• Binu S Mathew, Denise H Fleming, Visalakshi Jeyaseelan, Sujith J Chandy, V M Annapandian, P K Subbanna, and George T John.
• Clinical Pharmacology Unit, Department of Biostatistics and Clinical Pharmacology, Christian Medical College, Vellore, India.
• Br J Clin Pharmacol. 2008 Oct 1; 66 (4): 467-72.

AimsTo develop and validate limited sampling strategy (LSS) equations to estimate area under the curve (AUC(0-12)) 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 AUC(0-12). 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) > or = 0.907. Two point models included one with trough (C(0)) and 1.5 h postdose (C(1.5)), 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 AUC(0-12). 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 [AUC(0-12) = 19.16 + (6.75.C(0)) + (3.33.C1.5)] can be used as a predictable and accurate measure of AUC(0-12) in stable renal transplant patients prescribed prednisolone and mycophenolate.

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