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Objectives

Data maturity in observational studies is essential for ensuring reliability and validity of findings. Inherent biases may indeed lead to unexpected results compared with randomized clinical trials. Interim analyses outputs are typically hard to predict, either because all patients are not yet recruited, or because longer follow-up is required. Thus, endpoints stability in real-world evidence (RWE) must be evaluated largely based on the data in hand maturity assessment. This work proposes a comprehensive approach, from protocol to interpretation of results, for assessing data maturity.

Methods

First, a literature review was conducted to provide exhaustive knowledge on data maturity concepts and considerations. Next, a mock prospective, observational, multi-center study design was developed with time-based recruitment. Patient-level data and associated survival outcomes were simulated for interim and final …