The unbound fraction (f(U)) of cyclosporine in plasma is approximately
0.02. The measurement of cyclosporine f(U) requires a laborious equil
ibrium dialysis procedure, which is not practical in a clinical settin
g. A mathematical model was developed to estimate cyclosporine f(U) fr
om concentrations of serum lipoproteins, the major binding proteins fo
r cyclosporine. Values of f(U) were determined ex vivo in 126 plasma s
amples obtained from 58 recipients of heart and lung transplants, usin
g equilibrium dialysis. Concentrations of serum lipids, measured using
standard enzymatic techniques, were used as concentration markers for
serum lipoproteins. Patients were randomly assigned to either of two
equal-sized groups. One group (subgroup 1) was used to evaluate the pa
rameters of the model, and the other group isubgroup 2) was used to ex
amine its predictive performance. The parameters were estimated using
least squares non-linear regression. A model incorporating concentrati
ons of serum HDL- and LDL-cholesterol, serum albumin, and time after t
ransplantation gave the best fit. For subgroup 2, mean prediction erro
r (ME), a measure of bias, and root mean squared error (RMSE) and medi
an absolute error (MAE), measures of precision, and their 95% confiden
ce intervals were estimated. For the best fit model, ME was 0.07 x 10(
-2) (-0.065 x 10(-2) - 0.1 x 10(-2)), indicating that the model provid
ed an unbiased estimate of the value of cyclosporine f(U). Root mean s
quared error and MAE were 0.536 x 10(-2) (0.398 x 10(-2) - 0.645 x 10(
-2)) and 0.27 x 10(-2) (0.226 x 10(-2) - 0.409 x 10(-2)), respectively
. Prediction error was normally distributed; approximately 30% of the
prediction errors were <10% and <5% of prediction errors were >50%. Th
is model has shown a reasonable predictive performance in the patients
with cardiac transplants studied; however, its predictive performance
will need to be validated in a larger number of recipients of transpl
ants of various types.