Addressing Bias in Indirect Treatment Comparisons: A Framework for Identifying TEMs and PVs
Author(s)
Paige Pierce, MSc1, Lytske Bakker, PhD1, Dorothea Heldt, MSc2, Outi Ahdesmaki, BSc, MBA3, Claire Ainsworth, BSc, MSc3.
1OPEN Health HEOR & Market Access, Rotterdam, Netherlands, 2OPEN Health HEOR & Market Access, Berlin, Germany, 3OPEN Health HEOR & Market Access, London, United Kingdom.
1OPEN Health HEOR & Market Access, Rotterdam, Netherlands, 2OPEN Health HEOR & Market Access, Berlin, Germany, 3OPEN Health HEOR & Market Access, London, United Kingdom.
OBJECTIVES: Systematic identification and consideration of treatment effect modifiers (TEMs) and prognostic variables (PVs) in indirect treatment comparisons (ITCs) are essential to address bias and increase the validity of results from comparative effectiveness research. The objective of this study is to review the literature for guidance on TEM/PV identification in ITCs, then provide a practical, actionable framework based on the findings.
METHODS: EU Joint Clinical Assessment (JCA) and National Institute for Health and Care Excellence (NICE) guidelines for ITCs were reviewed for recommendations related to TEM/PV identification. This research was supplemented with a targeted review of published studies seeking to identify TEMs/PVs, involvement of statistical expertise, and a review of recent NICE technology appraisals for reporting of and critique relating to consideration of TEMs/PVs. Consolidating the reviewed evidence, a framework was established for the structured and transparent identification and reporting of TEMs/PVs for ITCs.
RESULTS: Although the importance of comprehensive reporting of the TEMs/PVs identification process is emphasized in both JCA and NICE guidelines, formal guidelines on methodologies are unestablished. Common themes amongst the reviewed evidence base suggested that TEMs/PVs should be identified using an iterative approach, including a structured review of the literature, clinical consultation and empirical analyses. Further, multiple data sources should be leveraged, and when considering inclusion/exclusion based on statistical tests, modest thresholds are recommended to capture all potential TEMs/PVs. Poor quality, or complete lack of identification and adjustment for TEMs/PVs were criticized, thus clear methodological guidelines are essential for ITC execution. A stepwise framework for TEM/PV identification was developed using statistical expertise and recommendations found in the literature review.
CONCLUSIONS: There is an unmet need for clear guidelines on how to identify and report TEMs/PVs for ITCs. The proposed framework will improve ITC quality combining multiple methods in an iterative approach for identification and validation of variables of interest.
METHODS: EU Joint Clinical Assessment (JCA) and National Institute for Health and Care Excellence (NICE) guidelines for ITCs were reviewed for recommendations related to TEM/PV identification. This research was supplemented with a targeted review of published studies seeking to identify TEMs/PVs, involvement of statistical expertise, and a review of recent NICE technology appraisals for reporting of and critique relating to consideration of TEMs/PVs. Consolidating the reviewed evidence, a framework was established for the structured and transparent identification and reporting of TEMs/PVs for ITCs.
RESULTS: Although the importance of comprehensive reporting of the TEMs/PVs identification process is emphasized in both JCA and NICE guidelines, formal guidelines on methodologies are unestablished. Common themes amongst the reviewed evidence base suggested that TEMs/PVs should be identified using an iterative approach, including a structured review of the literature, clinical consultation and empirical analyses. Further, multiple data sources should be leveraged, and when considering inclusion/exclusion based on statistical tests, modest thresholds are recommended to capture all potential TEMs/PVs. Poor quality, or complete lack of identification and adjustment for TEMs/PVs were criticized, thus clear methodological guidelines are essential for ITC execution. A stepwise framework for TEM/PV identification was developed using statistical expertise and recommendations found in the literature review.
CONCLUSIONS: There is an unmet need for clear guidelines on how to identify and report TEMs/PVs for ITCs. The proposed framework will improve ITC quality combining multiple methods in an iterative approach for identification and validation of variables of interest.
Conference/Value in Health Info
2025-11, ISPOR Europe 2025, Glasgow, Scotland
Value in Health, Volume 28, Issue S2
Code
SA6
Topic
Methodological & Statistical Research, Study Approaches
Topic Subcategory
Meta-Analysis & Indirect Comparisons
Disease
No Additional Disease & Conditions/Specialized Treatment Areas