Contribution of Population Pharmacokinetics to Dose Optimization of Ganciclovir-Valganciclovir in Solid-Organ Transplant Patients

Abstract

Treatment of solid-organ transplant (SOT) patients with ganciclovir (GCV)-valganciclovir (VGCV) according to the manufacturer's recommendations may result in over- or underexposure. Bayesian prediction based on a population pharmacokinetics model may optimize GCV-VGCV dosing, achieving the area under the curve (AUC) therapeutic target. We conducted a two-arm, randomized, open-label, 40% superiority trial in adult SOT patients receiving GCV-VGCV as prophylaxis or treatment of cytomegalovirus infection. Group A was treated according to the manufacturer's recommendations. For group B, the dosing was adjusted based on target exposures using a Bayesian prediction model (NONMEM). Fifty-three patients were recruited (27 in group A and 26 in group B). About 88.6% of patients in group B and 22.2% in group A reached target AUC, achieving the 40% superiority margin (P< 0.001; 95% confidence interval [CI] difference, 47 to 86%). The time to reach target AUC was significantly longer in group A than in group B (55.9 ± 8.2 versus 15.8 ± 2.3 days,P< 0.001). A shorter time to viral clearance was observed in group B than in group A (12.5 versus 17.6 days;P= 0.125). The incidences of relapse (group A, 66.67%, and group B, 9.01%) and late-onset infection (group A, 36.7%, and group B, 7.7%) were higher in group A. Neutropenia and anemia were related to GCV overexposure. GCV-VCGV dose adjustment based on a population pharmacokinetics Bayesian prediction model optimizes GCV-VGCV exposure. (This study has been registered at ClinicalTrials.gov under registration no. NCT01446445.).

FIG 1

Study patient allocation and disposition.

FIG 2

Average estimated systemic exposure of GCV following administration of oral VGC by CL_CR cutoff values.

FIG 3

Rate of first achievement of AUC target according to randomization group over the follow-up period (Kaplan-Meier analysis using log rank statistics) for all patients included (A), for patients on prophylaxis (B), and for patients on treatment of CMV infection (C). Time scale is based on days under GCV-VGCV treatment.

FIG 4

Kaplan-Meier curves showing cumulative probability of viral clearance in patients treated with either oral VGCV or i.v. GCV.

FIG 5

Plots of individual viral load decays observed until day 45 for patients treated according to the manufacturer's recommendation (left) and for patients with dose adjusted by Bayesian approach (right). The gray line represents the limit of quantification of the analytical method. (Relapse data are not shown.)

FIG 6

Receiver-operator curve (ROC) of dose adjustment based on target AUC, recipient IgG serostatus, and immunological risk for predicting relapse (A) and of dose adjustment based on AUC target, recipient IgG serostatus, episodes of rejection, and immunological risk for predicting late CMV disease (B).

FIG 7

Dosage distributions considering the randomization group, route of administrations, type of treatment, and CL_CR cutoffs. (A) i.v. GCV dosage; (B) oral VGCV dosage in patients on prophylaxis; (C) oral VGCV dosage in patients on treatment for CMV infection.