Methods for Analytical Validation of Novel Digital Clinical Measures: Implementation Feasibility Evaluation Using Real-World Datasets.

ABSTRACT:

Background

Sensor-based digital health technologies (sDHTs) are increasingly used to support scientific and clinical decision-making. The digital measures (DMs) they generate offer significant potential to accelerate the drug development timeline, decrease clinical trial costs, and improve access to care. However, choosing an appropriate statistical methodology when conducting analytical validation (AV) of a DM is complicated, particularly for novel DMs, for which appropriate, established reference measures (RMs) may not exist. More understanding of, and a standardized approach to, AV in these scenarios is needed.

Objective

In a prior simulation study, 3 statistical methods were tested for their ability to estimate a simulated relationship between a sDHT-derived DM and sever

SUBMITTER: Turner S 

PROVIDER: S-EPMC12622859 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature