Optimizing the Use of Geriatric Livers for Transplantation in the Eurotransplant Region.

Acceptance criteria for liver allografts are ever more expanding because of a persisting wait-list mortality. Older livers are therefore offered and used more frequently for transplantation. This study aims to analyze the use and longterm outcome of these transplantations. Data were included on 17,811 first liver transplantations (LTs) and information on livers that were reported for allocation but not transplanted from 2000 to 2015 in the Eurotransplant (ET) region. Graft survival was defined as the period between transplantation and date of retransplantation or date of recipient death. In the study period, 2394 (13%) transplantations were performed with livers ≥70 years old. Graft survival was 74%, 57%, and 41% at 1-, 5-, and 10-year follow-up, respectively. A history of diabetes mellitus in the donor (hazard ratio [HR], 1.3; P = 0.01) and positive hepatitis C virus antibody in the recipient (HR, 1.5; P < 0.001) are specific risk factors for transplantations with livers ≥70 years old. Although donor age is associated with a linearly increasing risk of graft loss between 25 and 80 years old, no difference in graft survival could be observed when "preferred" recipients were transplanted with a liver <70 or ≥70 years old (HR 1.1; CI 0.92-1.23, P = 0.40) or with a donor <40 or ≥70 years old (HR 1.2; CI 0.96-1.37, P = 0.13). Utilization of reported livers ≥70 years old increased from 42% in 2000-2003 to 76% in 2013-2015 without a decrease in graft survival (P = 0.45). In conclusion, an important proportion of LTs in the ET region are performed with livers ≥70 years old. The risk of donor age on graft loss increases linearly between 25 and 80 years old. Livers ≥70 years old can, however, be transplanted safely in preferred patients and are to be used more frequently to further reduce wait-list mortality.

The center effect in liver transplantation in the Eurotransplant region: a retrospective database analysis.

Apart from donor and recipient risk factors, the effect of center-related factors has significant impact on graft survival after liver transplantation (LT). To investigate this effect in Eurotransplant, a retrospective database analysis was performed, including all LT's in adult recipients (≥18 years) in the Eurotransplant region from 1.1.2007 until 31.12.2013. Additionally, a survey was sent out to all transplant centers requesting information on surgeons' experience and exposure. In total, 10 265 LT's were included (median follow-up 3.3 years), performed in 39 transplant centers. Funnel plots showed significant differences in graft survival between the transplant centers. After correction for donor and recipient risk, with the Eurotransplant donor risk index (ET-DRI) and the simplified recipient risk index (sRRI) and random effects, these differences diminished. Mean historical volume (in the preceding 5 years) was a significant (P < 0.001), nonlinear marker for graft survival in the multivariate analysis. This study demonstrates that funnel plots can be used for benchmarking purposes in LT. Case-mix correction can be performed with the use of the ET-DRI and sRRI. The center effect encompasses the entire complex process of preoperative workup, operation to follow-up.

Abdominal organ procurement in the Netherlands - an analysis of quality and clinical impact.

Between March 2012 and August 2013, 591 quality forms were filled out for abdominal organs in the Netherlands. In 133 cases (23%), there was a discrepancy between the evaluation from the procuring and transplanting surgeons. Injuries were seen in 148 (25%) organs of which 12 (2%) led to discarding of the organ: one of 133 (0.8%) livers, five of 38 (13%) pancreata and six of 420 (1.4%) kidneys (P < 0.001). Higher donor BMI was a risk factor for procurement-related injury in all organs (OR: 1.06, P = 0.011) and donor after cardiac death (DCD) donation in liver procurement (OR: 2.31, P = 0.034). DCD donation is also associated with more pancreata being discarded due to injury (OR: 10.333, P = 0.046). A higher procurement volume in a centre was associated with less injury in pancreata (OR = -0.95, P = 0.013) and kidneys (OR = -0.91, P = 0.012). The quality form system efficiently monitors the quality of organ procurement. Although there is a relatively high rate of organ injury, the discard rate is low and it does not significantly affect 1-year graft survival for any organ. We identified higher BMI as a risk factor for injury in abdominal organs and DCD as a risk factor in livers. A higher procurement volume is associated with fewer injuries.

Development of the Eurotransplant Discard Risk Index to Predict Acceptance of Livers for Transplantation: A Retrospective Database Analysis.

OBJECTIVES: The utilization of liver allografts could be optimized if nonacceptance is predicted. This study aimed to evaluate the prognostic ability of an updated Discard Risk Index in Eurotransplant. MATERIALS AND METHODS: Potential deceased donors from January 2010 to December 2015 who had been reported to Eurotransplant were included in our analyses. Liver utilization was defined by transplant status as the primary outcome to evaluate the performance of the Eurotransplant-developed Discard Risk Index. RESULTS: Of 11670 potential livers, 9565 (81%) were actually transplanted. Donor sex, age, history of diabetes, drug abuse, use of vasopressors, body mass index category, serum sodium, cause of death, donor type, and levels of C-reactive protein, bilirubin, aspartate and alanine aminotransferases, international normalized ratio, and gamma-glutamyltranspeptidase were associated with discard and combined in the Eurotransplant-developed Discard Risk Index. Correlation between the two Discard Risk Indexes was high (r = 0.86), and both achieved high C statistics of 0.72 and 0.75 (P < .001), respectively. Despite strong calibration, discard rates of 0.8% for overall donors and 6% of donors after circulatory death could be predicted with 80% accuracy. CONCLUSIONS: The Eurotransplant-developed Discard Risk Index showed a high prognostic ability to predict liver utilization in a European setting. The model could therefore be valuable for identifying livers at high risk of not being transplanted in an early stage. These organs might profit the most from modified allocation strategies or advanced preservation techniques.

Predictive Capacity of Risk Models in Liver Transplantation.

BACKGROUND: Several risk models to predict outcome after liver transplantation (LT) have been developed in the last decade. This study compares the predictive performance of 7 risk models. METHODS: Data on 62 294 deceased donor LTs performed in recipients ≥18 years old between January 2005 and December 2015 in the United Network for Organ Sharing region were used for this study. The balance of risk, donor risk index (DRI), Eurotransplant-DRI, donor-to-recipient model (DRM), simplified recipient risk index, Survival Outcomes Following Liver Transplantation (SOFT), and donor Model for End-stage Liver Disease scores were calculated, and calibration and discrimination were evaluated for patient, overall graft, and death-censored graft survival. Calibration was evaluated by outcome of high-risk transplantations (>80th percentile of the respective risk score) and discrimination by concordance index (c-index). RESULTS: Patient survival at 3 months was best predicted by the SOFT (c-index: 0.68) and Balance of Risk score (c-index: 0.64), while the DRM and SOFT score had the highest predictive capacity at 60 months (c-index: 0.59). Overall, graft survival was best predicted by the SOFT score at 3-month follow-up (c-index: 0.65) and by the SOFT and DRM at 60-month follow-up (c-index: 0.58). Death-censored graft survival at 60-month follow-up is best predicted by the DRI (c-index: 0.59) and Eurotransplant-DRI (c-index: 0.58). For patient and overall graft survival, high-risk transplantations were best defined by the DRM. For death-censored graft survival, this was best defined by the DRI. CONCLUSIONS: This study shows that models dominated by recipient factors have the best performance for short-term patient survival. Models that also include sufficient donor factors have better performance for long-term graft survival. Death-censored graft survival is best predicted by models that predominantly included donor factors.

Outcome of Liver Transplant Patients With High Urgent Priority: Are We Doing the Right Thing?

BACKGROUND: About 15% of liver transplantations (LTs) in Eurotransplant are currently performed in patients with a high-urgency (HU) status. Patients who have acute liver failure (ALF) or require an acute retransplantation can apply for this status. This study aims to evaluate the efficacy of this prioritization. METHODS: Patients who were listed for LT with HU status from January 1, 2007, up to December 31, 2015, were included. Waiting list and posttransplantation outcomes were evaluated and compared with a reference group of patients with laboratory Model for End-Stage Liver Disease (MELD) score (labMELD) scores ≥40 (MELD 40+). RESULTS: In the study period, 2299 HU patients were listed for LT. Ten days after listing, 72% of all HU patients were transplanted and 14% of patients deceased. Patients with HU status for primary ALF showed better patient survival at 3 years (69%) when compared with patients in the MELD 40+ group (57%). HU patients with labMELD ≥45 and patients with HU status for acute retransplantation and labMELD ≥35 have significantly inferior survival at 3-year follow-up of 46% and 42%, respectively. CONCLUSIONS: Current prioritization for patients with ALF is highly effective in preventing mortality on the waiting list. Although patients with HU status for ALF have good outcomes, survival is significantly inferior for patients with a high MELD score or for retransplantations. With the current scarcity of livers in mind, we should discuss whether potential recipients for a second or even third retransplantation should still receive absolute priority, with HU status, over other recipients with an expected, substantially better prognosis after transplantation.

The Effect of Histidine-tryptophan-ketoglutarate Solution and University of Wisconsin Solution: An Analysis of the Eurotransplant Registry.

BACKGROUND: Both University of Wisconsin (UW) and histidine-tryptophan-ketoglutarate (HTK) solutions are currently used in the Eurotransplant region for preservation of liver allografts. Previous studies on their effect have led to a lot of discussion. This study aims to compare the effect of HTK and UW on graft survival. METHODS: First liver transplantations in recipients 18 years or older from January 1, 2007, until December 31, 2016, were included. Graft survival was compared for livers preserved with HTK and UW at 30 days, 1, 3, and 5 years. Multivariable analysis of risk factors was performed and outcome was adjusted for important confounders. RESULTS: Of all 10 628 first liver transplantations, 8176 (77%) and 2452 (23%) were performed with livers preserved with HTK and UW, respectively. Kaplan-Meier curves showed significant differences in graft survival between HTK and UW at 30 days (89% vs 93%, P=<0.001), 1 year (75% vs 82%, P=<0.001), 3 years (67% vs 72%, P<0.001), and at 5 years (60% vs 67%, P<0.001). No significant differences in outcome were observed in separate analyses of Germany or non-German countries. In multivariable analysis, UW was associated with a decreased risk of graft loss at 30 days (HR 0.772, P=0.002) and at 1 year (0.847 (0.757-0.947). When adjusted for risk factors, no differences in long term outcome could be detected. CONCLUSIONS: Because the use of preservation fluids is clustered geographically, differences in outcome by preservation fluids are strongly affected by regional differences in donor and recipient characteristics. When adjusted for risk factors, no differences in graft survival exist between transplantations performed with livers preserved with either HTK or UW.

Identification and Validation of the Predictive Capacity of Risk Factors and Models in Liver Transplantation Over Time.

BACKGROUND: Outcome after liver transplantation (LT) is determined by donor, transplant and recipient risk factors. These factors may have different impact on either patient or graft survival (outcome type). In the literature, there is wide variation in the use of outcome types and points in time (short term or long term). Objective of this study is to analyze the predictive capacity of risk factors and risk models in LT and how they vary over time and per outcome type. METHODS: All LTs performed in the Netherlands from January 1, 2002, to December 31, 2011, were analyzed with multivariate analyses at 3-month, 1-year, and 5-year for patient and (non-)death-censored graft survival. The predictive capacity of the investigated risk models was compared with concordance indices. RESULTS: Recipient age, model for end-stage liver disease sodium, ventilatory support, diabetes mellitus, hepatocellular carcinoma, previous malignancy, hepatitis C virus antibody, hepatitis B virus antibody, perfusion fluid, and Eurotransplant donor risk index (ET-DRI) had significant impact on outcome (graft or patient survival) at 1 or multiple points in time. Significant factors at 3-month patient survival (recipient age, model for end-stage liver disease sodium, ventilatory support) were used to compose a concept model. This model, had a higher c-index than the balance-of-risk score, DRI, ET-DRI, donor-recipient model and simplified recipient risk index for long-term patient and non-death-censored graft survival. CONCLUSIONS: In this study, the effects of recipient risk factors and models on different outcome types and time points were shown. Short-term patient survival mainly depends on recipient risk factors, long-term graft survival on donor risk factors and is more difficult to predict. Next to the concept model, the donor-recipient model has a higher predictive capacity to other risk models for (long-term) patient and non-death-censored graft survival. The DRI and ET-DRI best predicted death-censored graft survival. Knowledge about risk factors and models is critical when using these for waitlist management and/or help in organ allocation and decision-making.