CLINICAL IMMUNOSUPPRESSION - KIDNEY LATE

J.R. Maclean¹, M. Pfister², S. Zhou², A. Roy², J. Mathias², M. Heifets^2
1Health Economics And Outcomes Research, Bristol-Myers Squibb, Plainsboro/UNITED STATES OF AMERICA, ², Bristol-Myers Squibb, Princeton/UNITED STATES OF AMERICA

Body: Introduction:
Immunosupressive (IS) regimens require life-long adherence to maintain the transplanted organ. While calcineurin inhibitors (CNI)-based regimens are effective, dose optimization is critical tominimize both organ rejection and CNI-related toxicities. The relationship between variability in drug exposure and health outcomes is well documented [Waiser et al, Nephrology DialysisTransplantation 2002; 17:1310-1317 & Kahan, JASN; 11:1122-1131]. One major cause of variability in drug exposure is non-adherence [Kenna LA et al, AAPS J 2005; 7: E390-407]. Non-adherence remainsa major challenge in the provision of medical care, particularly in the management of chronic conditions such as organ transplantation where the implications of suboptimal adherence are assignificant as allograft rejection, a return to dialysis, and potentially death. Between 14% and 65% of renal graft losses have been attributed to non-adherence in cohort studies [Butler JA et al,Transplantation 2004; 77: 769-776]. Therefore, the goal of this study was to describe the impact of patient behavior (defined by adherence) on CsA treatment characteristics (defined by dose andexposure).

Methods:
A model was developed based on published data on real-world adherence to twice-daily oral CsA [Russell, Res in Nurs and Health 2006; 29:521-532] coupled with a population pharmacokinetic model of CsAexposure [Lukas, J. Clin. Pharmacy and Ther 2005; 30:549-557] to describe the potential impact of drug adherence on CsA exposure in renal transplant recipients, as characterized by variability intrough concentration (C₀) and average concentration (C_avg), and time outside therapeutic exposure range. Exposure variability was assessed using the coefficient of variation (CV%) with a CV% greater than 28.05 deemed high for C₀ and that exceeding 28.4 deemed high for C_avg. Real world adherence patterns were simulated according to the patient clustersdescribed by Russell et al, namely, almost always on time, frequently on time, rarely on time/frequently late doses, rarely on time/frequently missed doses, and all others.

Results:
There is large variability in C_avg despite dose adjustments based on therapeutic drug monitoring of C₀. Furthermore, real-world adherence translates to about 67% of patientsexperiencing a high CV% in C₀ and nearly 29% of patients experiencing a high CV% in C_avg.

Conclusions:
Real-world adherence patterns introduce substantial variability in CsA drug exposure as demonstrated by the high CV% in C₀ and C_avg. Our model-based approach to characterize therelationship between adherence and drug exposure may have implications in linking adherence to health outcomes among transplant recipients; further studies are warranted to highlight themulti-dimensional link between therapeutic dose/exposure, adherence and eventual health outcomes to pave the way for developing immunosuppressive regimens that may optimize the likelihood ofadherence (and hence, possibly outcomes) over the long-term.

Disclosure: All authors have declared no conflicts of interest.