The new liver allocation score for transplantation is validated and improved transplant survival benefit in Germany but not in the United Kingdom

External Validation of the United Kingdom Transplant Benefit Score in Australia and New Zealand

Introduction: In Australia and New Zealand, liver allocation is needs based (based on model for end-stage liver disease score). An alternative allocation system is a transplant benefit-based model. Transplant benefit is quantified by complex waitlist and transplant survival prediction models. Research Questions: To validate the UK transplant benefit score in an Australia and New Zealand population. Design: This study analyzed data on listings and transplants for chronic liver disease between 2009 and 2018, using the Australia and New Zealand Liver and Intestinal Transplant Registry. Excluded were variant syndromes, hepatocellular cancer, urgent listings, pediatric, living donor, and multi-organ listings and transplants. UK transplant benefit waitlist and transplant benefit score were calculated for listings and transplants, respectively. Outcomes were time to waitlist death and time to transplant failure. Calibration and discrimination were assessed with Kaplan-Meier analysis and C-statistics. Results: There were differences in the UK and Australia and New Zealand listing, transplant, and donor populations including older recipient age, higher recipient and donor body mass index, and higher incidence of hepatitis C in the Australia and New Zealand population. Waitlist scores were calculated for 2241 patients and transplant scores were calculated for 1755 patients. The waitlist model C-statistic at 5 years was 0.70 and the transplant model C-statistic was 0.56, with poor calibration of both models. Conclusion: The UK transplant benefit score model performed poorly, suggesting that UK benefit-based allocation would not improve overall outcomes in Australia and New Zealand. Generalizability of survival prediction models was limited by differences in transplant populations and practices.

The Toronto Postliver Transplantation Hepatocellular Carcinoma Recurrence Calculator: A Machine Learning Approach

Liver transplantation (LT) listing criteria for hepatocellular carcinoma (HCC) remain controversial. To optimize the utility of limited donor organs, this study aims to leverage machine learning to develop an accurate posttransplantation HCC recurrence prediction calculator. Patients with HCC listed for LT from 2000 to 2016 were identified, with 739 patients who underwent LT used for modeling. Data included serial imaging, alpha-fetoprotein (AFP), locoregional therapies, treatment response, and posttransplantation outcomes. We compared the CoxNet (regularized Cox regression), survival random forest, survival support vector machine, and DeepSurv machine learning algorithms via the mean cross-validated concordance index. We validated the selected CoxNet model by comparing it with other currently available recurrence risk algorithms on a held-out test set (AFP, Model of Recurrence After Liver Transplant [MORAL], and Hazard Associated with liver Transplantation for Hepatocellular Carcinoma [HALT-HCC score]). The developed CoxNet-based recurrence prediction model showed a satisfying overall concordance score of 0.75 (95% confidence interval [CI], 0.64-0.84). In comparison, the recalibrated risk algorithms' concordance scores were as follows: AFP score 0.64 (outperformed by the CoxNet model, 1-sided 95% CI, >0.01; P = 0.04) and MORAL score 0.64 (outperformed by the CoxNet model 1-sided 95% CI, >0.02; P = 0.03). The recalibrated HALT-HCC score performed well with a concordance of 0.72 (95% CI, 0.63-0.81) and was not significantly outperformed (1-sided 95% CI, ≥0.05; P = 0.29). Developing a comprehensive posttransplantation HCC recurrence risk calculator using machine learning is feasible and can yield higher accuracy than other available risk scores. Further research is needed to confirm the utility of machine learning in this setting.

Public preferences for the allocation of donor organs for transplantation: A discrete choice experiment

This study aimed to assess public preferences for the allocation of donor organs in Germany with the focus on ethical principles of distributive justice. We performed a discrete choice experiment (DCE) using a self-completed online questionnaire. Based on a systematic review and focus group discussions, six attributes, each with two-four levels, were selected (corresponding principle of distributive justice in brackets), including (1) life years gained after transplantation (principle of distributive justice: effectiveness/benefit - utilitarianism), (2) quality of life after transplantation (effectiveness/benefit - utilitarianism), (3) chance for a further donor organ offer (principle of distributive justice: medical urgency - favouring the worst-off), (4) age (medical and social risk factors: sociodemographic status), (5) registered donor (principle of distributive justice: value for society), and (6) individual role in causing organ failure (principle of distributive justice: own fault). Each respondent was presented with eight choice sets and asked to choose between two hypothetical patients without an opt-out. Data were analysed using conditional logit, mixed logit and latent class models. The final sample comprised 1028 respondents. Choice decisions were significantly influenced by all attributes except chance for a further donor organ offer. The attributes of good quality of life after transplantation, younger age, and no individual role in causing organ failure had the greatest impact on choice decisions. Life years gained after transplantation and being a registered donor were less important for the public. The latent class model identified four classes with preference heterogeneities. Respondents preferred to allocate deceased donor organs by criteria related to effectiveness/benefit, whereas medical urgency was of minor importance. Therefore, a public propensity for a rational, utilitarian, ethical model of allocation could be identified. Public preferences can help to inform policy to warrant socially responsible allocation systems and thus improve organ donation rates.

Organ allocation in the age of the algorithm: avoiding futile transplantation - utility in allocation

PURPOSE OF REVIEW

This review describes and questions the evolution of allocation systems from local team decisions in the 20th century to patient-oriented allocation using complex algorithm predicting transplant benefit.

RECENT FINDINGS

The opening years of the 2000s have seen the implementation of prioritization scores aiming at increasing transparency and reducing waitlist mortality. The 2010s have underlined the necessity of drawing the upper limits of how sick a patient can be while still ensuring acceptable survival. More complex algorithms evaluating transplant benefit have been implemented in allocation systems to take this issue into account.

SUMMARY

Allocation algorithms are becoming more and more complex, integrating numerous parameters from both donor and recipient to achieve optimal matching. The limitations of implementing these complex algorithms are represented by the evermoving waiting list demography, geographic disparities between recipients and donors, team policy adaptation to rule changes, and implicit biases within the transplant community. Survival as the only metric by which to define benefit may be seen as restrictive; quality of life may be a fruitful measure for better defining benefit in organ transplantation in the future.

Chemotherapy and Hepatic Steatosis: Impact on Postoperative Morbidity and Survival after Liver Resection for Colorectal Liver Metastases

Background

Hepatic steatosis and chemotherapy in the treatment of colorectal liver metastases (CLM) are often linked to increased mortality and morbidity after liver resection. This study evaluates the influence of macrovesicular hepatic steatosis and chemotherapeutic regimes on graded morbidity and mortality after liver resection for CLM.

Methods

A total of 323 cases of liver resection for CLM were retrospectively analysed using univariable and multivariable linear, ordinal and Cox regression analyses. The resected liver tissue was re-evaluated by a single observer to determine the grade and type of hepatic steatosis.

Results

Macrovesicular steatosis did not influence postoperative morbidity and survival, as evidenced by risk-adjusted multivariable Cox regression analysis (p = 0.521). Conversion chemotherapy containing oxaliplatin was an independent and significant risk factor for mortality in risk-adjusted multivariable Cox regression analysis (p = 0.005). Identified independently, significant risk factors for postoperative morbidity were neoadjuvant treatment of metastases of the primary tumour with irinotecan (p = 0.003), the duration of surgery in minutes (p = 0.001) and the number of intraoperatively transfused packed red blood cells (p ≤ 0.001). Surprisingly, macrovesicular hepatic steatosis was not a risk factor for postoperative morbidity and was even associated with lower rates of complications (p = 0.006).

Conclusion

The results emphasize the multifactorial influence of preoperative liver damage and chemotherapy on the severity of postoperative morbidity, as well as the significant impact of conversion chemotherapy containing oxaliplatin on survival.

Organ utilization - the next hurdle in transplantation?

Nonutilization of organs from consented deceased donors remains a significant factor in limiting patient access to transplantation. Critical to reducing waste is a clear understanding of why organs are not used: accurate metrics are essential to identify the extent and causes of waste but use of these measures as targets or comparators between units/jurisdictions must be done with caution as focus on any one measure may result in unintended adverse consequences. Comparison between centres or countries may be misleading because of variation in definitions, patient or graft characteristics. Two of the most challenging areas to improve appropriate deceased donor organ utilization are appetite for risk and lack of validated tools to help identify an organ that will function appropriately. Currently, the implanting surgeon is widely considered to be accountable for the use of a donated organ so guidelines must be clear to allow and support sensible decisions and recognition that graft failure or inadvertent disease transmission are not necessarily attributable to poor decision-making. Accepting an organ involves balancing risk and benefit for the potential recipient. Novel technologies such as machine perfusion may allow for more robust guidance as to the functioning of the organ.

Public preferences for the allocation of donor organs for transplantation: Focus group discussions

BACKGROUND

Deceased donor organs are scarce resources because of a large supply-and-demand mismatch. This scarcity leads to an ethical dilemma, forcing priority-setting of how these organs should be allocated and whom to leave behind.

OBJECTIVE

To explore public preferences for the allocation of donor organs in regard to ethical aspects of distributive justice.

METHODS

Focus groups were facilitated between November and December 2018 at Hannover Medical School. Participants were recruited locally. Transcripts were assessed with content analysis using the deductive framework method. All identified and discussed criteria were grouped according to the principles of distributive justice and reported following the COREQ statement.

RESULTS

Six focus groups with 31 participants were conducted. Overall, no group made a final decision of how to allocate donor organ; however, we observed that not only a single criterion/principle but rather a combination of criteria/principles is relevant. Therefore, the public wants to allocate organs to save as many lives as possible by both maximizing success for and also giving priority to urgent patients considering the best compatibility. Age, waiting time, reciprocity and healthy lifestyles should be used as additional criteria, while sex, financial status and family responsibility should not, based on aspects of equality.

CONCLUSIONS

All participants recognized the dilemma that prioritizing one patient might cause another one to die. They discussed mainly the unclear trade-offs between effectiveness/benefit and medical urgency and did not establish an agreement about their importance. The results suggest a need of preference studies to elucidate public preferences in organ allocation.

[Donor liver histology : Joint recommendations of the DGP, DTG and DSO]

BACKGROUND

The indications, implementation and reporting of liver biopsies for deceased organ donation are not mandatory or regulated. Reliable data on outcome quality and prognostic relevance are therefore not available. Defined standards are thus required to enable meaningful studies and to ensure high data quality of a national transplantation registry.

OBJECTIVE

Presentation of a synopsis of available studies and literature-based recommendations.

RESULTS AND CONCLUSION

Against the background of an organ shortage and a growing number of older donors, pretransplantation liver histology is of significant relevance to guide clinical decision making. With the joint recommendations of the German Transplantation Society (DTG), the German Society of Pathology (DGP) and the German Organ Transplantation Foundation (DSO) standardized procedures are defined for the first time.

Impact of the new MELD-based allocation system on waiting list and post-transplant survival - a cohort analysis using the French national CRISTAL database

Concerns related to equity and efficacy of our previous center-based allocation system have led us to introduce a patient-based allocation system called the "Liver Score" that incorporates the MELD score. The main objective of this study was to compare waitlist and post-transplant survivals before and after implementation of the "Liver Score" using the French transplant registry (period before: 2004-2006 and period after: 2007-2012). Patients transplanted during the second period were sicker and had a higher MELD. One-year waitlist survival (74% versus 76%; p=0.8) and one-year post-transplant survival (86.3% vs 85.7%; p=0.5) were similar between the 2 periods. Cirrhotic recipients with MELD>35 had lower one-year post-transplant survival compared to those with MELD<35 (74.8% vs 86.3%; p<0.01), mainly explained by their higher intubation and renal failure rates. The MELD showed a poor discriminative capacity. In cirrhotic recipients with MELD>35, patients presenting 2 or 3 risk factors (dialysis, intubation or infection) had a lower 1-year survival compared to those with none of these risk factors (61.2% vs 92%; p<0.01). The implementation of the MELD-based allocation system has led to transplant sicker patients with no impact on waitlist and post-transplant survivals. Nevertheless, selection of patients with MELD>35 should be completed to allow safe transplantation. This article is protected by copyright. All rights reserved.

Potential savings in the treatment pathway of liver transplantation: an inter-sectorial analysis of cost-rising factors

INTRODUCTION

Identification of cost-driving factors in patients undergoing liver transplantation is essential to target reallocation of resources and potential savings.

AIM

The aim of this study is to identify main cost-driving factors in liver transplantation from the perspective of the Statutory Health Insurance.

METHODS

Variables were analyzed with multivariable logistic regression to determine their influence on high cost cases (fourth quartile) in the outpatient, inpatient and rehabilitative healthcare sectors as well as for medications.

RESULTS

Significant cost-driving factors for the inpatient sector of care were a high labMELD-score (OR 1.042), subsequent re-transplantations (OR 7.159) and patient mortality (OR 3.555). Expenditures for rehabilitative care were significantly higher in patients with a lower adjusted Charlson comorbidity index (OR 0.601). The indication of viral cirrhosis and hepatocellular carcinoma resulted in significantly higher costs for medications (OR 21.618 and 7.429). For all sectors of care and medications each waiting day had a significant impact on high treatment costs (OR 1.001). Overall, cost-driving factors resulted in higher median treatment costs of 211,435 €.

CONCLUSIONS

Treatment costs in liver transplantation were significantly influenced by identified factors. Long pre-transplant waiting times that increase overall treatment costs need to be alleviated by a substantial increase in donor organs to enable transplantation with lower labMELD-scores. Disease management programs, the implementation of a case management for vulnerable patients, medication plans and patient tracking in a transplant registry may enable cost savings, e.g., by the avoidance of otherwise necessary re-transplants or incorrect medication.

Distinct risk factors for early and late blood transfusion following pancreaticoduodenectomy

BACKGROUND

The International Study Group of Pancreatic Surgery (ISGPS) has defined two periods of postpancreatectomy hemorrhage, early (<24 h) and late (>24 h). A previously published Blood Usage Risk Score (BURS) aimed to predict early and late blood transfusion. The primary aim of this study was to define risk factors for early and late blood transfusion after pancreaticoduodenectomy. Secondary aims were to assess the predictive accuracy of the BURS.

METHODS

In this retrospective observational study, multivariable analyses were used to identify independent risk factors for both early and late blood transfusion. The predictive ability of the BURS was then assessed using a receiver operating characteristic (ROC) curve analysis.

RESULTS

Among 628 patients, 99 (15.8%) and 144 (22.9%) received early and late blood transfusion, respectively. Risk factors for blood transfusion differed between early and late periods. Preoperative anemia and venous resection were associated with early blood transfusion whilst Whipple's resection (as opposed to pylorus preserving pancreaticoduodenectomy), lack of biliary stent and a narrow pancreatic duct were predictors of late blood transfusion. The BURS was significantly predictive of early blood transfusion, albeit with a modest degree of accuracy (AUROC: 0.700, P < 0.001), but not of late blood transfusion (AUROC: 0.525, P = 0.360). Late blood transfusion was independently associated with increasing severity of postoperative pancreatic fistula (POPF) (OR: 1.85, 3.18 and 9.97 for biochemical, types B and C POPF, respectively, relative to no POPF).

CONCLUSIONS

Two largely different sets of variables are related to early and late blood transfusion following pancreaticoduodenectomy. The BURS was significantly associated with early, albeit with modest predictive accuracy, but not late blood transfusion. An understanding of POPF risk allows assessment of the need for late blood transfusion.

Identifying independent risk factors for graft loss after primary liver transplantation

PURPOSE

The aim of the study is the identification of independent risk factors for re-transplantation after primary liver transplantation beyond the occurrence of hepatic artery thrombosis.

METHODS

Eight hundred thirty-four adult patients undergoing primary liver transplantation were analyzed. A propensity score was developed using multivariable binary logistic regression with hepatic artery thrombosis as the dependent variable. The logit link function of the propensity score was included into multivariable Cox regression analysis for graft survival to adjust the study population.

RESULTS

Graft loss was observed in 134 patients (16.1%). Independent significant risk factors for graft loss were recipient platelet count (p = 0.040; HR: 1.002; 95%-CI: 1.000-1.003), preoperative portal vein thrombosis (p = 0.032; HR: 1.797; 95%-CI: 1.054-2.925), donor age (p < 0.001; HR: 1.026; 95%-CI: 1.012-1.040), percentage of macrovesicular steatosis of the graft (p = 0.011; HR: 1.037; 95%-CI: 1.009-1.061), early complications leading to revision surgery (p < 0.001; HR: 2.734; 95%-CI: 1.897-3.956), duration of the transplant procedure (p < 0.001; HR: 1.005; 95%-CI: 1.003-1.007) as well as transplantation of a split liver graft (p = 0.003; HR: 2.637; 95%-CI: 1.420-4.728). The logit of the propensity score did not reach statistical significance in the final multivariable Cox regression model (p = 0.111) indicating good adjustment for the occurrence of hepatic artery thrombosis.

CONCLUSION

Liver transplant programs might benefit from regular donor organ biopsies to assess the amount of macrovesicular steatosis. An elevated recipient platelet count can promote reperfusion injury leading to graft loss. A liver graft from an elderly donor should not be split or be transplanted in a recipient with detected portal vein thrombosis.