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Background: Lung cancer is among the top causes of cancer-related deaths. Epidermal growth factor receptor (EGFR)-tyrosine kinase inhibitors can increase progression-free survival compared with standard chemotherapy in patients with EGFR mutation-positive advanced non-small cell lung cancer (NSCLC)., Objective: The aim of the study was to evaluate the cost-effectiveness of EGFR mutation analysis and first-line therapy with erlotinib for mutation-positive patients compared with non-individualized standard chemotherapy from the perspective of German statutory health insurance., Methods: A state transition model was developed for a time horizon of 10 years (reference year 2014). Data sources were published data from the European Tarceva versus Chemotherapy (EURTAC) randomized trial for drug efficacy and safety and German cost data. We additionally performed deterministic, probabilistic and structural sensitivity analyses., Results: The individualized strategy incurred 0.013 additional quality-adjusted life-years (QALYs) and additional costs of € 200, yielding an incremental cost-effectiveness ratio (ICER) of € 15,577/QALY. Results were most sensitive to uncertainty in survival curves and changes in utility values. Cross-validating health utility estimates with recent German data increased the ICER to about € 58,000/QALY. The probabilistic sensitivity analysis indicated that the individualized strategy is cost-effective, with a probability exceeding 50 % for a range of possible willingness-to-pay thresholds., Limitations: The uncertainty of the predicted survival curves is substantial, particularly for overall survival, which was not a primary endpoint in the EURTAC study. Also, there is limited data on quality of life in metastatic lung cancer patients., Conclusions: Individualized therapy based on EGFR mutation status has the potential to provide a cost-effective alternative to non-individualized care for patients with advanced adenocarcinoma. Further clinical research is needed to confirm these results.

Context: This study assesses if, and how, existing methods for economic evaluation are applicable to the evaluation of personalized medicine (PM) and, if not, where extension to methods may be required., Methods: A structured workshop was held with a predefined group of experts (n = 47), and was run using a modified nominal group technique. Workshop findings were recorded using extensive note taking, and summarized using thematic data analysis. The workshop was complemented by structured literature searches., Results: The key finding emerging from the workshop, using an economic perspective, was that two distinct, but linked, interpretations of the concept of PM exist (personalization by 'physiology' or 'preferences'). These interpretations involve specific challenges for the design and conduct of economic evaluations. Existing evaluative (extra-welfarist) frameworks were generally considered appropriate for evaluating PM. When 'personalization' is viewed as using physiological biomarkers, challenges include representing complex care pathways; representing spillover effects; meeting data requirements such as evidence on heterogeneity; and choosing appropriate time horizons for the value of further research in uncertainty analysis. When viewed as tailoring medicine to patient preferences, further work is needed regarding revealed preferences, e.g. treatment (non)adherence; stated preferences, e.g. risk interpretation and attitude; consideration of heterogeneity in preferences; and the appropriate framework (welfarism vs. extra-welfarism) to incorporate non-health benefits., Conclusions: Ideally, economic evaluations should take account of both interpretations of PM and consider physiology and preferences. It is important for decision makers to be cognizant of the issues involved with the economic evaluation of PM to appropriately interpret the evidence and target future research funding.

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.

Background: Recently, individualized or personalized medicine (PM) has become a buzz word in the academic as well as public debate surrounding health care. However, PM lacks a clear definition and is open to interpretation. This conceptual vagueness complicates public discourse on chances, risks and limits of PM. Furthermore, stakeholders might use it to further their respective interests and preferences. For these reasons it is important to have a shared understanding of PM. In this paper, we present a sufficiently precise as well as adequate definition of PM with the potential of wide acceptance., Methods: For this purpose, in a first step a systematic literature review was conducted to understand how PM is actually used in scientific practice. PubMed was searched using the keywords "individualized medicine", "individualised medicine", "personalized medicine" and "personalised medicine" connected by the Boolean operator OR. A data extraction tabloid was developed putting forward a means/ends-division. Full-texts of articles containing the search terms in title or abstract were screened for definitions. Definitions were extracted; according to the means/ends distinction their elements were assigned to the corresponding category. To reduce complexity of the resulting list, summary categories were developed inductively from the data using thematic analysis. In a second step, six well-known criteria for adequate definitions were applied to these categories to derive a so-called precising definition., Results: We identified 2457 articles containing the terms PM in title or abstract. Of those 683 contained a definition of PM and were thus included in our review. 1459 ends and 1025 means were found in the definitions. From these we derived the precising definition: PM seeks to improve stratification and timing of health care by utilizing biological information and biomarkers on the level of molecular disease pathways, genetics, proteomics as well as metabolomics., Conclusions: Our definition includes the aspects that are specific for developments labeled as PM while, on the other hand, recognizing the limits of these developments. Furthermore, it is supported by the quantitative analysis of PM definitions in the literature, which suggests that it it is widely acceptable and thus has the potential to avoid the above mentioned issues.