An Alternative Approach for Statistical Analysis of Kidney Transplant Data: Multivariate Analysis of Single-center Experience
American Journal of Kidney Diseases
To avoid the center effect and the possible hidden interactions of multicenter studies, the validity of the Cox Proportional Hazards Model for the analysis of a single-center kidney transplant program was tested, considering 287 renal transplants performed in a 10-year period. The inclusion of type of donor and main immunosuppressive drug as covariates in the model did not violate the proportionality assumption of the Cox model. According to this method, the following covariates were significant in predicting graft survival: cyclosporine, type of donor, good human leukocyte antigen (HLA)-A and HLA-B match (DR data were not considered), highest percentage of reactive antibodies against panel cells, and nephroangiosclerosis as a primary renal disease. Cyclosporine did not significantly improve graft survival in living related donor transplants. Pretransplant blood transfusions, cold ischemia time, and donor ABO blood group were initially significant but dropped out in the step-down procedure. Recipient's age at transplant, cyclosporine, HLA-A and HLA-B match, and nephroangiosclerosis were significant in predicting patient survival. It was concluded that using long-term data of cadaveric and living related renal transplants either on azathioprine or cyclosporine is a valid way to perform multivariate analysis of single-center transplant programs that do not have large samples.