A logistic-regression model provides novel guidelines to maximize the anti-acute rejection properties of cyclosporine with a minimum of toxicity.

Abstract

Although cyclosporine has become the mainstay of immunosuppression in organ transplantation, there is still no consensus on the criteria to optimize its anti-rejection activity with minimum toxicity. A clear and objective definition of target cyclosporine trough levels at different times from renal transplantation is still lacking, primarily because of the lack of a model correlating cyclosporine levels with probability of rejection or toxicity. In this study, logistic-regression model was developed that was applied to data collected retrospectively from two postoperative periods, i.e., Days 0 to 9 and 10 to 30, in 135 consecutive cadaveric renal transplant recipients, for a total of 1851 determinations. Only minimum and maximum trough levels were considered for each period. Concentration-response curves were estimated for Days 0 to 9 (P = 0.0001 for efficacy and P = 0.028 for toxicity) and for Days 10 to 30 (P = 0.015 for efficacy and P = 0.037 for toxicity). Therapeutic intervals of 330 to 430 ng/mL (parent compound in whole blood) for Days 0 to 9 and 260 to 390 ng/mL for Days 10 to 30 predicted an incidence of acute rejection of 22% and 12%, respectively, with a reasonably low toxicity that primarily consisted of elevation of serum aminotransferases.