Estimated Post Transplant Survival Research Articles

Association of Race and Ethnicity With High Longevity Deceased Donor Kidney Transplantation Under the US Kidney Allocation System

Rationale & ObjectiveThe US Kidney Allocation System (KAS) prioritizes candidates with ≤20% Estimated Post-Transplant Survival (EPTS) for high longevity kidneys defined by a ≤20% Kidney Donor Profile Index (KDPI). Use of EPTS in the KAS deprioritizes candidates with older age, diabetes, and longer dialysis durations. We assessed whether this use also disadvantages racial-ethnic minority candidates, who are younger but more likely to have diabetes and longer durations of kidney failure requiring dialysis. Study DesignObservational cohort study. Setting& Participants: Adult candidates for and recipients of kidney transplantation represented in the Scientific Registry of Transplant Recipients from January 2015 through December 2020. ExposureRace and ethnicity. OutcomesAge-adjusted assignment to ≤20% EPTS, transplantation of a ≤20% KDPI kidney, and post-transplant survival in longevity matched recipients by racial-ethnicity. Analytic ApproachMultivariable logistic regression, Fine-Gray competing risks survival analysis, and Kaplan-Meier and Cox Proportional Hazards methods. ResultsThe cohort included 199,444 candidates (7% Asian, 29% Black, 19% Hispanic/Latino, 43% White) listed for deceased donor kidney transplantation. Non-White candidates had significantly higher rates of diabetes, longer dialysis duration, and were younger than White candidates. Adjusted for age, Asian, Black, and Hispanic/Latino candidates had significantly lower odds of having a ETPS score ≤20% (OR 0.86, [0.81, 0.91], 0.52 [0.50, 0.54], and 0.49, [0.47, 0.51]), and were less likely to receive a ≤20% KDPI kidney (subHR 0.70 [0.66, 0.75], 0.89 [0.87, 0.92], and 0.73 [0.71, 0.76]), compared to White candidates. Among recipients with ≤20% EPTS scores transplanted with a ≤20% KDPI deceased donor kidney, Asian and Hispanic recipients had lower post-transplant mortality (HR 0.45 [0.27, 0.77], and 0.63 [0.47, 0.86]) and Black recipients had higher but not statistically significant post-transplant mortality (HR 1.22 [0.99, 1.52]) compared to White recipients. LimitationsProvider reported race-ethnicity data and 5-year post transplant follow-up period. ConclusionsThe US kidney allocation system is less likely to identify racial-ethnic minority candidates as having a ≤20% EPTS score which triggers allocation of high longevity deceased donor kidneys. These findings should inform the OPTN about how to remedy racial/ethnic disparities introduced through KAS’s current approach of allocating allografts with longer predicted longevity to recipients with longer estimated post-transplant survival.

Continuous allocation: The problem with EPTS and pediatric kidney candidates.

The 2014 Kidney Allocation System (KAS) introduced longevity matching for adult candidates using the Estimated Post-Transplant Survival (EPTS) score, which includes candidate age, time on dialysis, diabetes status, and number of previous solid organ transplants. The proposed continuous distribution framework may expand the use of this attribute to pediatric candidates, but there is no data on its performance among pediatric kidney transplant recipients. We performed a retrospective cohort study of 6800 pediatric kidney transplant recipients from 2001 to 2011 using Organ Procurement and Transplantation Network (OPTN) data. EPTS score was calculated for each patient and compared to reported patient survival to estimate the validity of the score in children. The median age of patients was 14.01 years (IQR 9.29-16.37 years), and dialysis vintage was 0.67 years (IQR 0-1.82 years). 18.2% of the cohort had a prior transplant and 1% had diabetes. Median EPTS score was 2 (IQR 1-2). Seven percent of patients died during the study period and 54.7% of the cohort was censored prior to 10 years. The c-statistic was 0.505 (95% CI: 0.49-0.53). Overall, EPTS is not a valid predictor of patient survival among pediatric kidney transplant recipients.

Graft and Patient Survival in Kidney Transplant with Deceased Donor Using KDRI (Kidney Donor Risk Index), KDPI (Kidney Donor Profile Index), and EPTS (Estimated Post-Transplant Survival) in Colombia.

BACKGROUND EPTS (Estimated Post-Transplant Survival), KDRI (Kidney Donor Risk Index), and KDPI (Kidney Donor Profile Index) were developed aiming to ameliorate donor-recipient longevity matching in kidney transplants. They are based on a prediction model made using the United States population; evidence of their use outside EEUU remains limited. The aim of this study was to describe the quality of deceased-donor kidneys and to determine recipient and graft survival, glomerular filtration rate, and incidence of delayed graft function in renal transplantation according to these indices in Cali, Colombia. MATERIAL AND METHODS In this historical cohort study, Kaplan-Meier method was used to analyze survival of recipient and graft according to the values of the indices categorized by quintiles. Glomerular filtration rate and incidence of delayed graft function were also analyzed according to KDRI and KDPI. RESULTS We included 380 patients. Medians of EPTS, KDRI, and KDPI were 24% (IQR 9-60), 0.8 (IQR 0.71-0.99), and 27% (IQR 13-49), respectively. Two-year survival was 97.8% in recipients with EPTS ≤20% and it decreased with higher values of the index. Recipient and graft survival were lower for all periods when donors had KDPI >80%. Incidence of delayed graft function was higher in patients whose donors had KDPI ≥60% (44% vs 21%). Glomerular filtration rate decreased with the highest values of KDPI for all periods. CONCLUSIONS Our study represents the initial evaluation of the usefulness of these indices in Colombia. Our results suggest that KDRI, KDPI, and EPTS may serve as valuable tools for kidney allocation in our setting. Further research with larger sample sizes is necessary to validate these indices in our population.

Characterization of Transplant Center Decisions to Allocate Kidneys to Candidates With Lower Waiting List Priority

Allocation of deceased donor kidneys is meant to follow a ranked match-run list of eligible candidates, but transplant centers with a 1-to-1 relationship with their local organ procurement organization have full discretion to decline offers for higher-priority candidates and accept them for lower-ranked candidates at their center. To describe the practice and frequency of transplant centers placing deceased donor kidneys with candidates who are not the highest rank at their center according to the allocation algorithm. This retrospective cohort study used 2015 to 2019 organ offer data from US transplant centers with a 1-to-1 relationship with their local organ procurement organization, following candidates for transplant events from January 2015 to December 2019. Participants were deceased kidney donors with a single match-run and at least 1 kidney transplanted locally and adult, first-time, kidney-only transplant candidates receiving at least 1 offer for a locally transplanted deceased donor kidney. Data were analyzed from March 1, 2022 to March 28, 2023. Demographic and clinical characteristics of donors and recipients. The outcome of interest was kidney transplantation into the highest-priority candidate (defined as transplanted after zero declines for local candidates in the match-run) vs a lower-ranked candidate. This study assessed 26 579 organ offers from 3136 donors (median [IQR] age, 38 [25-51] years; 2903 [62%] men) to 4668 recipients. Transplant centers skipped their highest-ranked candidate to place kidneys further down the match-run for 3169 kidneys (68%). These kidneys went to a median (IQR) of the fourth- (third- to eighth-) ranked candidate. Higher kidney donor profile index (KDPI; higher score indicates lower quality) kidneys were less likely to go to the highest-ranked candidate, with 24% of kidneys with KDPI of at least 85% going to the top-ranked candidate vs 44% of KDPI 0% to 20% kidneys. When comparing estimated posttransplant survival (EPTS) scores between the skipped candidates and the ultimate recipients, kidneys were placed with recipients with both better and worse EPTS than the skipped candidates, across all KDPI risk groups. In this cohort study of local kidney allocation at isolated transplant centers, we found that centers frequently skipped their highest-priority candidates to place kidneys further down the allocation prioritization list, often citing organ quality concerns but placing kidneys with recipients with both better and worse EPTS with nearly equal frequency. This occurred with limited transparency and highlights the opportunity to improve the matching and offer algorithm to improve allocation efficiency.

Temporal validation of the Australian estimated post-transplant survival score.

The Australian estimated post-transplant survival (EPTS-AU) prediction score was developed by re-fitting the United States of America EPTS, without diabetes, to the Australian and New Zealand kidney transplant population over 2002-2013. The EPTS-AU score incorporates age, previous transplantation and time on dialysis. Diabetes was excluded from the score, as this was not previously recorded in the Australian allocation system. In May 2021, the EPTS-AU prediction score was incorporated into the Australian kidney allocation algorithm to optimize utility for recipients (maximized benefit). We aimed to temporally validate the EPTS-AU prediction score to ensure it can be used for this purpose. Using the Australia and New Zealand Dialysis and Transplant (ANZDATA) Registry, we included adult recipients of deceased donor kidney-only transplants between 2014 and 2021. We constructed Cox models for patient survival. We assessed validation using measures of model fit (Akaike information criterion and misspecification), discrimination (Harrell's C statistic and Kaplan-Meier curves), and calibration (observed vs. predicted survival). Six thousand four hundred and two recipients were included in the analysis. The EPTS-AU had moderate discrimination with a C statistic of 0.69 (95% CI 0.67, 0.71), and clear delineation between Kaplan-Meier's survival curves of EPTS-AU. The EPTS was well calibrated with the predicted survivals equating with the observed survival outcomes for all prognostic groups. The EPTS-AU performs reasonably well in choosing between recipients (discrimination) and to predict a recipient's survival (calibration). Reassuringly, the score is functioning as intended to predict post-transplant survival for recipients as part of the national allocation algorithm.

Prevalence and Predictors of Suboptimal Kidney Donor Profile Index (KDPI) and Estimated Post-Transplant Survival (EPTS) Mismatches in Kidney Transplant Recipients

Prevalence and Predictors of Suboptimal Kidney Donor Profile Index (KDPI) and Estimated Post-Transplant Survival (EPTS) Mismatches in Kidney Transplant Recipients

Kidney Donor Profile Index and allograft outcomes: interactive effects of estimated post-transplant survival score and ischaemic time.

The Kidney Donor Profile Index (KDPI) is routinely reported by the donation agencies in Australia. We determined the association between KDPI and short-term allograft loss and assessed if this association was modified by the estimated post-transplant survival (EPTS) score and total ischaemic time. Using data from the Australia and New Zealand Dialysis and Transplant Registry, the association between KDPI (in quartiles) and 3-year overall allograft loss was examined using adjusted Cox regression analysis. The interactive effects between KDPI, EPTS score and total ischaemic time on allograft loss were assessed. Of 4006 deceased donor kidney transplant recipients transplanted between 2010 and 2015, 451 (11%) recipients experienced allograft loss within 3years post-transplant. Compared with recipients of kidneys with a KDPI of 0-25%, recipients who received donor kidneys with a KDPI >75% experienced a 2-fold increased risk of 3-year allograft loss {adjusted hazard ratio [HR] 2.04 [95% confidence interval (CI) 1.53-2.71]}. The adjusted HRs for kidneys with a KDPI of 26-50% and 51-75% were 1.27 (95% CI 0.94-1.71) and 1.31 (95% CI 0.96-1.77), respectively. There were significant interactions between KDPI and EPTS scores (P-value for interaction <.01) and total ischaemic time (P-value for interaction <.01) such that the associations between higher KDPI quartiles and 3-year allograft loss were strongest in recipients with the lowest EPTS scores and longest total ischaemic time. Recipients with higher post-transplant expected survival and transplants with longer total ischaemia who received donor allografts with higher KDPI scores experienced a greater risk of short-term allograft loss compared with those recipients with reduced post-transplant expected survival and with shorter total ischemia.

The strategy of diminishing age gap effect on different donor-recipient combinations in living donor kidney transplantation.

The disparity between kidney donation and the number of uremic patients on the waiting list has increased the demand for older live-donor kidneys (OLK). However, the donor-recipient age gap may have an impact on the recipient's outcome. Patients who underwent living donor kidney transplantation at our institute between 2005 and 2019 were enrolled and categorized into four donor-recipient groups according to age (≥50 years and <50 years). The Estimated Post-Transplant Survival (EPTS) score was used to quantify the recipient's condition. Adjusted models analyzed recipient outcomes and related risks among the four groups. Of the 154 pairs of live donors and recipients, OLK did not influence overall or death-censored graft survival. The four donor-recipient combinations had similar recipient outcomes, except it slightly worsened in the "old donor to young recipient" group. The EPTS score (adjusted HR, 1.02; 95% CI, 1.01-1.04; p = 0.014) and rejection (adjusted HR, 4.26; 95% CI, 1.36-13.37; p = 0.013) were significant risk factors for overall and death-censored graft survival, respectively. Recipients with pretransplant diabetes or prior solid organ transplantation could have amplified risk effects. The main causes of graft loss were death in older recipients and chronic rejection in younger recipients. OLK is safe for young recipients. Nevertheless, adequate immunosuppression should be maintained to prevent rejection and subsequent graft loss, especially for those receiving second kidney transplantation. In contrast, older recipients should avoid overt immunosuppression and control their comorbidities, such as diabetes-related complications to improve their long-term outcomes.

Survival Benefit in Older Patients Transplanted With Viremic Hepatitis C Positive Kidneys When Compared With High KDPI Kidneys.

Because of the continued demand in kidney transplantation, organs from donors with risk criteria for blood-borne viruses, high Kidney Donor Profile Index (KDPI) kidneys, and hepatitis C virus (HCV)-positive kidneys are being considered. There continues to be reluctance on the part of the providers and the candidates to accept HCV-positive kidneys. We conducted a retrospective analysis of the Organ Procurement and Transplantation Network database of all adult (≥18 y old) recipients undergoing kidney transplant from May 10, 2013, to June 30, 2021. We compared patient and graft survival in candidates who received HCV-positive kidneys versus non-hepatitis C (Hep C) high KDPI kidneys by estimated posttransplant survival (EPTS) groups. HCV-viremic kidneys were transplanted in 5.6% of patients in the EPTS >61% group compared with 5.1% of patients in the 21%-60% EPTS group and 1.9% of 0%-20% EPTS group ( P < 0.001). Of all transplants performed in the EPTS 61%-100% group, 11.9% were KDPI >85% compared with 5.2% in the EPTS 21%-60%, and 0.5% in the EPTS 0%-20%. Patient survival was significantly longer at 1, 3, and 5 y in the EPTS >61% group who received Hep C-viremic or -nonviremic allografts compared with non-Hep C kidneys with KDPI >85%. When it comes to listing, only 25% of candidates in the EPTS >61% group were listed for Hep C nucleic acid testing-positive kidneys in 2021. Our findings could be used for counseling candidates on the types of kidneys they should consider for transplantation. Also, listing practices for viremic Hep C kidneys need continued re-evaluation.

Comparison of Clinical Outcomes Among Deceased Donor Kidney Transplant Recipients Before and After Utilizing Estimated Posttransplant Survival Score for Kidneys Allocation in Malaysia

The Malaysian Kidney Allocation System implemented in 2020 includes only kidney transplant candidates with estimated posttransplant survival (EPTS) score of ≤20%, in replacement of Malaysian Organs Sharing System, which was based solely on dialysis vintage. We aim to compare the clinical outcomes of deceased-donor kidney transplant recipients (DDKTRs) with EPTS ≤20% to those with EPTS >20%. All DDKTRs between January 1, 2015, and December 29, 2020, were included and categorized into 2 groups: EPTS ≤20% and EPTS >20%. Cox regression was performed to evaluate the association of EPTS score and patient survival. The rate of postoperative complications, graft failure and patient survival were compared between 2 groups. Data were analyzed with SPSS v26 and R v4.0.4. The study complies with the Helsinki Congress and the Istanbul Declaration. We included 159 DDKTRs, with a median follow-up of 25 months (range, 10-60 months). The mean age of those with EPTS ≤20% was 32.2 ± 3.4 years and those with EPTS >20% was 46.0 ± 6.7 years, and the median EPTS score were 16% (range, 12%-18%) and 38% (range, 27%-56.5%), respectively. EPTS score was associated with patient survival (hazard ratio, 1.031; 95% CI 1.010-1.052; P=.003), and the cutoff points of 30% and above were associated with worse survival. It showed good discrimination (C-index, 0.729; 95% CI 0.579-0.878; P=.003) and the optimal cutoff value was 38% (65.5% sensitivity, 68.8% specificity, 17.8% positive predictive value, and 95.8% negative predictive value). Both groups had similar rate of surgical complications (P=.191), graft failure (P=.503), and patient survival (P=.654), but those with EPTS >20% had higher incidence of urinary tract infection (9.3% vs 27.6%, P=.016). There was no difference in clinical outcomes using an EPTS cutoff point of 20% but worse patient survival if higher cutoff point was used.

First Asian Kidney Donor Profile Index (KDPI) and Estimated Post-Transplant Survival (EPTS) models, with validation against US models in Thai population.

Differences in transplant characteristics limit the application of kidney donor profile index (KDPI) and estimated post-transplant survival (EPTS) models developed in Western countries to Asian populations. We analyzed data of the Thai Transplant Registry and the Thai Red Cross Society on 2558 DDKTs performed between 2001 and 2014. Thai KDPI and EPTS models were developed using Cox regression, and validation against the US models. Thai KDPI was developed based on seven donor factors: age, height, best estimated glomerular filtration rate, diabetes mellitus, hypertension, cerebrovascular accident, and adrenaline infusion. The Thai and US donor risk index had comparable predictive abilities for transplant survival (C-statistics .5871vs. .5548; P=.429). KTs from donors with a US KDPI>70% demonstrated significantly worse 5-year transplant survival. The Thai EPTS model was developed from four recipient factors: age, body weight, diabetes mellitus, and hepatitis C infection. The C-statistics of the Thai and US EPTS models were comparable (.5924vs. .6039; P=.360). A US EPTS>70% was revealed in only 2.5% of our cohort. The first simplified KDPI and EPTS models for an Asian population were developed. Our models are available at www.thai-kdpi-epts.org.

Artificial Intelligence-A Tool for Risk Assessment of Delayed-Graft Function in Kidney Transplant.

Delayed-graft function (DGF) might be responsible for shorter graft survival. Therefore, a clinical tool predicting its occurrence is vital for the risk assessment of transplant outcomes. In a single-center study, we conducted data mining and machine learning experiments, resulting in DGF predictive models based on random forest classifiers (RF) and an artificial neural network called multi-layer perceptron (MLP). All designed models had four common input parameters, determining the best accuracy and discriminant ability: donor’s eGFR, recipient’s BMI, donor’s BMI, and recipient–donor weight difference. RF and MLP designs, using these parameters, achieved an accuracy of 84.38% and an area under curve (AUC) 0.84. The model additionally implementing a donor’s age, gender, and Kidney Donor Profile Index (KDPI) accomplished an accuracy of 93.75% and an AUC of 0.91. The other configuration with the estimated post-transplant survival (EPTS) and the kidney donor risk profile (KDRI) achieved an accuracy of 93.75% and an AUC of 0.92. Using machine learning, we were able to assess the risk of DGF in recipients after kidney transplant from a deceased donor. Our solution is scalable and can be improved during subsequent transplants. Based on the new data, the models can achieve better outcomes.

VO2peak prior to transplant differentiates survival post kidney transplant.

The OPTN/UNOS utilizes the calculated estimated posttransplant survival (EPTS) score as the measure of post-kidney transplant survival to guide allocation of deceased donor kidney transplantation. This score does not include any metric of functional capacity. Peak oxygen uptake (VO2peak ), is an established predictor of survival among both the general and diseased populations. We assessed the association and discriminative capacity of VO2peak and that of EPTS score and all-cause mortality post-kidney transplant. Additionally, we assessed the "mortality risk" lower VO2peak conferred on those patients with low EPTS score. Among a cohort of 293 transplant recipients with at least 3-years post-transplant follow-up, the median VO2peak was 15.0ml/Kg/min. Lower pre-transplant VO2peak and higher EPTS score conferred higher risk of post-transplant mortality. Among the cohort of "low-risk" patients (patients with EPTS score<50) those with lower VO2peak had significantly higher risk of mortality (log rank p=0.045). In fact, the mortality risk among those with low-EPTS (<50) and low VO2peak <12ml/Kg/min was equivalent to those with high EPTS (>80) score. We concluded functional capacity as defined by VO2peak is an important reflection of post-transplant survival. VO2peak is able to identify those with low EPTS who have similar survival to that of high EPTS phenotype.

Association between ethnicity and kidney transplant waitlist outcomes beyond estimated post‐transplant survival score

White kidney transplant candidates have the highest pre-transplant mortality rate compared to other ethnicities. The reason for a higher mortality rate is not well-understood. Estimated post-transplant survival (EPTS) score has been used to predict patient survival after transplant and may be associated with pre-transplant survival. First-time kidney transplant candidates listed between 2015 and 2018 were identified from the Organ Procurement Transplantation Network database. Individuals listed for multiple organs, at multiple centers, and age <18years were excluded. We examined the impact of ethnicity on waitlist mortality and delisting. A total of 114806 candidates were included. The study population was categorized into four groups which were 43% white, 28% Black, 19.2% Hispanic, and 9.8% "other ethnicities." At 5.2years, the cumulative incidences of death and delist were 32%, 31%, 29%, and 26%, respectively. Compared to whites, adjusted subdistribution hazard ratio (aSHR) for death and delist among Black, Hispanics, and "other ethnicities" were 0.92 (95% CI 0.89-0.95), 0.89 (95% CI 0.85-0.91), and 0.76 (95% CI 0.72-0.80) after adjustment by EPTS along with other factors, respectively. After adjusting for EPTS score along with additional confounding factors and functional status at initial listing, white ethnicity was independently associated with an increased risk for death and delist.

The Sum of Kidney Donor Profile Index and Estimated Post-Transplant Survival Scale and Their Correlation with eGFR Decline in Deceased Donor Kidney Recipients.

The impact of donor quality on post-kidney transplant survival may vary by candidate condition. Analyzing the combined use of the Kidney Donor Profile Index (KDPI) and the estimated post-transplant survival (EPTS) scale and their correlation with the estimated glomerular filtration rate (eGFR) decline in deceased-donor kidney recipients (DDKR). This was a retrospective, observational cohort study. We included DDKRs between 2015 and 2017 at a national third-level hospital. We analyzed 68 DDKR. The mean age at transplant was 41 ± 14 years, 47 (69%) had sensitization events, 18 (26%) had delayed graft function, and 16 (23%) acute rejection. The graft survival at 12 and 36 months was 98.1% (95% CI 94-100) and 83.7% (95% CI 65-100), respectively. The Pearson correlation coefficient between the percentage reduction in the annual eGFR and the sum of EPTS and KDPI scales was r = 0.61, p < 0.001. The correlation coefficient between the percentage reduction in the annual eGFR and the EPTS and KDPI scales separately was r = 0.55, p < 0.001, and r = 0.53, p < 0.001, respectively. The sum of EPTS and KDPI scales can provide a better donor-recipient relationship and has a moderately positive correlation with the decrease in eGFR in DDKR.

Patients with High Priority for Kidney Transplant Who Are Not Given Expedited Placement on the Transplant Waiting List Represent Lost Opportunities.

Kidney transplantation is associated with the best outcomes for most patients with ESKD. The national Kidney Allocation System prioritizes patients with Estimated Post-Transplant Survival (EPTS) scores in the top 20% for expedited access to optimal deceased donor kidneys. We studied adults aged ≥18 years in the United States Renal Data System with top 20% EPTS scores who had been preemptively waitlisted or initiated dialysis in 2015-2017. We evaluated time to waitlist placement, transplantation, and mortality with unadjusted and multivariable survival models. Of 42,445 patients with top 20% EPTS scores (mean age, 38.0 years; 57% male; 59% White patients, and 31% Black patients), 7922 were preemptively waitlisted. Among 34,523 patients initiating dialysis, the 3-year cumulative waitlist placement incidence was 37%. Numerous factors independently associated with waitlisting included race, income, and having noncommercial insurance. For example, waitlisting was less likely for Black versus White patients, and for patients in the lowest-income neighborhoods versus those in the highest-income neighborhoods. Among patients initiating dialysis, 61% lost their top 20% EPTS status within 30 months versus 18% of patients who were preemptively listed. The 3-year incidence of deceased and living donor transplantation was 5% and 6%, respectively, for patients who initiated dialysis and 26% and 44%, respectively, for patients who were preemptively listed. Many patients with ESKDqualifying with top 20% EPTS status are not placed on the transplant waiting list in a timely manner, with significant variation on the basis of demographic and social factors. Patients who are preemptively listed are more likely to receive benefits of top 20% EPTS status. Efforts to expedite care for qualifying candidates are needed, and automated transplant referral for patients with the best prognoses should be considered. This article contains a podcast athttps://www.asn-online.org/media/podcast/JASN/2021_07_30_JASN2020081146.mp3.

Development of predictive score for post-transplant survival based on pre-transplant recipient characteristics.

BackgroundThe new kidney allocation system in the United States has introduced longevity matching, which gives priority to allocating the best quality organs to wait-listed candidates with the longest predicted survival for the efficient utilization of organs that are of limited availability. The estimated post-transplant survival (EPTS) score was developed in the United States to risk-stratify all wait-listed patients. However, prognostic indices used in Western countries were derived from data that may be different for Korea and do not necessarily reflect prognostic values for Korean deceased donor kidney transplantation. Prognostic indices for Korean wait-listed candidates therefore need to be developed from Korean data.MethodsWe analyzed 6,731 adult solitary kidney transplant patients for candidate risk prediction using the national data from the Korean Network for Organ Sharing (KONOS) and National Health Insurance Data Sharing Service (NHISS). Cox regression analysis was used to model the risk of patient death.ResultsThe Korean EPTS (K-EPTS) score was developed based on four recipient parameters (age, diabetes mellitus, hepatitis C virus, and duration of dialysis) that showed a significant association with post-transplant survival. K-EPTS scores showed good discrimination (C-statistics 0.690; 95% confidence interval, 0.666–0.715). Moreover, the ability of the K-EPTS score to discriminate patient survival was better than that of the EPTS according to the criteria of the United Network for Organ Sharing (US-EPTS) score (P<0.001).ConclusionsThe K-EPTS score, which was developed based on Korean national data, is expected to contribute to the assessment of recipient prognosis and efficient utilization of deceased donor kidneys.

Candidates with an Initial Estimated Post Transplant Survival (EPTS) Score &gt; 90% Were Less Likely to Receive Kidney Transplant Mainly due to Very Low Rate of Living Donor Kidney Transplant

The new kidney allocation system (KAS) and the Estimated Post Transplant Survival (EPTS) score were introduced in the United States. The transplant rate among very high EPTS candidates (> 90%) may be impacted by lack of KAS priority and geographic factors based on the location of the listed Organ Procurement Organization (OPO).

Validation of a survival benefit estimator tool in a cohort of European kidney transplant recipients

Pre-transplant prognostic scores help to optimize donor/recipient allocation and to minimize organ discard rates. Since most of these scores come from the US, direct application in non-US populations is not advisable. The Survival Benefit Estimator (SBE), built upon the Estimated Post-Transplant Survival (EPTS) and the Kidney Donor Profile Index (KDPI), has not been externally validated. We aimed to examine SBE in a cohort of Spanish kidney transplant recipients. We designed a retrospective cohort-based study of deceased-donor kidney transplants carried out in two different Spanish hospitals. Unadjusted and adjusted Cox models were applied for patient survival. Predictive models were compared using Harrell’s C statistics. SBE, EPTS and KDPI were independently associated with patient survival (p ≤ 0.01 in all models). Model discrimination measured with Harrell’s C statistics ranged from 0.57 (KDPI) to 0.69 (SBE) and 0.71 (EPTS). After adjustment, SBE presented similar calibration and discrimination power to that of EPTS. SBE tended to underestimate actual survival, mainly among high EPTS recipients/high KDPI donors. SBE performed acceptably well at discriminating post-transplant survival in a cohort of Spanish deceased-donor kidney transplant recipients, although its use as the main allocation guide, especially for high KDPI donors or high EPTS recipients requires further testing.

Deceased donor kidney allocation: an economic evaluation of contemporary longevity matching practices

BackgroundMatching survival of a donor kidney with that of the recipient (longevity matching), is used in some kidney allocation systems to maximize graft-life years. It is not part of the allocation algorithm for Australia. Given the growing evidence of survival benefit due to longevity matching based allocation algorithms, development of a similar kidney allocation system for Australia is currently underway. The aim of this research is to estimate the impact that changes to costs and health outcomes arising from ‘longevity matching’ on the Australian healthcare system.MethodsA decision analytic model to estimate cost-effectiveness was developed using a Markov process. Four plausible competing allocation options were compared to the current kidney allocation practice. Models were simulated in one-year cycles for a 20-year time horizon, with transitions through distinct health states relevant to the kidney recipient. Willingness to pay was considered as AUD 28000.ResultsBase case analysis indicated that allocating the worst 20% of Kidney Donor Risk Index (KDRI) donor kidneys to the worst 20% of estimated post-transplant survival (EPTS) recipients (option 2) and allocating the oldest 25% of donor kidneys to the oldest 25% of recipients are both cost saving and more effective compared to the current Australian allocation practice.Option 2, returned the lowest costs, greatest health benefits and largest gain to net monetary benefits (NMB). Allocating the best 20% of KDRI donor kidneys to the best 20% of EPTS recipients had the lowest expected incremental NMB.ConclusionOf the four longevity-based kidney allocation practices considered, transplanting the lowest quality kidneys to the worst kidney recipients (option 2), was estimated to return the best value for money for the Australian health system.