Predictive Score for Posttransplantation Outcomes

Abstract

Background Most current scoring tools to predict allograft and patient survival upon kidney transplantion(Tx) are based on variables collected posttransplantation. We developed a novel score to predict posttransplant outcomes using pretransplant information including routine laboratory data available prior to or at the time of transplantation. Methods Linking the 5-year patient data of a large dialysis organization to the SRTR, we identified 15,125 hemodialysis patients who underwent first deceased Tx. Prediction models were developed using Cox models for (a)mortality, (b)allograft loss(death censored) and (c)combined death or transplant failure. The cohort was randomly divided into a two-thirds set(Nd=10,083) for model development and a one-third set(Nv=5,042) for validation. Model predictive discrimination was assessed using the index of concordance, or C statistic, which accounts for censoring in time-to-event models(a–c). We used the bootstrap method to assess model overfitting and calibration using the development dataset. Results Patients were 50±13 years old and included 39% women, 15% African-Americans and 36% diabetics. For prediction of post-transplant mortality and graft loss, 10 predictors were used (recipients’ age, cause and length of ESRD, hemoglobin, albumin, selected comorbidities, race and type of insurance as well as donor age, diabetes status, extended criteria donor kidney(ECD), and number of HLA mismatches). The new model (www.TransplantScore.com) showed the overall best discrimination(C-statistics:0.70(95%CI: 0.67–0.73) for mortality;0.63(95%CI: 0.60–0.66) for graft failure;0.63(95%CI: 0.61–0.66) for combined outcome). Conclusions The new prediction tool, using data available prior to the time of transplantation, predicts relevant clinical outcomes and may perform better to predict patients’ graft survival than currently used tools.

Prediction of Three-Year Mortality After Deceased Donor Kidney Transplantation in Adults with Pre-Transplant Donor and Recipient Variables

“…It is striking that this study externally confirms the prognostic relevance of an older recipient age and pre-existing recipient diabetes for an increased risk of mortality after kidney transplantation in a European cohort as has been published before in a report from a large registry trial from the United States which has proposed a predictive score for post-transplant mortality [15].…”

The Authors’ Reply

“…In this study, our main goal was to develop a clinically useful prediction score which can be used prior to the time of transplantation to inform both the transplant team and the patient about the most likely outcome, if the transplant is to be performed (http://www.transplantscore.com/). [2] We agree with Wang and colleagues that including intra- and postoperative variables would likely increase the discrimination ability of our score. However, including these variables would make our score amenable to the major limitations for assessment of the predicted longevity of the graft and patient survival at or before the time of the transplantation.…”

Mortality in Elderly Waiting-List Patients Versus Age-Matched Kidney Transplant Recipients: Where is the Risk?

“…In a sub-analysis of 67 elderly patients (70 years or older) who received a KT, performed by Dusseux et al using logistic regression in a cohort of ESRD patients from the French national registry, patients with a risk score <6 points showed a good prognosis at the first three years post-transplantation [100]. Using a recent predictive score proposed by Molnar et al [127], our elderly Patient A would have a probability of death at the first and fifth year post-transplantation of 12% and 28%, respectively. By contrast, our Patient B would have a higher mortality risk (16% and 50%, respectively), as shown in Table 3.…”