Background: Pharmacogenetic testing can provide predictive insights about the efficacy and safety of drugs used in cancer treatment. Although many drug-gene associations have been reported in the literature, the strength of evidence supporting each association can vary significantly. Even among the subgroup of drugs classified by the PharmGKB database to have a high or moderate level of evidence, there is limited information regarding the economic value of pharmacogenetic testing.
Objectives: To: (a) summarize the available pharmacoeconomic evidence assessing the value of pharmacogenetic testing for cancer drugs with clinically relevant drug-gene associations; (b) determine the quality of the studies that contain this evidence; and (c) discuss the quality of this evidence with respect to the level of evidence of the drug-gene associations.
Methods: The PharmGKB database was used to identify cancer drugs with clinically relevant drug-gene associations graded high (1A, 1B) or moderate (2A, 2B). A systematic literature review was conducted using these drugs. Ovid MEDLINE and Embase databases were searched to identify cost-effectiveness, cost-utility, or cost-minimization studies comparing pharmacogenetic testing to an alternative. Cost and effect values from every relevant comparison within the studies were extracted, and the incremental cost-effectiveness ratio (ICER) was either extracted or calculated for each comparison. Quality assessment was conducted for each study using the Quality of Health Economic Studies (QHES) instrument. Qualitative synthesis was used to summarize the data.
Results: The search yielded 2,191 citations, of which 35 studies met the inclusion criteria. Pharmacoeconomic studies were available for the following drugs from the PharmGKB database: fluoropyrimidine, 6-mercaptopurine, irinotecan, carboplatin, cisplatin, erlotinib, gefitinib, cetuximab, panitumumab, and trastuzumab. The studies were conducted in Asia, Europe, Canada, the United States, and Mexico and reported cost-utility, cost-effectiveness, and cost-minimization outcomes. The mean QHES score was 80 (SD = 22) for the studies of drug-gene pairs with high (1A, 1B) and moderate (2A, 2B) levels of evidence (1A = 82, 1B = 93, 2A = 71, and 2B = 74). There was variation across studies in terms of reporting. 109 relevant comparisons were identified within the studies. Of those that reported cost per life-year or cost per quality-adjusted life-year (n = 58 comparisons), pharmacogenetic testing was dominant in 21% overall and 42%, 21%, 17%, and 5% of the comparisons in Asia, Europe, Canada, and the United States, respectively. Variability was observed in the ICER values regardless of geographic region or drug. Pharmacogenetic testing was cost saving in 17 of 19 cost-minimization comparisons and was favored most frequently when compared with genetically indiscriminate strategies containing the drug of interest.
Conclusions: There was mixed evidence regarding the value of pharmacogenetic testing to guide cancer treatment. For future pharmacogenomic-related economic studies, we recommend prioritizing clinically relevant drug-gene associations and greater adherence to available best practice guidelines for conducting and reporting economic evaluation studies.
Disclosures: No outside funding supported this review. Part of Hussain's research time was supported by a Merit Review Award (I01 BX000545), Medical Research Service, U.S. Department of Veterans Affairs. Hussain also reports personal fees from Bristol-Myers Squibb, AstraZeneca, Novartis, Bayer HealthCare Pharmaceuticals, and France Foundation, outside the submitted work. Onukwugha reports grants from Pfizer and Bayer HealthCare Pharmaceuticals, along with advisory board fees from Novo Nordisk, outside the submitted work. Faruque, Neuberger, and Noh have nothing to disclose.