Impact of Pharmacogenomic Information on Values of Care and Quality of Life Associated with Codeine and Tramadol-Related Adverse Drug Events

Ye Zhu; Guilherme S Lopes; Suzette J Bielinski; Bijan J Borah; Nicholas B Larson; Ann M Moyer; Janet E Olson; Liewei Wang; Richard Weinshilboum; Jennifer L St Sauver

doi:10.1016/j.mayocpiqo.2020.08.009

Impact of Pharmacogenomic Information on Values of Care and Quality of Life Associated with Codeine and Tramadol-Related Adverse Drug Events

Mayo Clin Proc Innov Qual Outcomes. 2021 Jan 13;5(1):35-45. doi: 10.1016/j.mayocpiqo.2020.08.009. eCollection 2021 Feb.

Authors

Ye Zhu^{1

2}, Guilherme S Lopes^{3

4}, Suzette J Bielinski³, Bijan J Borah^{1

2}, Nicholas B Larson⁴, Ann M Moyer⁵, Janet E Olson³, Liewei Wang⁶, Richard Weinshilboum⁶, Jennifer L St Sauver³

Affiliations

¹ Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN.
² Division of Health Care Policy and Research, Department of Health Sciences Research, Mayo Clinic, Rochester, MN.
³ Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic, Rochester, MN.
⁴ Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, MN.
⁵ Division of Clinical Biochemistry & Immunology, Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN.
⁶ Division of Clinical Pharmacology, Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, Rochester, MN.

Abstract

Objective: To assess the potential impact of Pharmacogenomic (PGx) variation in cytochrome P450 2D6 (CYP2D6) enzyme function, using loss in quality-adjusted life years (QALYs) associated with treatment problems, and the willingness to pay to avoid treatment problems from patients' and payers' perspectives.

Patients and methods: The study included patients prescribed tramadol or codeine, or both, between January 1, 2005, and December 31, 2017. Demographic information and adverse drug events, including adverse drug events and poor pain control, were collected from the electronic health records using natural language processing techniques and review by trained abstractors. Patients' willingness to pay and QALY estimates were based on comprehensive literature review. The CYP2D6 phenotypes were divided into 4 groups: ultra-rapid metabolizers, normal metabolizers, intermediate metabolizers, and poor metabolizers.

Results: Among the 2860 identified patients, 63 (2%) were ultrarapid metabolizers, 1449 (50%) were normal metabolizers, 1155 (40%) were intermediate metabolizers, and 193 (7%) were poor metabolizers. The patients' average estimated willingness-to-pay value to avoid treatment problems was $23 per month; poor metabolizers developed problems with the highest estimated willingness-to-pay value ($32 per month). The mean QALY loss among all patients was 0.024 QALYs (8.8 healthy days); poor metabolizers had the highest loss (0.027 QALYs, 9.9 healthy days).

Conclusion: Patients with various phenotypes developed different treatment problem profiles. Poor CYP2D6 metabolizers developed problems with highest willingness to pay, and they might potentially benefit most from PGx-guided treatment and problem prevention.

Keywords: ADE, adverse drug event; CYP2D6, Cytochrome P450 2D6; PGx, pharmacogenomics; QALY, quality-adjusted life year; REP, Rochester Epidemiology Project; RIGHT, Right Drug; Right Dose, Right Time-Using Genomic Data to Individualize Treatment.