A limited sampling strategy for tacrolimus in renal transplant patients - Mathew, Binu S.; Fleming, Denise H.; Jeyaseelan, Visalakshi; Chandy, Sujith J.; Annapandian, V. M.; Subbanna, P. K.; John, George T. (British journal of clinical pharmacology, 2008)
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. AIMS To develop and validate limited sampling strategy (LSS) equations to estimate area under the curve (AUC0–12) in renal transplant patients. METHODS Twenty‐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 (R2), bias and precision were identified. The predictive performance of these models was validated by the jackknife technique. RESULTS Three models were identified, all with R2 ≥ 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 R2 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 R2 = 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). CONCLUSION The two‐point LSS equation [AUC0–12 = 19.16 + (6.75.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.