Abstract
Conducting older adult-specific clinical trials can help overcome the lack of clinical evidence for older adults due to their underrepresentation in clinical trials. These trials can help examine potential treatment heterogeneity between older versus younger patients, however there is a risk of failure that trial sponsors should take into account before making funding decisions. We aimed to develop a machine learning model that predicts trial failure among older adult-specific clinical trials using trial-level factors.
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