Evidence integration and bridging methodologies for high-risk and innovative medical devices and in vitro diagnostic medical devices: a scoping review

High-risk and innovative medical devices, as well as in vitro diagnostic medical devices, often pose challenges for conventional clinical evaluation because randomized clinical trials may be difficult to conduct. As a result, methodologies for integrating heterogeneous evidence and conducting bridging studies are becoming increasingly important in regulatory decision-making and health technology evaluation.

To map methodologies for evidence integration and bridging studies in high-risk and innovative medical devices and in vitro diagnostic medical devices, and to identify key methodological and regulatory challenges.

A scoping review following Joanna Briggs Institute guidance was conducted using peer-reviewed and grey literature published from 2017 onward. Bibliographic databases, industry resources, and preprint platforms were searched. Included records addressed methods for comparing or integrating evidence for medical devices and in vitro diagnostic medical devices. Data extraction and synthesis were supported by artificial-intelligence-assisted analysis, with human verification.

Nineteen studies were included. Identified methods included Bayesian evidence synthesis, adaptive trial designs, indirect comparisons, propensity score methods, real-world data integration, linked evidence frameworks, in silico approaches, and bridging studies. These methods support evaluation when conventional randomized clinical trials are limited or infeasible. Major challenges included evidence heterogeneity, bias, limited methodological standardization, and variable regulatory acceptance, particularly for in vitro diagnostic medical devices and digital technologies.

Evidence integration methodologies are increasingly important in the evaluation of innovative medical devices and in vitro diagnostic medical devices. However, clearer methodological standards and harmonized guidance are still needed to support consistent and reliable use of heterogeneous evidence.

The scoping review was registered with the Open Science Framework (OSF). The Unique Identifier is 10.17605/OSF.IO/XNBSP, and the registration is publicly available at https://doi.org/10.17605/OSF.IO/XNBSP.