Factors affecting inter-individual variability in endoxifen concentrations in patients with breast cancer: results from the prospective TOTAM trial

被引:7
作者
Braal, C. Louwrens [1 ]
Westenberg, Justin D. [1 ]
Buijs, Sanne M. [1 ]
Abrams, Steven [2 ,3 ]
Mulder, Tessa A. M. [4 ]
van Schaik, Ron H. N. [4 ]
Koolen, Stijn L. W. [1 ,5 ]
Jager, Agnes [1 ]
Mathijssen, Ron H. J. [1 ]
机构
[1] Erasmus MC Canc Inst, Dept Med Oncol, Dr Molewaterpl 40,POB 2040, NL-3015 CN Rotterdam, Netherlands
[2] UHasselt, Data Sci Inst, Interuniv Inst Biostat & Stat Bioinformat, Hasselt, Belgium
[3] Univ Antwerp, Global Hlth Inst, Family Med & Populat Hlth, Antwerp, Belgium
[4] Erasmus MC Univ Ctr, Dept Clin Chem, Rotterdam, Netherlands
[5] Erasmus MC Univ Ctr, Dept Hosp Pharm, Rotterdam, Netherlands
关键词
Tamoxifen; Endoxifen; Early breast cancer; Predictive modeling; Therapeutic drug monitoring; ADJUVANT TAMOXIFEN; ESTROGEN-RECEPTOR; MULTIPLE IMPUTATION; PHASE-I; CYP2D6; ADHERENCE; LEVEL; METABOLITES; THERAPY; IMPACT;
D O I
10.1007/s10549-022-06643-y
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
Introduction Endoxifen-the principal metabolite of tamoxifen-is subject to a high inter-individual variability in serum concentration. Numerous attempts have been made to explain this, but thus far only with limited success. By applying predictive modeling, we aimed to identify factors that determine the inter-individual variability. Our purpose was to develop a prediction model for endoxifen concentrations, as a strategy to individualize tamoxifen treatment by model-informed dosing in order to prevent subtherapeutic exposure (endoxifen < 16 nmol/L) and thus potential failure of therapy. Methods Tamoxifen pharmacokinetics with demographic and pharmacogenetic data of 303 participants of the prospective TOTAM study were used. The inter-individual variability in endoxifen was analyzed according to multiple regression techniques in combination with multiple imputations to adjust for missing data and bootstrapping to adjust for the over-optimism of parameter estimates used for internal model validation. Results Key predictors of endoxifen concentration were CYP2D6 genotype, age and weight, explaining altogether an average-based optimism corrected 57% (95% CI 0.49-0.64) of the inter-individual variability. CYP2D6 genotype explained 54% of the variability. The remaining 3% could be explained by age and weight. Predictors of risk for subtherapeutic endoxifen (< 16 nmol/L) were CYP2D6 genotype and age. The model showed an optimism-corrected discrimination of 90% (95% CI 0.86-0.95) and sensitivity and specificity of 66% and 98%, respectively. Consecutively, there is a high probability of misclassifying patients with subtherapeutic endoxifen concentrations based on the prediction rule. Conclusion The inter-individual variability of endoxifen concentration could largely be explained by CYP2D6 genotype and for a small proportion by age and weight. The model showed a sensitivity and specificity of 66 and 98%, respectively, indicating a high probability of (misclassification) error for the patients with subtherapeutic endoxifen concentrations (< 16 nmol/L). The remaining unexplained inter-individual variability is still high and therefore model-informed tamoxifen dosing should be accompanied by therapeutic drug monitoring.
引用
收藏
页码:65 / 74
页数:10
相关论文
共 47 条
  • [31] National Cancer Institute, Common Terminology Criteria for Adverse Events v. 4.03 (CTCAE)
  • [32] Model checking in multiple imputation: An overview and case study
    Nguyen C.D.
    Carlin J.B.
    Lee K.J.
    [J]. Emerging Themes in Epidemiology, 14 (1):
  • [33] Impact of SERM adherence on treatment effect: International Breast Cancer Study Group Trials 13-93 and 14-93
    Pagani, Olivia
    Gelber, Shari
    Colleoni, Marco
    Price, Karen N.
    Simoncini, Edda
    [J]. BREAST CANCER RESEARCH AND TREATMENT, 2013, 142 (02) : 455 - 459
  • [34] Serum Detection of Nonadherence to Adjuvant Tamoxifen and Breast Cancer Recurrence Risk
    Pistilli, Barbara
    Paci, Angelo
    Ferreira, Arlindo R.
    Di Meglio, Antonio
    Poinsignon, Vianney
    Bardet, Aurelie
    Menvielle, Gwenn
    Dumas, Agnes
    Pinto, Sandrine
    Dauchy, Sarah
    Fasse, Leonor
    Cottu, Paul H.
    Lerebours, Florence
    Coutant, Charles
    Lesur, Anne
    Tredan, Olivier
    Soulie, Patrick
    Vanlemmens, Laurence
    Jouannaud, Christelle
    Levy, Christelle
    Everhard, Sibille
    Arveux, Patrick
    Martin, Anne Laure
    Dima, Alexandra
    Lin, Nancy U.
    Partridge, Ann H.
    Delaloge, Suzette
    Michiels, Stefan
    Andre, Fabrice
    Vaz-Luis, Ines
    [J]. JOURNAL OF CLINICAL ONCOLOGY, 2020, 38 (24) : 2762 - +
  • [35] Model-Based Quantification of Impact of Genetic Polymorphisms and Co-Medications on Pharmacokinetics of Tamoxifen and Six Metabolites in Breast Cancer
    Puszkiel, Alicja
    Arellano, Cecile
    Vachoux, Christelle
    Evrard, Alexandre
    Le Morvan, Valerie
    Boyer, Jean-Christophe
    Robert, Jacques
    Delmas, Caroline
    Dalenc, Florence
    Debled, Marc
    Venat-Bouvet, Laurence
    Jacot, William
    Dohollou, Nadine
    Bernard-Marty, Chantal
    Laharie-Mineur, Hortense
    Filleron, Thomas
    Roche, Henri
    Chatelut, Etienne
    Thomas, Fabienne
    White-Koning, Melanie
    [J]. CLINICAL PHARMACOLOGY & THERAPEUTICS, 2021, 109 (05) : 1244 - 1255
  • [36] Factors Affecting Tamoxifen Metabolism in Patients With Breast Cancer: Preliminary Results of the French PHACS Study
    Puszkiel, Alicja
    Arellano, Cecile
    Vachoux, Christelle
    Evrard, Alexandre
    Le Morvan, Valerie
    Boyer, Jean-Christophe
    Robert, Jacques
    Delmas, Caroline
    Dalenc, Florence
    Debled, Marc
    Venat-Bouvet, Laurence
    Jacot, William
    Suc, Etienne
    Sillet-Bach, Isabelle
    Filleron, Thomas
    Roche, Henri
    Chatelut, Etienne
    White-Koning, Melanie
    Thomas, Fabienne
    [J]. CLINICAL PHARMACOLOGY & THERAPEUTICS, 2019, 106 (03) : 585 - 595
  • [37] Tamoxifen metabolism predicts drug concentrations and outcome in premenopausal patients with early breast cancer
    Saladores, P.
    Muerdter, T.
    Eccles, D.
    Chowbay, B.
    Zgheib, N. K.
    Winter, S.
    Ganchev, B.
    Eccles, B.
    Gerty, S.
    Tfayli, A.
    Lim, J. S. L.
    Yap, Y. S.
    Ng, R. C. H.
    Wong, N. S.
    Dent, R.
    Habbal, M. Z.
    Schaeffeler, E.
    Eichelbaum, M.
    Schroth, W.
    Schwab, M.
    Brauch, H.
    [J]. PHARMACOGENOMICS JOURNAL, 2015, 15 (01) : 84 - 94
  • [38] Clinical pharmacokinetics and pharmacogenetics of tamoxifen and endoxifen
    Sanchez-Spitman, A. B.
    Swen, J. J.
    Dezentje, V. O.
    Moes, D. J. A. R.
    Gelderblom, H.
    Guchelaar, H. J.
    [J]. EXPERT REVIEW OF CLINICAL PHARMACOLOGY, 2019, 12 (06) : 523 - 536
  • [39] Bootstrap inference when using multiple imputation
    Schomaker, Michael
    Heumann, Hristian
    [J]. STATISTICS IN MEDICINE, 2018, 37 (14) : 2252 - 2266
  • [40] Breast cancer treatment outcome with adjuvant tamoxifen relative to patient CYP2D6 and CYP2C19 genotypes
    Schroth, Werner
    Antoniadou, Lydia
    Fritz, Peter
    Schwab, Matthias
    Muerdter, Thomas
    Zanger, Ulrich M.
    Simon, Wolfgang
    Eichelbaum, Michel
    Brauch, Hiltrud
    [J]. JOURNAL OF CLINICAL ONCOLOGY, 2007, 25 (33) : 5187 - 5193