Article Text

Evidence used in model-based economic evaluations for evaluating pharmacogenetic and pharmacogenomic tests: a systematic review protocol
  1. Jaime L Peters1,
  2. Chris Cooper1,
  3. James Buchanan2
  1. 1Evidence Synthesis & Modelling for Health Improvement (ESMI), University of Exeter Medical School, Exeter, UK
  2. 2Nuffield Department of Population Health, Health Economics Research Centre, University of Oxford, Oxford, UK
  1. Correspondence to Dr Jaime L Peters; j.peters{at}exeter.ac.uk

Abstract

Introduction Decision models can be used to conduct economic evaluations of new pharmacogenetic and pharmacogenomic tests to ensure they offer value for money to healthcare systems. These models require a great deal of evidence, yet research suggests the evidence used is diverse and of uncertain quality. By conducting a systematic review, we aim to investigate the test-related evidence used to inform decision models developed for the economic evaluation of genetic tests.

Methods and analysis We will search electronic databases including MEDLINE, EMBASE and NHS EEDs to identify model-based economic evaluations of pharmacogenetic and pharmacogenomic tests. The search will not be limited by language or date. Title and abstract screening will be conducted independently by 2 reviewers, with screening of full texts and data extraction conducted by 1 reviewer, and checked by another. Characteristics of the decision problem, the decision model and the test evidence used to inform the model will be extracted. Specifically, we will identify the reported evidence sources for the test-related evidence used, describe the study design and how the evidence was identified. A checklist developed specifically for decision analytic models will be used to critically appraise the models described in these studies. Variations in the test evidence used in the decision models will be explored across the included studies, and we will identify gaps in the evidence in terms of both quantity and quality.

Dissemination The findings of this work will be disseminated via a peer-reviewed journal publication and at national and international conferences.

  • GENETICS
  • HEALTH ECONOMICS
  • STATISTICS & RESEARCH METHODS

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