Impact of age, gender and race on patient and graft survival following renal transplantation--developing country experience.
BACKGROUND
Optimising renal allograft survival is crucially important in developing countries because of limited resources to treat irreversible renal failure. However, although many factors can be manipulated to improve outcome, certain demographic factors are immutable in individual patients. The present study evaluated the impact of age, gender and race on the outcome of renal transplantation.


METHODS
Relevant data were reviewed for 542 patients receiving primary renal allografts over a 23-year period. The survival of patients and grafts were calculated using the Kaplan-Meier method. Both univariate and multivariate analyses were used to determine the association between the demographic factors and patient and graft survival.


RESULTS
Actuarial survival of both patients and grafts decreased with increasing age. The most striking differences were demonstrated when patients older than 40 years were compared with younger patients. However, when patient survival was censored for death with functioning grafts--a very important cause of graft loss--then actuarial graft survival improved with increasing age. There was no gender difference in graft survival, but female recipients of renal allografts had a higher mortality than their male counterparts. There were no racial differences in either patient or graft survival.


CONCLUSIONS
Age is an important determinant of outcome after renal transplantation, but race is not. Gender does not influence graft survival, but females do have a higher overall mortality rate following renal transplantation at our centre.
Moosa
M Rafique
MR
Department of Internal Medicine, University of Stellenbosh and Renal Unit, Tygerberg Hospital, W Cape.
D000328:Adult; D005260:Female; D006085:Graft Survival; D006801:Humans; D007166:Immunosuppressive Agents / Q000627:therapeutic use; D016030:Kidney Transplantation / Q000208:ethnology / Q000276:immunology / Q000401:mortality / Q000706:statistics & numerical data*; D008297:Male; D008875:Middle Aged; D015999:Multivariate Analysis; D016016:Proportional Hazards Models; D013019:South Africa / Q000453:epidemiology; D016019:Survival Analysis
D007166:Immunosuppressive Agents