A SUMMARY OF GUIDANCE AND METHODS FOR IDENTIFICATION OF PROGNOSTIC FACTORS IN A SYSTEMATIC REVIEW FOR A JCA DOSSIER EVIDENCE SYNTHESIS WORKFLOW

Author(s)

Jonathon Briggs, PhD1, Walter Bouwmeester, PhD1, Milica Jevdjevic, PhD1, Andrew Frederickson, MS2.
1Precision AQ, London, United Kingdom, 2Precision AQ, Gladstone, NJ, USA.
OBJECTIVES: In the absence of randomized controlled trials directly comparing relevant treatments, population adjusted indirect comparisons (PAICs) can be used to estimate differences in treatment effects adjusted for between study differences in patient characteristics. The Joint Clinical Assessment (JCA) dossier guidance requires a systematic review to identify all prognostic factors, however specific guidance is not provided.To identify and summarize methodological guidance on conducting prognostic factors literature reviews and assess the applicability of the current guidance and recommendations for conducting a prognostic factor review in a JCA dossier evidence synthesis workflow.
METHODS: Guidelines for prognostic factor reviews were identified in searches of prognostic factor systematic reviews, prognostic factor methods publications and the Cochrane Handbook for systematic reviews. Key guidance for conducting prognostic factor reviews were compared and evaluated within the context of a wider JCA dossier evidence synthesis workflow.
RESULTS: Guidance on designing and conducting a prognostic factor review covered common aspects of literature reviews including designing a research question, study identification and data extraction. Guidance specific to prognostic factor review design and recommended search filters were outlined in the Cochrane Handbook for systematic reviews of prognostic research and prediction models. Key items to consider for data extraction and assessing the validity of prognostic models (model design, predictor handling and selection, model performance measures, predictor/ prognostic factors and outcomes) were described in the CHARMS checklist and the PROBAST tool is used to assess bias in prediction model design.
CONCLUSIONS: Current JCA guidance on identification of prognostic factors lacks detail on specific methods for prognostic factor systematic reviews. However, current guidance and tools can ensure high quality reviews conducted to identify prognostic factors and inform ITCs in a JCA dossier.

Conference/Value in Health Info

2026-11, ISPOR Europe 2026, Vienna, Austria

Value in Health, Volume 29, Issue 12S

Code

SA106

Topic

Health Technology Assessment, Methodological & Statistical Research, Study Approaches

Topic Subcategory

Literature Review & Synthesis, Meta-Analysis & Indirect Comparisons

Disease

No Additional Disease & Conditions/Specialized Treatment Areas

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