A limited sampling strategy for tacrolimus in renal transplant patients

Abstract

WHAT IS ALREADY KNOWN ABOUT THIS SUBJECT• Tacrolimus trough concentration is being currently used for dose individualization.• Limited sampling strategies (LSS) have been developed and validated for renal transplant patients.• Earlier literature has suggested that measurement of tacrolimus AUC is more reliable than trough with respect to both rejection and nephrotoxicity. WHAT THIS STUDY ADDS• Four thousand renal transplants take place annually in India, with many patients prescribed tacrolimus in combination with mycophenolate and steroid.• In this study a LSS with two points, i.e. trough and 1.5 h postdose was developed and validated to estimate AUC0-12.• The added benefit of only a single additional sample with completion of blood collection in 1.5 h and minimum additional cost makes this a viable LSS algorithm in renal transplant patients.• In patients having tacrolimus trough concentrations outside the recommended range (<3 and >10 ng ml -1 in the treatment protocol in our institution) or having side-effects in spite of trough concentrations in the desired range, we can estimate AUC using this LSS for a better prediction of exposure. AIMSTo develop and validate limited sampling strategy (LSS) equations to estimate area under the curve (AUC0-12) in renal transplant patients. METHODSTwenty-nine renal transplant patients (3-6 months post transplant) who were at steady state with respect to tacrolimus kinetics were included in this study. The blood samples starting with the predose (trough) and collected at fixed time points for 12 h were analysed by microparticle enzyme immunoassay. Linear regression analysis estimated the correlations of tacrolimus concentrations at different sampling time points with the total measured AUC0-12. By applying multiple stepwise linear regression analysis, LSS equations with acceptable correlation coefficients (R 2 ), bias and precision were identified. The predictive performance of these models was validated by the jackknife technique. RESULTSThree models were identified, all with R 2 Ն 0.907. Two point models included one with trough (C0) and 1.5 h postdose (C1.5), another with trough and 4 h postdose. Increasing the number of sampling time points to more than two increased R 2 marginally (0.951 to 0.990). After jackknife validation, the two sampling time point (trough and 1.5 h postdose) model accurately predicted AUC0-12. Regression coefficient R 2 = 0.951, intraclass correlation = 0.976, bias [95% confidence interval (CI)] 0.53% (-2.63, 3.69) and precision (95% CI) 6. 35% (4.36, 8.35). CONCLUSIONThe two-point LSS equation .C0) + (3.33.C1.5)] can be used as a predictable and accurate measure of AUC0-12 in stable renal transplant patients prescribed prednisolone and mycophenolate.

Developmental Pharmacogenetics of Immunosuppressants in Pediatric Organ Transplantation

“…92 Thus, AUC-guided tacrolimus TDM has been proposed with a target of 150 to 200 h*ng/mL. Numerous LSS-based on regression linear method [103][104][105][106][107] and Bayesian estimator 108 have been developed but only in adults and no further validation was conducted in children. Therefore, validation of pediatric-specific LSS for tacrolimus should be performed in future investigations.…”

Development of Limited Sampling Strategies for the Estimation of Tacrolimus Area Under the Curve in Adult Kidney Transplant Recipients According to the Posttransplantation Time

“…The correlation coefficients were between 0.95 and 0.99 and %RMSE between 4.1 and 8.6. Mathew et al 21 have found that the C/C 1.5 combination was highly correlated with the tacrolimus AUC (r 2 = 0.95). According to our results, the inclusion of a third point in the LSS seems to be superfluous because the differences in correlation coefficients and prediction error indicators between 2-and 3-time point LSS are very slight.…”

“…8,17,21 However, this time point becomes less predictive for AUC after 1 year of exposure to tacrolimus, and thus it could not be considered as a reliable parameter for the TDM of this drug.…”

“…In agreement with this study, Barraclough et al 20 have shown that the performance of the C 0 to predict AUC decreases over time. 21 The correlation coefficient r² between C 0 and AUC was indeed 0.64 during the first 5 days after transplantation to become 0.21 beyond 3 months. In the same study, the best correlated 1-time point with AUC in both groups was C 6 (r² = 0.91 and 0.79, respectively).…”

Optimal Pharmacokinetics of Cyclosporine and Tacrolimus Based Relationship Among AUC, Trough and Peak Concentration

“…Therefore, TAC was examined to show which blood sampling point is the best correlated with AUC as CYA. One study reported that C o is the best correlated with AUC 27) , whereas another study suggested that a formula with fewer blood sampling points, and not C o , is the most closely correlated with AUC (limited sampling strategy) [28][29][30][31] .…”