Abeling T, et al. - Researchers established multivariable Cox models for risk assessment at 3 and 12- months post- kidney transplantation as identification and quantification of the relevant factors for death can improve patients’ individual risk assessment and decision-making. They used a well-documented patient cohort (n = 892) in a renal transplant programme with protocol biopsies. They noted that the important areas that need special attention in the pre- and post-transplant care of renal transplant patients were indicated by the identified factors (age, pre-transplant heart failure and a score of cardiovascular disease and type 2 diabetes, post-transplant urinary tract infection, treatment of rejection, new-onset heart failure, coronary events and malignancies). Individual risks that may contribute to decreased survival could be weighed using nomograms, a tool offered on the basis of these models.

Methods

• This study included patients transplanted between 2000 and 2007 followed up to 11 years (total observation 5227 patient-years; median 5.9 years).
• Loss to follow-up was negligible (n = 15).
• Researchers performed a total of 2251 protocol biopsies and 1214 biopsies for cause and treated all rejections and clinical borderline rejections in protocol biopsies.

Results

• Data revealed that 10-year patient survival was 78%.
• Researchers found inferior survival of patients with graft loss and superior survival of patients with living-donor transplantation.
• They noted that at 3 and 12 months, the models had eight common factors, including age, pre-transplant heart failure and a score of cardiovascular disease and type 2 diabetes, post-transplant urinary tract infection, treatment of rejection, new-onset heart failure, coronary events and malignancies.
• At 3 months, deceased donor transplantation, transplant lymphocele, BK virus nephropathy and severe infections were reported as additional variables of the model.
• At 12 months, they found that graft function and graft loss were significant factors of the model.
• Good discrimination of the models was shown by internal validation and validation with a separate cohort of patients (n = 349).