Individual dynamic prediction and prognostic analysis for long-term allograft survival after kidney transplantation

Abstract

Background Predicting allograft survival is vital for efficient transplant success. With dynamic changes in patient conditions, clinical indicators may change longitudinally, and doctors’ judgments may be highly variable. It is necessary to establish a dynamic model to precisely predict the individual risk/survival of new allografts. Methods The follow-up data of 407 patients were obtained from a renal allograft failure study. We introduced a landmarking-based dynamic Cox model that incorporated baseline values (age at transplantation, sex, weight) and longitudinal changes (glomerular filtration rate, proteinuria, hematocrit). Model performance was evaluated using Harrell’s C-index and the Brier score. Results Six predictors were included in our analysis. The Kaplan–Meier estimates of survival at baseline showed an overall 5-year survival rate of 87.2%. The dynamic Cox model showed the individual survival prediction with more accuracy at different time points (for the 5-year survival prediction, the C-index = 0.789 and Brier score = 0.065 for the average of all time points) than the static Cox model at baseline (C-index = 0.558, Brier score = 0.095). Longitudinal covariate prognostic analysis (with time-varying effects) was performed. Conclusions The dynamic Cox model can utilize clinical follow-up data, including longitudinal patient information. Dynamic prediction and prognostic analysis can be used to provide evidence and a reference to better guide clinical decision-making for applying early treatment to patients at high risk.

Variation in Post-Transplant Cancer Incidence among Italian Kidney Transplant Recipients over a 25-Year Period

“…The knowledge of modifiable risk factors and the availability of individualized screening may improve prevention and, therefore, the clinical outcome of KT recipients [36]. Close advice in cancer screening and prevention has long been suggested, but recently more tailored and intensified prognostic and predictive analyses have been suggested to better guide treatment modulation in high-risk patients [37,38]. Informed Consent Statement: Informed consent was obtained from all subjects involved in the study at time of transplant.…”

Porcine anti-human lymphocyte immunoglobulin depletes the lymphocyte population to promote successful kidney transplantation

“…Kidney transplantation (KTx) is the most effective treatment for end-stage renal disease ( 1 , 2 ). The development of immunosuppressant therapies has greatly improved organ and recipient survival ( 3 – 5 ).…”