Is individualized medicine more cost-effective? A systematic review.

Background: Individualized medicine (IM) is a rapidly evolving field that is associated with both visions of more effective care at lower costs and fears of highly priced, low-value interventions. It is unclear which view is supported by the current evidence. Objective: Our objective was to systematically review the health economic evidence related to IM and to derive general statements on its cost-effectiveness. Data sources: A literature search of MEDLINE database for English- and German-language studies was conducted. Study appraisal and synthesis method: Cost-effectiveness and cost-utility studies for technologies meeting the MEDLINE medical subject headings (MeSH) definition of IM (genetically targeted interventions) were reviewed. This was followed by a standardized extraction of general study characteristics and cost-effectiveness results. Results: Most of the 84 studies included in the synthesis were from the USA (n = 43, 51 %), cost-utility studies (n = 66, 79 %), and published since 2005 (n = 60, 71 %). The results ranged from dominant to dominated. The median value (cost-utility studies) was calculated to be rounded $US22,000 per quality-adjusted life year (QALY) gained (adjusted to$US, year 2008 values), which is equal to the rounded median cost-effectiveness in the peer-reviewed English-language literature according to a recent review. Many studies reported more than one strategy of IM with highly varying cost-effectiveness ratios. Generally, results differed according to test type, and tests for disease prognosis or screening appeared to be more favorable than tests to stratify patients by response or by risk of adverse effects. However, these results were not significant. Limitations: Different definitions of IM could have been used. Quality assessment of the studies was restricted to analyzing transparency. Conclusions: IM neither seems to display superior cost-effectiveness than other types of medical interventions nor to be economically inferior. Instead, rather than 'whether' healthcare was individualized, the question of 'how' it was individualized was of economic relevance

A systematic review of the quality of economic models comparing thrombosis inhibitors in patients with acute coronary syndrome undergoing percutaneous coronary intervention.

Background: Thrombosis inhibitors can be used to treat acute coronary syndromes (ACS). However, there are various alternative treatment strategies, of which some have been compared using health economic decision models. Objective: To assess the quality of health economic decision models comparing thrombosis inhibitors in patients with ACS undergoing percutaneous coronary intervention, and to identify areas for quality improvement. Data Sources: The literature databases MEDLINE, EMBASE, EconLit, National Health Service Economic Evaluation Database (NHS EED), Database of Abstracts of Reviews of Effects (DARE) and Health Technology Assessment (HTA). Study Appraisal and Synthesis Methods: A review of the quality of health economic decision models was conducted by two independent reviewers, using the Philips checklist. Results: Twenty-one relevant studies were identified. Differences were apparent regarding the model type (six decision trees, four Markov models, eight combinations, three undefined models), the model structure (types of events, Markov states) and the incorporation of data (efficacy, cost and utility data). Critical issues were the absence of particular events (e.g. thrombocytopenia, stroke) and questionable usage of utility values within some studies. Limitations: As we restricted our search to health economic decision models comparing thrombosis inhibitors, interesting aspects related to the quality of studies of adjacent medical areas that compared stents or procedures could have been missed. Conclusions: This review identified areas where recommendations are indicated regarding the quality of future ACS decision models. For example, all critical events and relevant treatment options should be included. Models also need to allow for changing event probabilities to correctly reflect ACS and to incorporate appropriate, age-specific utility values and decrements when conducting cost-utility analyses