Impact of longitudinal exposure to mycophenolic acid on acute rejection in renal-transplant recipients using a joint modeling approach
Pharmacological Research , Volume 72 p. 52- 60
This study aimed to investigate the association between longitudinal exposure to mycophenolic acid (MPA) and acute rejection (AR) risk in the first year after renal transplantation, and to propose MPA exposure targets conditionally to this association. A joint model, adjusted for monitoring strategy (fixed-dose versus concentration-controlled) and recipient age, was developed; it combined a mixed-effects model to describe the whole pattern of MPA exposure (i.e. area under the concentration-time curve (AUC)) and a survival model. MPA AUC thresholds were determined using time-dependent receiver-operating characteristics (ROC) curves. Data from 490 adult renal-transplant recipients, representative of the general population of adult renal-transplant patients (i.e. including patients considered at low immunological risk-enrolled in the OPERA trial as well as second renal transplant and patients co-treated by either cyclosporine or tacrolimus), were analyzed. A significant association was found between the longitudinal exposure to MPA (MPA AUCs = f(t)) and AR (p = 0.0081), and validated by bootstrapping. A significant positive correlation was observed between time post-transplantation and ROC thresholds which increased in average from 35 mg h/L in the first days to 41 mg h/L beyond six months post-transplantation (p < 0.001). Using a new modeling approach which recognizes the repeated measures in a same patient, this study supports the association between MPA exposure and AR.
|Acute rejection, Joint modeling, Longitudinal exposure, Mycophenolic acid, Renal-transplant recipients, ROC thresholds|
|Organisation||Department of Biostatistics|
Daher Abdi, Z, Essig, M, Rizopoulos, D, le Meur, Y, Prémaud, A, Woillard, J.B, … Rousseau, A. (2013). Impact of longitudinal exposure to mycophenolic acid on acute rejection in renal-transplant recipients using a joint modeling approach. Pharmacological Research, 72, 52–60. doi:10.1016/j.phrs.2013.03.009