IDENTIFICATION OF TREATMENT EFFECT MODIFIERS (TEMS) AND PROGNOSTIC FACTORS (PFS) IN MATCHING-ADJUSTED INDIRECT COMPARISONS (MAICS)- A SYSTEMATIC LITERATURE REVIEW (SLR)
Author(s)
Rob Bonemei, BSc, MSc, PhD1, Leticia Barcena, BSc1, Conor McCloskey, BSc, PhD1, Sunita Nair, PhD2.
1Clarivate, London, United Kingdom, 2Clarivate, Bangalore, India.
1Clarivate, London, United Kingdom, 2Clarivate, Bangalore, India.
OBJECTIVES: MAICs are increasingly used in health technology assessment when head-to-head randomised controlled trials (RCT) evidence is unavailable. NICE guidance states that anchored MAICs should adjust for all TEMs, while PFs should not be accounted for to avoid over-matching while unanchored MAICs require adjustment for both TEMs and PFs. The aim of this SLR is to explore how the identification as well as the differentiation of TEMs and PFs has been reported in MAICs.
METHODS: We conducted a SLR following the PRISMA guidelines to identify MAICs published in the last five years in oncology. Searches were run on 16 April 2026 in MEDLINE, Embase, and Cochrane library (via OVID), limited to full English publications. Publications were screened and data extracted by two independent reviewers.
RESULTS: Thirty-two publications reporting MAICs were included, comprising 14 (44%) anchored MAICs, 16 (50%) unanchored MAICs, and 2 (6%) reporting both approaches. Twelve publications (38%) reported identifying TEMs and PFs conducting a review, which was described as a SLR in one, targeted literature review in five, and review of the literature in six, in combination with consultation with clinical experts. Four publications (13%) combined evidence from the published literature with expert consultation, while one publication (3%) reported expert consultation alongside empirical identification of TEMs. One publication (3%) relied solely on published literature. The approach used to identify TEMs and PFs was unclear in 14 publications (44%). Only three publications (9%), all of which reported anchored MAICs, described using Cox regression analyses to distinguish TEMs from PFs.
CONCLUSIONS: There is substantial heterogeneity and poor transparency in the identification and reporting of TEMs and PFs across published MAICs, highlighting a critical need for transparent methods for identifying and justifying TEMs and PFs in MAIC analyses to align with HTA expectations and to support reimbursement and access.
METHODS: We conducted a SLR following the PRISMA guidelines to identify MAICs published in the last five years in oncology. Searches were run on 16 April 2026 in MEDLINE, Embase, and Cochrane library (via OVID), limited to full English publications. Publications were screened and data extracted by two independent reviewers.
RESULTS: Thirty-two publications reporting MAICs were included, comprising 14 (44%) anchored MAICs, 16 (50%) unanchored MAICs, and 2 (6%) reporting both approaches. Twelve publications (38%) reported identifying TEMs and PFs conducting a review, which was described as a SLR in one, targeted literature review in five, and review of the literature in six, in combination with consultation with clinical experts. Four publications (13%) combined evidence from the published literature with expert consultation, while one publication (3%) reported expert consultation alongside empirical identification of TEMs. One publication (3%) relied solely on published literature. The approach used to identify TEMs and PFs was unclear in 14 publications (44%). Only three publications (9%), all of which reported anchored MAICs, described using Cox regression analyses to distinguish TEMs from PFs.
CONCLUSIONS: There is substantial heterogeneity and poor transparency in the identification and reporting of TEMs and PFs across published MAICs, highlighting a critical need for transparent methods for identifying and justifying TEMs and PFs in MAIC analyses to align with HTA expectations and to support reimbursement and access.
Conference/Value in Health Info
2026-11, ISPOR Europe 2026, Vienna, Austria
Value in Health, Volume 29, Issue 12S
Code
MSR203
Topic
Health Technology Assessment, Methodological & Statistical Research, Study Approaches
Disease
No Additional Disease & Conditions/Specialized Treatment Areas, Oncology