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Purpose Tamoxifen is part of endocrine therapy in breast cancer treatment. Studies have indicated the use of endoxifen concentrations, tamoxifen active metabolite, to guide tamoxifen efficacy. Three endoxifen thresholds have been suggested (5.9 ng/ml, 5.2 ng/ml and 3.3 ng/ml) for therapeutic drug monitoring (TDM). Our aim was to validate these thresholds and to examine endoxifen exposure with clinical outcome in early-breast cancer patients using tamoxifen. Methods Data from 667 patients from the CYPTAM study (NTR1509) were available. Patients were stratified (above or below), according to the endoxifen threshold values for tamoxifen efficacy and tested by Cox regression. Logistic regressions to estimate the probability of relapse and tamoxifen discontinuation were performed. Results None of the thresholds showed a statistically significant difference in relapse-free survival: 5.2 ng/ml threshold: hazard ratio (HR): 2.545, 95% confidence interval (CI) 0.912–7.096, p value: 0.074; 3.3 ng/ml threshold: HR: 0.728; 95% CI 0.421–1.258, p value: 0.255. Logistic regression did not show a statistically significant association between the risk of relapse (odds ratio (OR): 0.971 (95% CI 0.923–1.021, p value: 0.248) and the risk for tamoxifen discontinuation (OR: 1.006 95% CI 0.961–1.053, p value: 0.798) with endoxifen concentrations. Conclusion Our findings do not confirm the endoxifen threshold values for TDM nor does it allow definition of a novel threshold. These findings indicate a limited value of TDM to guide tamoxifen efficacy.

Aim of the review The translation of evidence based medicine to a specific patient presents a considerable challenge. We present by means of the examples nortriptyline, tramadol, clopidogrel, coumarins, abacavir and antipsychotics the discrepancy between available pharmacogenetic information and its implementation in daily clinical practice. Method Literature review. Results A mechanism based approach may be helpful to personalize medicine for the individual patient to which pharmacogenetics may contribute significantly. The lack of consistency in what we accept in bioequivalence and in pharmacogenetics of drug metabolising enzymes is discussed and illustrated with the example of nortriptyline. The impact of pharmacogenetics on examples like tramadol, clopidogrel, coumarins and abacavir is described. Also the present status of the polymorphisms of 5-HT2A and C receptors in antipsychotic-induced weight gain is presented as a pharmacodynamic example with until now a greater distance to clinical implementation. Conclusion The contribution of pharmacogenetics to tailor-made pharmacotherapy, which especially might be of value for patients deviating from the average, has not yet reached the position it seems to deserve.