Methods for reducing uncertainty in personalized medicine

Methods for reducing uncertainty in personalized medicine Gregory F. Guzauskas Chair of the Supervisory Committee: Professor David L. Veenstra, PharmD, PhD Department of Pharmacy Background. Evidence uncertainty and paternalistic practices in genomic medicine lead to suboptimal decision-making circumstances, and may result in unfavorable patient outcomes. Reducing decision uncertainty, combined with a shared (patient and clinician) decision-making approach, is believed to result in better overall treatment decisions that better meet patients’ needs and fewer negative consequences. Objective. (1) To demonstrate the use of value of information analysis to estimate the societal value and research priority of a trial studying pharmacogenomicguided antiplatelet selection, and (2) to obtain key stakeholder opinions on the necessity and feasibility of a shared decision tool for whole genome sequencing. Methods. Objective (1) was accomplished using an expected value of sample information (EVSI) approach. Objective (2) was accomplished using qualitative analysis of key informant interview transcripts. See additional abstracts for more information. Results. (1) Substantial value could be realized by performing a pharmacogenomic clinical trial, although reducing uncertainty in the pharmacogenomic association was less valuable than reducing uncertainty in adverse event outcomes. (2) Genetic services providers were open to shared decision-making tools and would use the tool if validated. Conclusions. Decision tools are potentially useful for helping genetics stakeholders assess uncertain evidence thresholds, make policy choices, or facilitate treatment decisions. OVERALL INTRODUCTION The ability of decision tools to create order among the chaos of genomic medicine is appealing, and thus began the journey of this dissertation research. Our first project in this field was a quantitative risk-benefit assessment of clopidogrel, a recently off-patent antiplatelet drug pharmacogenomically associated with poor thrombotic outcomes, versus prasugrel, a new antiplatelet drug without a pharmacogenomic association but packing increased bleeding risk, and versus a hypothetical pharmacogenomic strategy, in acute coronary syndrome patients. We found that the pharmacogenomic strategy was preferred in most model simulations, however uncertainty in the optimal strategy remained, and this analysis did not factor costs. Building from this analysis, we turned our attention to estimating the potential value of conducting a clinical trial, based on a recent failed randomized controlled trial and our previous risk-benefit model. In Chapter 1, we used value of information (VOI) methodology to assess the societal benefit a clinical trial would provide by reducing current decision uncertainty regarding the optimal antiplatelet therapy strategy, and we were able to comment on whether the current evidence base is sufficient to more widely implement pre-therapy pharmacogenomic testing or if a future trial would be worth the substantial investment it would require. We also previously engaged genetics services stakeholders directly to assess their interest in using decision tools to aid their policy decisions. (1) An important finding of this study was the concern genetic services stakeholders have regarding multiplex testing strategies. The implications of these concerns were clear: focusing future decision-analytic modeling efforts on single-gene test interventions was seen as inessential, and stakeholders preferred that our efforts be focused on modeling array-based or whole genome sequencing (WGS) technologies. Unfortunately, modeling multiplex genomic testing for multiple disorders is a significant challenge for which traditional decision-analytic approaches are ill equipped. Nonetheless, it gave us inspiration to draft a novel tool for assessing WGS that involves assigning clinically relevant categories to genomic loci that allow for a shared decision-making-driven, streamlined approach to return of WGS results. We explored the possibility of further research on this idea in Chapter 2. In this study, we conducted a qualitative analysis of 14 key informant genetics services providers (3 clinical geneticists, 4 genetic counselors, 2 molecular geneticists, and 5 cytogeneticists) to investigate the impacts of WGS on genetics services practice, the value of shared decision-making for genomic results, and the utility of a hypothetical decision tool to combine the two. Overall impressions and concluding statements can be found in the final chapter of this dissertation. Is it worth investing in a prospective randomized trial to inform pharmacogenomic testing guidelines? CYP2C19 and clopidogrel as a case study Gregory F. Guzauskas, MSPH Dissertation Chapter 1