Introduction 0–12 1 2 4 5 7 0–12 0 0 1 8 6 9 11 0–12 12 18 19 20 21 22 0 0–12 0–12 0–12 0–12 0 12 15 18 20 22 0 23 0 12 Materials and methods Patient population 1 1 Table 1 Demographic characteristics of renal-transplant recipients Demographic characteristics n Gender (male/female) 24/13 Age (years, mean ± SD) 51.3 ± 10.9 Length (cm, mean ± SD) 174 ± 8.4 Weight (kg, mean ± SD) 77.4 ± 13.5 2 25.6 ± 3.42 n   Glomerulonephritis 1  Chronic pyelonephritis 2  IgA nephropathy 4  Hypertensive nephropathy 7  Diabetes mellitus nephropathy 0  Polycystic kidney disease 8  Unknown 4  Other 11 n   First 30  Second 6  Third or more 1 n 29 −1 −1 0.054 ± 0.029 0 6.59 ± 1.39 0–12 122.5 ± 31.1 max 20.9 ± 6.5 max 1.24 ± 0.43 Use of azothioprine/MMF/rapamycine/steroids 3/4/0/2 Time since transplantation (days, mean and range) 1,542 (453–4,128) Haemoglobin (mmol/L, ref. M: 8.2–11.0, F: 7.3–9.7) 8.52 ± 0.83 Haematocrit fraction (ref. M: 0.41–0.52, F: 0.36–0.48) 0.41 ± 0.04 ALAT (units/L, ref. M: <45, F: <35) 24 ± 13 ASAT (units/L, ref. M: <35, F: <30) 17 ± 10 Serum albumin (g/L, ref. 34–45) 37.0 ± 3.84 Serum creatinine (μmol/L, ref. M: 71–110, F: 53–97) 128 ± 29 Creatinine clearance (Cockcroft-Gault; mL/min, ref. 90–140) 58.4 ± 26.6 Ref. M F MMF 0 0.5 1 2 3 4 5 7.5 12 Determination of tacrolimus concentrations n n Limited sampling strategies investigated 12 15 16 18 20 22 12 16 18 20 22 15 0 12 Pharmacokinetics and statistical analysis 0–12 0–12 pred 24 12 14 16 18 20 22 16 25 26 \documentclass[12pt]{minimal}
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\begin{document}$$ {\text{PE}}{\left( \%  \right)} = 100 \times {{\left( {{\text{AUC}}_{{{\text{pred}}}}  - {\text{AUC}}_{{{\text{actual}}}} } \right)}} \mathord{\left/  {\vphantom {{{\left( {{\text{AUC}}_{{{\text{pred}}}}  - {\text{AUC}}_{{{\text{actual}}}} } \right)}} {{\text{AUC}}}}} \right.  \kern-\nulldelimiterspace} {{\text{AUC}}}_{{{\text{actual}}}}  $$\end{document} \documentclass[12pt]{minimal}
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\begin{document}$$ {\text{APE}}{\left( \%  \right)} = 100 \times {{\left| {{\left( {{\text{AUC}}_{{{\text{pred}}}}  - {\text{AUC}}_{{{\text{actual}}}} } \right)}} \right|}} \mathord{\left/  {\vphantom {{{\left| {{\left( {{\text{AUC}}_{{{\text{pred}}}}  - {\text{AUC}}_{{{\text{actual}}}} } \right)}} \right|}} {{\text{AUC}}}}} \right.  \kern-\nulldelimiterspace} {{\text{AUC}}}_{{{\text{actual}}}}  $$\end{document} pred actual R 2 Results Evaluation of predictive performances of the limited sampling strategies 2 R 2 3 4 R 2 pred actual 0–12 0 12 1 Table 2 Overview of the characteristics of transplant patients included in the studies that described limited sampling strategies Study Transplanted organ a 0–12 b c d e f 16 Kidney 18 0/18 Imx II 2.5 years 1,2 20 Heart 22 0/25 Imx <1 year – 18 Kidney 15 0/15 Imx II 8.7 months 1,2,3 12 Kidney 22 13/14 Imx Unknown – 15 Kidney 43 64/20 Imx g 2 22 Lung 15 0/31 Imx 7.3 months – a b 0–12 c 0–12 d e f  1  2  3 g Table 3 R 2 0–12 Equation Time points Regression equations R 2 Ref 1. 0 \documentclass[12pt]{minimal}
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\begin{document}$$14.550 + 13.387 \times {\text{C}}_{0} $$\end{document} 0.54  2. 12 \documentclass[12pt]{minimal}
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\begin{document}$$15.892 + 17.852 \times {\text{C}}_{{12}} $$\end{document} 0.79  a 0 2 4 \documentclass[12pt]{minimal}
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\begin{document}$$24.36 + 0.97 \times {\text{C}}_{2}  + 7.94 \times {\text{C}}_{4} $$\end{document} 0.94 22 Limited sample strategies derived from the linear trapezoidal rule and the complete 12-h AUC. a 0–12 b 0–12 Table 4 0–12 Equation Time points R 2 Mean PE (%) Mean APE (%) a b 0 4 0.760 −14.9 ± 13.8 (−46.0–33.2) 17.9 ± 9.43 (1.12–46.0) 13 (35%) b 0 3 0.779 −11.5 ± 14.0 (−41.9 to 33.1) 15.7 ± 8.83 (2.0–41.9) 21 (57%) 1. 0 0.536 2.11 ± 14.8 (−27.1 to 24.4) 12.3 ± 8.22 (0.7–27.1) 22 (59%) 11. 0 1 0.703 6.58 ± 14.8 (−26.5 to 43.7) 12.6 ± 10.1 (0.1–43.7) 24 (65%) 2. 12 0.80 9.56 ± 11.6 (−12.7 to 29.9) 12.0 ± 8.97 (0.3–29.9) 24 (65%) b 0 2 3 0.502 −4.44 ± 17.4 (−45.3 to 50.6) 13.7 ± 11.4 (0.4–50.6) 25 (68%) b 0 2 4 0.537 −5.11 ± 16.3 (−43.1 to 50.3) 12.9 ± 10.4 (0.2–50.3) 28 (76%) b 0 1 3 0.525 9.95 ± 19.4 (−29.7 to 88.8) 13.1 ± 17.4 (0.4–88.8) 30 (81%) 25. 0 4 0.911 −7.83 ± 6.36 (−21.3 to 2.4) 8.08 ± 6.02 (0.1–21.3) 30 (81%) 7. 0 1 2 0.869 2.35 ± 9.96 (−17.2 to 27.3) 8.03 ± 6.22 (0.0–27.3) 31 (84%) 6. 0 4 0.896 −5.97 ± 6.71 (−20.1 to 4.7) 6.63 ± 6.04 (0.6–20.1) 31 (84%) b 0 2 0.802 −3.69 ± 10.2 (−19.6 to 18.6) 9.10 ± 5.67 (0.4–19.6) 31 (84%) 17. 0 1 4 0.943 5.91 ± 7.06 (−8.8 to 26.3) 7.02 ± 5.93 (0.2–26.3) 33 (89%) c 0 1 4 0.934 5.00 ± 7.28 (−9.8 to 25.8) 6.81 ± 5.57 (0.2–25.8) 34 (92%) 14. 2 4 0.964 2.28 ± 6.58 (−17.1 to 16.1) 5.45 ± 4.24 (0.7–17.1) 35 (95%) 24. 0 2 4 0.941 −4.81 ± 5.26 (−17.3 to 2.8) 5.32 ± 4.73 (0.1–17.3) 35 (95%) 13. 1 4 0.973 6.30 ± 4.84 (−5.9 to 17.8) 6.68 ± 4.28 (0.3–17.8) 36 (97%) 8. 0 1 4 0.967 3.37 ± 5.21 (−5.2 to 17.7) 4.87 ± 3.80 (0.2–17.7) 36 (97%) 9. 0 2 4 0.962 0.10 ± 6.37 (−16.7 to 14.7) 4.71 ± 4.22 (0.3–16.7) 36 (97%) 26. 2 4 0.959 3.38 ± 5.24 (−7.6 to 15.5) 5.20 ± 3.37 (0.0–15.5) 36 (97%) 10. 1 2 4 0.976 3.07 ± 5.40 (−14.9 to 13.2) 4.99 ± 3.64 (0.1–14.9) 37 (100%) c 0 2 4 0.953 −1.58 ± 5.29 (−14.9 to 10.1) 4.00 ± 3.75 (0.0–14.9) 37 (100%) 12. 0 4 0.930 3.55 ± 6.30 (−9.8 to 14.3) 6.29 ± 3.46 (0.1–14.3) 37 (100%) 4. 2 4 0.963 −1.66 ± 4.99 (−12.0 to 14.3) 4.13 ± 3.20 (0.2–14.3) 37 (100%) 5. 0 2 4 0.959 1.33 ± 5.24 (−11.8 to 14.0) 4.22 ± 3.32 (0.5–14.0) 37 (100%) 3. 0 2 4 0.965 −0.20 ± 4.79 (−10.4 to 13.7) 3.64 ± 3.06 (0.2–13.7) 37 (100%) a 0–12 b 0–12 c 0–12 Fig. 1 0–12 x y  Discussion 12 14 16 18 20 22 0 12 actual 0–12 0–12 pred actual In contrast to most studies that describe LSS for tacrolimus in literature, we used an HPLC-MS/MS assay to determine the tacrolimus concentration. Because there seems to be a fixed difference of about 15% between the immunoassay and the HPLC-MS/MS, the prediction will change proportionally, and the predictivity of the LSS will be the same. Also potential interfering drug-drug interactions will have an equal influence on the different tacrolimus concentrations, which consequently has no effect on the predictivity of the different LSS. 23 20 22 0–12 23 0–12 0 12 0–12