right assumption? If the heterogeneity of treatment effects does exist, pooling relatively consistent outcomes of similar subgroups from different trials would help us gaining better understanding of a certain disease or a specific intervention and could facilitate designing future trials with more precisely targeted patient population. Our talk will illustrate how understanding the heterogeneity of the patient populations can help to improve future study design by using past severe sepsis trials as an example. By implementing different subgroup analyses approaches for the pooled dataset of several past trials, our goal is to identify subgroups of patients that might potentially benefit from certain experimental agents. We hope our research on the heterogeneity patient populations would help to develop future clinical trial in certain disease area that minimizes risks to the patients while enhancing the quality of the evidence that could be collected.