Predicting steady‐state endoxifen plasma concentrations in breast cancer patients by CYP2D6 genotyping or phenotyping. Which approach is more reliable?. Issue 5 (19th August 2020)

• Record Type: Journal Article
• Authors: Gusella, Milena; Pasini, Felice; Corso, Barbara; Bertolaso, Laura; De Rosa, Giovanni; Falci, Cristina; Modena, Yasmina; Barile, Carmen; Da Corte Z, Donatella; Fraccon, AnnaPaola; Toso, Silvia; Cretella, Elisabetta; Brunello, Antonella; Modonesi, Caterina; Segati, Romana; Oliani, Cristina; Minicuci, Nadia; Padrini, Roberto
• Is Part Of: Pharmacology research & perspectives. Volume 8:Issue 5(2020)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2020-08-19
• Subjects: breast cancer -- CYP2D6 -- dextromethorphan -- endoxifen; Pharmacology -- Periodicals; Drug development -- Periodicals; 615.105
• DOI: 10.1002/prp2.646
• Languages: English
• ISSNs: 2052-1707

Abstract

Abstract: In previous studies, steady‐state Z‐endoxifen plasma concentrations (ENDOss) correlated with relapse‐free survival in women on tamoxifen (TAM) treatment for breast cancer. ENDOss also correlated significantly with CYP2D6 genotype (activity score) and CYP2D6 phenotype (dextromethorphan test). Our aim was to ascertain which method for assessing CYP2D6 activity is more reliable in predicting ENDOss. The study concerned 203 Caucasian women on tamoxifen‐adjuvant therapy (20 mg q.d.). Before starting treatment, CYP2D6 was genotyped (and activity scores computed), and the urinary log(dextromethorphan/dextrorphan) ratio [log(DM/DX)] was calculated after 15 mg of oral dextromethorphan. Plasma concentrations of TAM, N‐desmethyl‐tamoxifen (ND‐TAM), Z‐4OH‐tamoxifen (4OH‐TAM) and ENDO were assayed 1, 4, and 8 months after first administering TAM. Multivariable regression analysis was used to identify the clinical and laboratory variables predicting log‐transformed ENDOss (log‐ENDOss). Genotype‐derived CYP2D6 phenotypes (PM, IM, NM, EM) and log(DM/DX) correlated independently with log‐ENDOss. Genotype‐phenotype concordance was almost complete only for poor metabolizers, whereas it emerged that 34% of intermediate, normal, and ultrarapid metabolizers were classified differently based on log(DM/DX). Multivariable regression analysis selected log(DM/DX) as the best predictor, with patients' age, weak inhibitor use, and CYP2D6 phenotype decreasingly important: log‐ENDOss = 0.162 ‐ log(DM/DX) × 0.170 + age × 0.0063 ‐ weak inhibitor use × 0.250 + IM × 0.105 + (NM + UM) × 0.210; ( R 2 = 0.51). In conclusion, log(DM/DX) seems superior to genotype‐derived CYP2D6 phenotype in predicting ENDOss.