研究者情報 | |
ナカザワ リュウト
NAKAZAWA RYUTO 中澤龍斗 所属 医学部医学科 腎泌尿器外科学 職種 教授 |
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論文種別 | 原著 |
言語種別 | 英語 |
査読の有無 | 査読あり |
表題 | Clinically useful limited sampling strategy to estimate area under the concentration-time curve of once-daily tacrolimus in adult Japanese kidney transplant recipients. |
掲載誌名 | 正式名:PloS one 略 称:PLoS One ISSNコード:1932620319326203 |
掲載区分 | 国外 |
巻・号・頁 | 14(12),e0225878頁 |
著者・共著者 | Nakazawa Ryuto, Yoshiike Miki, Nozawa Shiari, Aida Koichiro, Katsuoka Yuichi, Fujimoto Eisuke, Yazawa Masahiko, Kikuchi Eiji, Shibagaki Yugo, Sasaki Hideo |
担当区分 | 筆頭著者,責任著者 |
発行年月 | 2019/12 |
概要 | BACKGROUND:An extended-release, once-daily, oral formulation of tacrolimus is currently used after kidney transplantation as a substitute for the conventional twice-daily formulation. The purpose of this study was to provide a limited sampling strategy with minimum and optimum sampling points to predict the tacrolimus area under the concentration-time curve (AUC) after administration of once-daily tacrolimus in de novo adult kidney transplant patients.METHODS:A total of 36 adult Japanese kidney transplant patients receiving once-daily tacrolimus were included: 31 were allocated to a study group to develop limited sampling strategy (LSS) model equations based on multiple stepwise linear regression analysis, and 5 were allocated to a validation group to estimate the precision of the LSS equations developed by the study group. Twelve-hour AUC (AUC0-12) was calculated by the trapezoidal rule, and the relationship between individual concentration points and AUC0-12 were determined by multiple linear regression analysis. The coefficient of determination (R2) was used to assess the goodness-of-fit of the regression models. Three error indices (mean error, mean absolute error, and root mean squared prediction error) were calculated to evaluate predictive bias, accuracy, and precision, respectively. Quality of the statistical models was compared with Akaike's information criterion (AIC).RESULTS:A four-point model using C0, C2, C4 and C6 gave the best fit to predict AUC0-12 (R2 = 0.978). In the three- and two-point models, the best fits were at time points C2, C4, and C6 (R2 = 0.973), and C2 and C6 (R2 = 0.962), respectively. All three models reliably estimated tacrolimus AUC0-12, consistent with evaluations by the three error indices and Akaike's information criterion. Practically, the two-point model with C2 and C6 was considered to be the best combination, providing a highly accurate prediction and the lowest blood sampling frequency.CONCLUSIONS:The two-point model with C2 |
DOI | 10.1371/journal.pone.0225878 |
PMID | 31825991 |