Using Information Available at the Time of Donor Offer to Predict Kidney Transplant Survival Outcomes: A Systematic Review of Prediction Models.

Statistical models that can predict graft and patient survival outcomes following kidney transplantation could be of great clinical utility. We sought to appraise existing clinical prediction models for kidney transplant survival outcomes that could guide kidney donor acceptance decision-making. We searched for clinical prediction models for survival outcomes in adult recipients with single kidney-only transplants. Models that require information anticipated to become available only after the time of transplantation were excluded as, by that time, the kidney donor acceptance decision would have already been made. The outcomes of interest were all-cause and death-censored graft failure, and death. We summarised the methodological characteristics of the prediction models, predictive performance and risk of bias. We retrieved 4,026 citations from which 23 articles describing 74 models met the inclusion criteria. Discrimination was moderate for all-cause graft failure (C-statistic: 0.570-0.652; Harrell's C: 0.580-0.660; AUC: 0.530-0.742), death-censored graft failure (C-statistic: 0.540-0.660; Harrell's C: 0.590-0.700; AUC: 0.450-0.810) and death (C-statistic: 0.637-0.770; Harrell's C: 0.570-0.735). Calibration was seldom reported. Risk of bias was high in 49 of the 74 models, primarily due to methods for handling missing data. The currently available prediction models using pre-transplantation information show moderate discrimination and varied calibration. Further model development is needed to improve predictions for the purpose of clinical decision-making. Systematic Review Registration: https://osf.io/c3ehp/l.

An external validation of the Kidney Donor Risk Index in the UK transplant population in the presence of semi-competing events.

BACKGROUND: Transplantation represents the optimal treatment for many patients with end-stage kidney disease. When a donor kidney is available to a waitlisted patient, clinicians responsible for the care of the potential recipient must make the decision to accept or decline the offer based upon complex and variable information about the donor, the recipient and the transplant process. A clinical prediction model may be able to support clinicians in their decision-making. The Kidney Donor Risk Index (KDRI) was developed in the United States to predict graft failure following kidney transplantation. The survival process following transplantation consists of semi-competing events where death precludes graft failure, but not vice-versa. METHODS: We externally validated the KDRI in the UK kidney transplant population and assessed whether validation under a semi-competing risks framework impacted predictive performance. Additionally, we explored whether the KDRI requires updating. We included 20,035 adult recipients of first, deceased donor, single, kidney-only transplants between January 1, 2004, and December 31, 2018, collected by the UK Transplant Registry and held by NHS Blood and Transplant. The outcomes of interest were 1- and 5-year graft failure following transplantation. In light of the semi-competing events, recipient death was handled in two ways: censoring patients at the time of death and modelling death as a competing event. Cox proportional hazard models were used to validate the KDRI when censoring graft failure by death, and cause-specific Cox models were used to account for death as a competing event. RESULTS: The KDRI underestimated event probabilities for those at higher risk of graft failure. For 5-year graft failure, discrimination was poorer in the semi-competing risks model (0.625, 95% CI 0.611 to 0.640;0.611, 95% CI 0.597 to 0.625), but predictions were more accurate (Brier score 0.117, 95% CI 0.112 to 0.121; 0.114, 95% CI 0.109 to 0.118). Calibration plots were similar regardless of whether the death was modelled as a competing event or not. Updating the KDRI worsened calibration, but marginally improved discrimination. CONCLUSIONS: Predictive performance for 1-year graft failure was similar between death-censored and competing event graft failure, but differences appeared when predicting 5-year graft failure. The updated index did not have superior performance and we conclude that updating the KDRI in the present form is not required.

Serum neopterin as an indicator of increased risk of renal allograft rejection.

Acute rejection remains associated with poor graft outcome. An early predictor of acute renal transplant rejection is the long sought after goal for transplant immunologists. In this study we measured levels of serum neopterin at day 5 post-transplant in a cohort of 216 consecutive renal allograft recipients, and compared this with serum creatinine and acute rejection episodes during the first year post transplant. We compared serum neopterin in recipients from living donors (LD), donors after brain death (DBD) and donors after cardiac death (DCD). In all cases higher neopterin levels were correlated with acute rejection in the first year post transplant, but this was only significant in recipients of DCD kidneys who suffered acute cellular or vascular rejection (p=0.04, odds ratio 1.08, 95% CI 1.003-1.012). The neopterin/creatinine ratio, which takes into account the effect of kidney function on circulating neopterin levels, was significantly higher for all recipients who suffered biopsy proven cellular or vascular rejection in the first year post transplant, compared to all other patients (p=0.001, for an increase of 0.1, odds ratio=1.64, 95% CI 1.21-2.20). The ability to use non-invasive biomarkers in the transplant recipient has the potential to increase transplant survival for these patients.

A retrospective study of the prognostic impact of cytokine secretion in mixed lymphocyte culture on long-term graft function following allogeneic renal transplantation.

We have previously shown that in vitro measurement of cytokine production prior to renal transplantation can provide predictive information on the risk of acute rejection. Our earlier studies demonstrated that patients who secreted high levels of interferon-gamma (IFN-gamma) in OKT3-stimulated or mixed lymphocyte culture had a significantly increased risk of acute rejection compared with patients who secreted lower levels. In this study, we performed a retrospective analysis of the same cohort of patients in order to determine the prognostic value of cytokine profiles and other variables on long-term graft function. Our results show that high levels of IFN-gamma in pretransplant mixed lymphocyte culture are a highly significant predictor of poorer creatinine levels at 18, 24 and 36 months post-transplant.