Risk Stratification for Rejection and Infection after Kidney Transplantation

Abstract

Background and objectives: Definition of individual risk profile is the first step to implement strategies to keep the delicate balance between under- and overimmunosuppression after kidney transplantation.

Design, setting, participants, & measurements: We used data from the Efficacy Limiting Toxicity Elimination Symphony Study (1190 patients between 2002 and 2004) to model risk of rejection and infection in the first year after kidney transplantation. External validation was performed in a study population from the Fixed-Dose Concentration-Controlled Trial (630 patients between 2003 and 2006).

Results: Despite different temporal dynamics, rejections and severe infections had similar overall incidences in the first year after transplantation (23.4% and 25.5%, respectively), and infections were the principal cause of death (43.2% of all deaths). Recipient older age, deceased donor, higher number of HLA mismatches, and high risk for cytomegalovirus disease were associated with infection; deceased donor, higher number of HLA mismatches, and immunosuppressive therapy including cyclosporin A (compared with tacrolimus), with rejection. These factors were integrated into a two-dimensional risk stratification model, which defined four risk groups: low risk for infection and rejection (30.8%), isolated risk for rejection (36.1%), isolated risk for infection (7.0%), and high risk for infection and rejection (26.1%). In internal validation, this model significantly discriminated the subgroups in terms of composite end point (low risk for infection/rejection, 24.4%; isolated risk for rejection and isolated risk for infection, 31.3%; high risk for infection/rejection, 54.4%; P<0.001), rejection episodes (isolated risk for infection and low risk for infection/rejection, 13.0%; isolated risk for rejection and high risk for infection/rejection, 24.2%; P=0.001), and infection episodes (low risk for infection/rejection and isolated risk for rejection, 12.0%; isolated risk for infection and high risk for infection/rejection, 37.6%; P<0.001). External validation confirmed the applicability of the model to an independent cohort.

Conclusions: We propose a two-dimensional risk stratification model able to disentangle the individual risk for rejection and infection in the first year after kidney transplantation. This concept can be applied to implement a personalized immunosuppressive and antimicrobial treatment approach.

Keywords: cause of death; cyclosporin; death; humans; immunosuppression; kidney transplantation; tacrolimus; transplant infectious disease; transplant outcomes; transplant recipients.

Figure 1.

Rejections and severe infections have similar incidences in the first year after transplantation. Kaplan–Meier estimate of freedom from the rejection end point and the infection end point. Kaplan–Meier curves in consideration of the complete study population of the Efficacy Limiting Toxicity Elimination Symphony Study (study arms A–C; n=1190). The curves for infection (red) and rejection (purple) end points intersect at day 139 after transplantation.

Figure 2.

Two–dimensional risk stratification for serious infection and rejection. The risk for rejection and infection was calculated for each patient in the Efficacy Limiting Toxicity Elimination Symphony Study (study arms A–C; n=1190) and displayed in a two-dimensional plot (x axis, rejection; y axis, infection). The two–dimensional risk space was divided in four quadrants by an average patient. The panels indicate the influences of (A) age, (B) donor type, (C) cytomegalovirus (CMV) status, and (D) HLA mismatches on the individual risk profile. BPAR, biopsy–proven acute rejection; CMV D+/R−, high risk for CMV disease with a seropositive donor and a seronegative recipient; EDC, extended criteria donor.

Figure 3.

The two-dimensional risk stratification model discriminated the subgroups in terms of composite end point, rejection and infection in the internal validation. Patients in the validation cohort were classified in four risk groups according to the two–dimensional stratification model. The registered incidences of infection and rejection end points in the four subgroups are shown. The area of the pie plot is proportional to the event frequency (proportion of patients with an event of any type in the respective quadrant). The compartments of the pie plots indicate the incidence of rejection and infection in patients with at least one episode. BPAR, biopsy–proven acute rejection; Inf, infection; ir, low risk for both infection and rejection; iR, low risk for infection and high risk for rejection; Ir, high risk for infection and low risk for rejection; IR, high risk for both infection and rejection.