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External Evaluation of a Bayesian Warfarin Dose Optimization Based on a Kinetic-Pharmacodynamic Model.
Aoyama, Takahiko; Hirai, Toshinori; Tsuji, Yasuhiro; Miyamoto, Aoi; Itoh, Toshimasa; Iwamoto, Takuya; Matsumoto, Yoshiaki.
  • Aoyama T; Laboratory of Clinical Pharmacokinetics, School of Pharmacy, Nihon University.
  • Hirai T; Department of Pharmacy, Mie University Hospital, Faculty of Medicine, Mie University.
  • Tsuji Y; Center for Pharmacist Education, School of Pharmacy, Nihon University.
  • Miyamoto A; Laboratory of Clinical Pharmacokinetics, School of Pharmacy, Nihon University.
  • Itoh T; Department of Pharmacy, Tokyo Women's Medical University, Medical Center East.
  • Iwamoto T; Department of Pharmacy, Mie University Hospital, Faculty of Medicine, Mie University.
  • Matsumoto Y; Laboratory of Clinical Pharmacokinetics, School of Pharmacy, Nihon University.
Biol Pharm Bull ; 45(1): 136-142, 2022.
Article en En | MEDLINE | ID: mdl-34980775
ABSTRACT
Warfarin is a representative anticoagulant with large interindividual variability. The published kinetic-pharmacodynamic (K-PD) model allows the prediction of warfarin dose requirement in Swedish patients; however, its applicability in Japanese patients is not known. We evaluated the model's predictive performance in Japanese patients with various backgrounds and relationships using Bayesian parameter estimation and sampling times. A single-center retrospective observational study was conducted at Tokyo Women's Medical University, Medical Center East. The study population consisted of adult patients aged >20 years who commenced warfarin with a prothrombin time-international normalized ratio (PT-INR) from June 2015 to June 2019. The published K-PD model modified by Wright and Duffull was assessed using prediction-corrected visual predictive checks, focusing on clinical characteristics, including age, renal function, and individual prediction error. The external dataset included 232 patients who received an initial warfarin daily dose of 3.2 ± 1.28 mg with 2278 PT-INR points (median [range] follow-up period of 23 d [7-28]). Prediction-corrected visual predictive checks carried a propensity for underprediction. Additionally, age >60 years, body mass index ≤25 kg/m2, and estimated glomerular filtration rate ≤60 mL/min/1.73 m2 had a pronounced tendency to underpredict PT-INR. However, Bayesian prediction using four prior observations reduced underprediction. To improve the prediction performance of these special populations, further studies are required to construct a model to predict warfarin dose requirements in Japanese patients.
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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Warfarina / Anticoagulantes Tipo de estudio: Observational_studies / Prognostic_studies Límite: Adult / Female / Humans / Middle aged Idioma: En Año: 2022 Tipo del documento: Article

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Warfarina / Anticoagulantes Tipo de estudio: Observational_studies / Prognostic_studies Límite: Adult / Female / Humans / Middle aged Idioma: En Año: 2022 Tipo del documento: Article