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Tacrolimus trough levels after month 3 as a predictor of acute rejection following kidney transplantation: a lesson learned from DeKAF Genomics.

ABSTRACT: Most calcineurin inhibitor (CNI)-based protocols reduce blood trough goals approximately 2-3 months post-transplant in clinically stable kidney transplant recipients. The CNI target trough level to prevent rejection, after reduction, is unknown. Using a multivariate Cox proportional hazards model, we determined the association of time-varying tacrolimus (TAC) trough levels with acute rejection (AR) occurring in the first 6 months post-transplant, but specifically we assessed this association after 3 months. A total of 1930 patients received TAC-based immunosuppression prior to AR in a prospective study. Of the 151 (7.8%) who developed AR, 47 developed AR after 3 months post-transplant. In an adjusted time-varying multivariate model, each 1 ng/ml decrease in TAC trough levels was associated with a 7.2% increased risk of AR [hazards ratio (HR) = 1.07, 95% confidence interval (CI) (1.01, 1.14) P = 0.03] in the first 6 months. There was an additional 23% increased risk of AR with each 1 ng/ml decrease in the TAC trough levels in months 3-6 [HR = 1.23, 95% CI (1.06, 1.43) P = 0.008]. In conclusion, lower TAC trough levels were significantly associated with increased risk of AR in the first 6 months post-transplant with additional risk of AR between months 3 and 6 post-transplant. The timing and practice of TAC dose reduction should be personalized based on the individual's risk factors.

SUBMITTER: Israni AK

PROVIDER: S-EPMC3787982 | biostudies-literature | 2013 Oct

REPOSITORIES: biostudies-literature

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Tacrolimus trough levels after month 3 as a predictor of acute rejection following kidney transplantation: a lesson learned from DeKAF Genomics.

Israni Ajay K AK Riad Samy M SM Leduc Robert R Oetting William S WS Guan Weihua W Schladt David D Matas Arthur J AJ Jacobson Pamala A PA

Transplant international : official journal of the European Society for Organ Transplantation 20130724 10

Most calcineurin inhibitor (CNI)-based protocols reduce blood trough goals approximately 2-3 months post-transplant in clinically stable kidney transplant recipients. The CNI target trough level to prevent rejection, after reduction, is unknown. Using a multivariate Cox proportional hazards model, we determined the association of time-varying tacrolimus (TAC) trough levels with acute rejection (AR) occurring in the first 6 months post-transplant, but specifically we assessed this association aft ...[more]

PMID: 23879408

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Project description:BackgroundMonitoring and maintaining a stable tacrolimus trough level is essential because of its narrow therapeutic window and considerable fluctuation in the early phase after kidney transplantation. However, optimal tacrolimus exposure early after transplantation remains unclear among Chinese patients.MethodsIn this propensity score-matched cohort study, we thoroughly investigated the association between tacrolimus trough level at the first month and acute rejection (AR) as well as infection within the first year after kidney transplantation.ResultsIn a first step, a total of 1415 patients were divided into 3 groups according to the receiver operating characteristic curve: low-level group (410 patients with a tacrolimus trough level <5.35 ng/mL at the first month), median-level group (466 patients with a tacrolimus trough level from 5.35 to 7.15 ng/mL), and high-level group (539 patients with a tacrolimus trough level >7.15 ng/mL). Ultimately, 363 and 459 pairs of cases were enrolled by using 2 propensity score matches between low- and median-level groups and between high- and median-level groups, respectively. Compared with patients in the low-level group, patients in the median-level group had lower risk of AR without increased incidence of infection (AR, 12.4% versus 5.7%, P = 0.02; infection, 13.2% versus 13.2%, P = 1.00 for low- and median-level groups, respectively) within the first year. Compared with patients in the high-level group, patients in the median-level group had lower incidence of infection without the growing risk of AR (infection, 17.6% versus 12.2%, P = 0.021; AR, 4.6% versus 5.4%, P = 0.545 for high- and median-level groups, respectively) within the first year. Multilogistic analysis showed that tacrolimus trough levels were an independent factor for AR (odds ratio, 0.749, 95% confidence interval, 0.632-0.888, P = 0.001). Tacrolimus trough levels were also associated with infection (odds ratio 1.110, 95% confidence interval, 1.013-1.218, P = 0.001). Serum creatinine levels were similar among groups. No difference was found in 1-, 3-, and 5-year graft survival and patient survival among groups.ConclusionsThe tacrolimus trough level maintained between 5.35 and 7.15 ng/mL at the first posttransplant month may prevent AR without increasing the incidence of infection within the first year after living kidney transplantation among Chinese patients.

Project description:BACKGROUND AND OBJECTIVE:Given that a high intrapatient variability (IPV) of tacrolimus whole blood concentration increases the risk for a poor kidney transplant outcome, some experts advocate routine IPV monitoring for detection of high-risk patients. However, attempts to estimate the variance of tacrolimus trough concentrations (TTC) are limited by the need for patients to receive a fixed dose over time and/or the use of linear statistical models. A goal of this study is to overcome the current limitations through the novel application of statistical methodology generalizing the relationship between TTC and dose through the use of nonparametric functional regression modeling. METHODS:With TTC as a response and dose as a covariate, the model employs an unknown bivariate function, allowing for the potentially complex, nonlinear relationship between the two parameters. A dose-adjusted variance of TTC is then derived based on standard functional principal component analysis (FPCA). To assess the model, it was compared against an FPCA-based model and linear mixed-effects models using prediction error, bias, and coverage probabilities for simulated data as well as phase III data from the Astellas new drug application studies for extended-release tacrolimus. RESULTS:Our numerical investigation indicates that the new model better predicts dose-adjusted TTCs compared with the prediction of linear mixed effects models. Estimated coverage probabilities also indicate that the new model accurately accounts for the variance of TTC during the periods of large fluctuation in dose, whereas the linear mixed effects model consistently underestimates the coverage probabilities because of the inaccurate characterization of TTC fluctuation. CONCLUSION:This is the first known application of a functional regression model to assess complex relationships between TTC and dose in a real clinical setting. This new method has applicability in future clinical trials including real-world data sets due to flexibility of the nonparametric modeling approach.

Project description:Tacrolimus dosing to establish therapeutic levels in recipients of organ transplants is a challenging task because of much interpatient and intrapatient variability in drug absorption, metabolism, and disposition. In view of the reported impact of gut microbial species on drug metabolism, we investigated the relationship between the gut microbiota and tacrolimus dosing requirements in this pilot study of adult kidney transplant recipients. Serial fecal specimens were collected during the first month of transplantation from 19 kidney transplant recipients who either required a 50% increase from initial tacrolimus dosing during the first month of transplantation (Dose Escalation Group, n=5) or did not require such an increase (Dose Stable Group, n=14). We characterized bacterial composition in the fecal specimens by deep sequencing of the PCR amplified 16S rRNA V4-V5 region and we investigated the hypothesis that gut microbial composition is associated with tacrolimus dosing requirements. Initial tacrolimus dosing was similar in the Dose Escalation Group and in the Stable Group (4.2 ± 1.1 mg/day vs. 3.8 ± 0.8 mg/day, respectively, P=0.61, two-way between-group ANOVA using contrasts) but became higher in the Dose Escalation Group than in the Dose Stable Group by the end of the first transplantation month (9.6 ± 2.4 mg/day vs. 3.3 ± 1.5 mg/day, respectively, P<0.001). Our systematic characterization of the gut microbial composition identified that fecal Faecalibacterium prausnitzii abundance in the first week of transplantation was 11.8% in the Dose Escalation Group and 0.8% in the Dose Stable Group (P=0.002, Wilcoxon Rank Sum test, P<0.05 after Benjamini-Hochberg correction for multiple hypotheses). Fecal Faecalibacterium prausnitzii abundance in the first week of transplantation was positively correlated with future tacrolimus dosing at 1 month (R=0.57, P=0.01) and had a coefficient ± standard error of 1.0 ± 0.6 (P=0.08) after multivariable linear regression. Our novel observations may help further explain inter-individual differences in tacrolimus dosing to achieve therapeutic levels.

Dataset Information

Tacrolimus trough levels after month 3 as a predictor of acute rejection following kidney transplantation: a lesson learned from DeKAF Genomics.

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Tacrolimus trough levels after month 3 as a predictor of acute rejection following kidney transplantation: a lesson learned from DeKAF Genomics.

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