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Impact of Status on the Clinical and Financial Outcomes Among African American Kidney Transplant Recipients

Overview
Publisher Wolters Kluwer
Specialty General Surgery
Date 2022 Oct 7
PMID 36204191
Authors
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Abstract

Methods: The CYP3A5 phenotype status was identified in 438 adult kidney transplant (KTx) recipients (96% were African American) using 3 LoF alleles (, or ). Individuals were categorized as rapid metabolism phenotype without LoF alleles' intermediate phenotype for 1 LoF allele' and slow phenotype for 2 LoF alleles. KTx outcomes (patient/kidney survival and Medicare spending) were determined using linked transplant registry and claims data.

Results: Among the cohort, 23% had a rapid, 47% intermediate, and 30% a slow metabolism phenotype based on genotype. At 3 y, the rate of death censored graft failure and all cause graft failure was highest in the rapid metabolism phenotype and lowest in the intermediate metabolism phenotype group. First-year Medicare reimbursement differed significantly by genotype (rapid: $79 535, intermediate: $72 796, slow: $79 346,  = 0.03). After adjustment for donor and recipient characteristics, care for patients with intermediate metabolism was $4790 less expensive ( = 0.003).

Conclusions: Pharmacogenomic assessment of African American KTx recipients may be useful to guide therapy when as functional variants appear to be associated with differential outcome and spending after transplant.

Citing Articles

Higher number of tacrolimus dose adjustments in kidney transplant recipients who are extensive and intermediate CYP3A5 metabolizers.

Reininger K, Onyeaghala G, Anderson-Haag T, Schladt D, Wu B, Guan W Clin Transplant. 2022; 37(4):e14893.

PMID: 36571802 PMC: 10089949. DOI: 10.1111/ctr.14893.

References
1.
Li Y, van Setten J, Verma S, Lu Y, Holmes M, Gao H . Concept and design of a genome-wide association genotyping array tailored for transplantation-specific studies. Genome Med. 2015; 7:90. PMC: 4589899. DOI: 10.1186/s13073-015-0211-x. View

2.
Francke M, Andrews L, Le H, van de Wetering J, Clahsen-van Groningen M, van Gelder T . Avoiding Tacrolimus Underexposure and Overexposure with a Dosing Algorithm for Renal Transplant Recipients: A Single Arm Prospective Intervention Trial. Clin Pharmacol Ther. 2021; 110(1):169-178. PMC: 8359222. DOI: 10.1002/cpt.2163. View

3.
Schold J, Gregg J, Harman J, Hall A, Patton P, Meier-Kriesche H . Barriers to evaluation and wait listing for kidney transplantation. Clin J Am Soc Nephrol. 2011; 6(7):1760-7. DOI: 10.2215/CJN.08620910. View

4.
Mohamed M, Schladt D, Guan W, Wu B, van Setten J, Keating B . Tacrolimus troughs and genetic determinants of metabolism in kidney transplant recipients: A comparison of four ancestry groups. Am J Transplant. 2019; 19(10):2795-2804. PMC: 6763344. DOI: 10.1111/ajt.15385. View

5.
Luo X, Zhu L, Cai N, Zheng L, Cheng Z . Prediction of tacrolimus metabolism and dosage requirements based on CYP3A4 phenotype and CYP3A5(*)3 genotype in Chinese renal transplant recipients. Acta Pharmacol Sin. 2016; 37(4):555-60. PMC: 4820801. DOI: 10.1038/aps.2015.163. View