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European Journal of Clinical Pharmacology

, Volume 74, Issue 5, pp 571–582 | Cite as

Pharmacokinetic and pharmacodynamic re-evaluation of a genetic-guided warfarin trial

  • Carlo Federico Zambon
  • Vittorio Pengo
  • Stefania Moz
  • Dania Bozzato
  • Paola Fogar
  • Andrea Padoan
  • Mario Plebani
  • Francesca Groppa
  • Giovanni De Rosa
  • Roberto Padrini
Pharmacogenetics
  • 255 Downloads

Abstract

Purpose

A previous trial failed to demonstrate the superiority of a demographic-genetic algorithm in predicting warfarin (W) dose over a standard clinical approach. The purpose of the present study is to re-analyse the results in subgroups of patients with differing baseline sensitivity to W, integrated with additional pharmacokinetic data.

Methods

The original trial allocated 180 treatment-naïve patients with non-valvular atrial fibrillation to a control arm (CTL, n = 92) or a genetic-guided arm (GEN, n = 88). Before starting anticoagulation treatment, all patients were genotyped for CYP2C9, VKORC1 and CYP4F2 variants and classified into four quartiles (Q1, Q2, Q3, Q4) according to the algorithm-predicted W maintenance dose. International normalised ratios (INR) and plasma concentrations of S-warfarin [S-W]s and R-warfarin [R-W]s were measured at baseline and on days 5, 7, 9, 12, 15 and 19 of therapy.

Results

In the lowest dose quartile (Q1), the number of INRs > 3 and mean INR values on days 5 and 7 were significantly higher in CTL than in GEN. In Q3 and Q4, the mean INR values reached therapeutic level (> 2) 2 days later in CTL than in GEN. During follow-up, the mean time courses of INRs and [S-W]s in GEN were remarkably stable in all dose quartiles. Thus, mean changes from starting to final doses were significantly smaller in GEN than in CTL. Plasma concentrations of R-W (a partially active enantiomer) steadily increased from day 5 to day 19 in all Qs in both CTL and GEN, except in the Q1 CTL group, due to the marked dose reduction required.

Conclusions

This analysis showed that the demographic-genetic algorithm used to predict the W dose can identify patients with differing degrees of sensitivity to W and to ‘normalise’ their average anticoagulant responses. The progressive rise in [R-W]s throughout the 19-day follow-up indicates that the (partial) contribution of R-W to the W anticoagulant effect changes continually during the early phase of treatment.

Keywords

Warfarin Algorithm Pharmacogenetics Pharmacodynamic Pharmacokinetics 

Notes

Acknowledgements

The authors would like to thank Drs Giovanni Nante, Enrico Tiso, Gentian Denas and Seena Padayattil Jose for their help in collecting patients’ data.

Authors’ contributions

Concept of study: CF Zambon, V Pengo, M Plebani and R Padrini.

Acquisition of clinical data: V Pengo, P Fogar, S Moz and D Bozzato.

Genotyping: CF Zambon, S Moz and A Padoan.

Drug assays: G De Rosa and F Groppa.

Funding

This study was funded by the University of Padova, Italy (‘fondi DOR’, 2016).

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

The original study was approved by the Ethics Committee of Azienda-ULSS 16, Padova Protocol no. 8793. All procedures in this study were carried out according to the 1964 Helsinki Declaration and its later amendments.

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  • Carlo Federico Zambon
    • 1
  • Vittorio Pengo
    • 2
  • Stefania Moz
    • 3
  • Dania Bozzato
    • 3
  • Paola Fogar
    • 4
  • Andrea Padoan
    • 3
  • Mario Plebani
    • 3
  • Francesca Groppa
    • 3
  • Giovanni De Rosa
    • 3
  • Roberto Padrini
    • 3
  1. 1.Department of Biomedical Sciences DSB, Medical SchoolUniversity of PadovaPaduaItaly
  2. 2.Department of Cardiac, Thoracic and Vascular Sciences, Medical SchoolUniversity of PadovaPaduaItaly
  3. 3.Department of Medicine DIMED, Medical SchoolUniversity of PadovaPaduaItaly
  4. 4.Department of Laboratory MedicineAzienda Ospedaliera di PadovaPaduaItaly

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