Methodological approaches in the economic evaluation of prognostic and predictive companion diagnostics: a systematic scoping review
Year: 2025
Type: article
Study design: Systematic Review
Abstract: INTRODUCTION: This systematic scoping review aimed to identify and analyze current methodological approaches used in model-based economic evaluations (EEs) of prognostic and predictive companion diagnostics (pCDx), highlighting methodological gaps and challenges. METHODS: Systematic searches were conducted in PubMed and Scopus (January 2009-March 2023). Included studies were model-based EEs, methodological papers, or reviews specifically addressing prognostic or predictive CDx. Data extraction followed the modified CHEERS checklist. Results were synthesized narratively across six methodological domains. No formal risk of bias assessment was done per scoping review conventions. RESULTS: Eighty-eight studies were included, of which 60 were model-based EEs. Most studies utilized Markov cohort models (37%) or decision tree-Markov hybrids (30%). Quality-adjusted life-years (QALYs) were the main outcome (88%). Only 15% of studies derived clinical utility from randomized controlled trials, and fewer than half explicitly modeled diagnostic accuracy. Methodological limitations included inconsistent modeling of real-world test-treatment pathways, insufficient consideration of pretest probabilities, diagnostic thresholds, and inadequate uncertainty analyses. CONCLUSIONS: This review identified variability and methodological gaps in economic evaluations of pCDx. Standardizing evaluation methods, integrating real-world evidence, and systematically considering the diagnostic accuracy and uncertainty could improve the robustness of pCDx evaluations. Limitations of this study included overrepresentation of breast cancer studies. REGISTRATION: OSF Registries (22 February 2023) DOI 10.17605/OSF.IO/GVFMQ.
Institution: University of Eastern Finland
Language: English
Subfield: Economics and Econometrics
Domain: Social Sciences
Open Access status: hybrid
OpenAlex ID: W4411327335