OP179 Quantitative Evidence Synthesis Methods For Assessing The Effectiveness Of Treatment Sequences For Clinical And Economic Decision-Making: Methodology Review

Introduction The sequential use of alternative treatments for chronic conditions represents a complex, dynamic intervention pathway; previous treatment and patient characteristics affect both choice effectiveness subsequent treatments. Evidence synthesis methods that produce the least biased estimates treatment-sequencing effects are required to inform reliable clinical policy decision-making. A comprehensive review was conducted establish what existing available, outline assumptions they make, identify their shortcomings. Methods encompassed meta-analytic techniques decision-analytic modelling, any disease condition, type sequence, but not diagnostic tests, screening, or monitoring. It focused on estimation did consider impact sequencing costs utility values. Results included ninety-one studies. Treatment-sequencing is usually dealt with at decision-modelling stage rarely addressed using evidence methodology effectiveness. Most meta-analyses discrete treatments, sometimes stratified by line therapy. Prospective trials scarce. In absence, there no single best way evaluate sequences, rather range approaches, each which has advantages disadvantages influenced available decision problem. Due scarcity data modelling studies generally apply simplifying taxonomy all possible developed, providing unique resource aid critique models. Conclusions evolution network meta-analysis in HTA demonstrates decision-making should account multiple many conditions. However, yet be accounted within evaluations. Economic often based assumption independence. This can lead misrepresentation true level uncertainty, potential bias estimating cost and, eventually, wrong decision.