OBJECTIVES : The field of pharmacogenomics (PGx) studies the inherited genetic variations of individuals in drug metabolism, distribution and interactions with the therapeutic targets. PGx testing can potentially help improve efficiency and accuracy in individualizing drug therapy. This study is to explore the evidence on the timing of PGx testing (preemptive or reactive PGx testing compared to usual care) in cardiovascular disease (CVD) management.

METHODS : We developed a decision analytic model composed of a short-term decision tree and life-time Markov model to compare three strategies to implement panel-PGx testing: preemptive, reactive or usual care. The model incorporated PGx-guided treatment strategies following the guidelines from the Clinical Pharmacogenetics Implementation Consortium. The gene-drug pairs assessed were: CYP2C19 (clopidogrel), CYP2C9/VKORC1 (warfarin) and SLCO1B1 (statin). The target population was a hypothetical cohort of 10,000 patients with high risks of CVD, and with the same age and race distribution as with the US population of aged 45-year-old and above. All model inputs were from the similar population captured from the literature. We also conducted scenario analyses to assess whether cost-effectiveness results vary by age, gender, race, risk level and the follow-up duration.

RESULTS : Compared to usual care, reactive PGx testing yielded an ICER of $15,085/QALY, while preemptive PGx testing yielded $251,288/QALY; preemptive PGx testing yielded an additional 0.6 QALYs as opposed to 0.2 QALYs for reactive PGx testing; reactive PGx testing increased the average lifetime costs by $3,385, while preemptive PGx testing resulted in average costs of $138,403. The sensitivity analysis sugested that QALYs and the cost-effectiveness are largely affected by age, race, risk level and study time frame.

CONCLUSIONS : The results suggested that reactive PGx testing overall is cost-effective and is preferred over usual care. Preemptive testing provides the highest QALYs, however resulted in substantially higher costs.