Journal of Hepatology
Volume 45, Issue 4 , Pages 488-494, October 2006

Should donors and recipients be matched in liver transplantation?

  • Patrizia Burra

      Affiliations

    • Division of Gastroenterology, Department of Surgical and Gastroenterological Sciences, Padova University Hospital, Padova, Italy
    • Corresponding Author InformationCorresponding author. Tel.: +39 049 8212892; fax: +39 049 8760820.
    • ,
  • Robert J. Porte

      Affiliations

    • Department of Surgery, Section Hepatobiliary Surgery and Liver Transplantation, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands

published online 31 July 2006.

Article Outline

Abbreviations: CTP, Child–Turcotte–Pugh classification, HCC, hepatocellular carcinoma

 

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1. Introduction 

Survival rates after liver transplantation are currently around 85%, 69% and 61% at 1, 5 and 10 years, respectively [1], [2]. Most current organ allocation systems are based on the principle that the sickest patients should be treated first. Models have been developed to estimate the risk of death, considering the underlying disease and urgency of the receiving patient assuming that all donor livers carry the same risk of failure. This, however, is not the case: it has been shown in recent years that the risk of graft failure, and even patient death, after transplantation differs among recipients. While some patients may “tolerate” and overcome the initial poor function of a compromised donor organ, others may not have the same reserve. Increasing awareness of the diversity in donor organ quality has stimulated the debate on matching between specific recipient and donor factors to avoid futility, but also to avoid personal and institutional differences in organ acceptance. Allocation policies must serve the patients most in need as well as achieve the best post-transplant results. This approach is a balance between individual justice (serving individuals in need) and population utility (getting the best results for the entire population at risk).

As will be discussed in this paper, it is time to consider and develop allocation systems that are not only based on the likelihood of dying without a transplant, but also on the likelihood of surviving with a given donor liver.

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2. The current donor liver allocation systems 

To help decide which patient with chronic liver disease should be transplanted first, numerous models have been developed to predict mortality without a transplant, but also survival of patients after liver transplantation based on pretransplantation features of the recipient. A correct evaluation of the severity of liver disease is crucial in order to establish priorities in allocating organs for liver transplantation, making it necessary to develop a disease severity index based on variables that can be generalized, verified and easily obtained.

2.1. Allocation based on the Child–Turcotte–Pugh classification 

The Child–Turcotte–Pugh (CTP) classification is widely used as a means for assessing the severity of a patient’s liver disease. It was originally created to assess the operative risk for patients with end-stage liver disease and variceal bleeding who were undergoing portosystemic shunt surgery [3]. A limitation of the CTP score is that it does not consider renal function, which is an independent predictor of survival in patients with end-stage liver disease [4]. The CTP classification is also limited by its inability to discriminate disease severity among the most severely ill patients: patients with serum bilirubin levels of 3mg/dl and 30mg/dl are awarded the same CTP scors.

The United Network for Organ Sharing (UNOS) classification, in the USA, as well as the allocation system used in the Eurotransplant area, have used the CTP score. Although it has been used extensively, this classification system has serious drawbacks: it considers only three categories of disease severity for patients with end-stage liver disease (i.e. status 3 (CTP score⩾7), status 2B (CTP score⩾10), and status 2A (CTP score⩾10, in intensive care with less than a week to live) [5]. This means that the conditions of patients classified as status 2B, who account for the majority of candidates for liver transplantation, can vary from people living at home and still working full time to people requiring constant hospitalization. On the basis of the UNOS classification as well as the Eurotransplant allocation system, waiting time has been introduced into the scheme. The inclusion of waiting time has been based on the principle that in the case of patients having the same degree of disease severity, those who had waited the longest were given priority. Waiting time, however, became a dominant factor influencing the priorities for assigning an organ, almost completely disregarding the severity of the patient’s liver disease. This has stimulated the search for alternative models.

2.2. Allocation based on the model for end-stage liver disease 

The search for a prognostic scoring system based on objective variables has prompted the proposal of a new model, named the Model for End-Stage Liver Disease (MELD), which considers the patient’s serum bilirubin and creatinine levels, and the international normalized ratio (INR) for prothrombin time [6]. The MELD scoring system was created to estimate the chances of survival for patients with varying degrees of severity and different etiologies of liver disease, that were undergoing a transjugular intrahepatic portosystemic shunt (TIPS) procedure. Its validity has been tested in four independent data sets, including patients hospitalized for hepatic decompensation, ambulatory patients with non-cholestatic cirrhosis, patients with primary biliary cirrhosis, and a historical group of patients with liver cirrhosis followed up from the 1980s. Since its introduction, the MELD score has been widely used as a measure of mortality risk in patients with end-stage liver disease and it has been judged suitable for use as a disease severity index for the purpose of guiding organ allocation priorities [7]. The MELD score has been prospectively applied to estimate mortality at 3 months in 3437 adults who were candidates for liver transplantation, 412 (12%) of whom died during the 3-month follow-up period [8]. Mortality on the waiting list has been shown to increase proportionally to the MELD score at the time of listing [6]. Recently a group from Vienna reported that patients who died on the waiting list for transplantation had significantly higher MELD scores at the time of listing and at the time of removal, and a significantly greater increase in MELD score after listing, compared with the patients who did get transplanted. In multivariable analyses, these authors found that refractory ascites, bacterial peritonitis, and co-morbidity score were independent predictors of death on the waiting list, although MELD at the time of listing had almost twice the hazard of death as the other factors [9]. The magnitude and change in two consecutive MELD scores (delta MELD) – i.e. MELD score on day 0 and 30 – was superior in predicting waiting list mortality than baseline MELD scores [10]. With implementation of a MELD-based liver allocation system in the United States, mortality risk was chosen as the definition of need for liver transplantation for adult patients with chronic and nonmalignant liver diseases [11]. MELD has also been used to predict the mortality risk after liver transplantation. A higher mortality rate has been recorded in recipients with higher MELD scores, and this predictive score was superior than the corresponding UNOS status [12].

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3. Matching donor and recipient 

The most important principle currently used for organ allocation is based on the recipient’s needs and chances of dying on the waiting list. However, not every available donor organ can be used for every patient. Traditionally, donor livers and recipients have been only matched for ABO blood types and body size. The latter criterion, however, has become of relative importance, especially in pediatric transplantation, due to the rapid advancement in liver reduction techniques and split liver transplantation [13]. For example in pediatric transplantation, a donor–recipient weight ratio as high as 12:1 can be acceptable in the situation of a split liver graft of the left lateral segments. Since uniform criteria are lacking most centers would accept around 30% higher or lower donor body weights compared to the recipient in the situation of full size adult liver transplantation. Larger discrepancies may result in a difficult closure of the abdomen or the so called “small for size syndrome”, respectively [14]. While more accurate matching does not occur officially, additional matching criteria may be used, especially in countries where a center-based allocation system still exists. Within the allocation system used in Eurotransplant it is currently possible to define a limited number of donor characteristics which may or may not be acceptable for a given recipient. These donor characteristics include for example hepatitis B core positivity and whether or not a split liver is acceptable.

Apart from official allocation policies, surgeons may still decline a donor liver because of specific characteristics of donor and recipient. Although exact figures are not available, this practice may be more common than currently appreciated, particularly in patient-oriented allocation systems. Organs from donors with hepatitis B (e.g. anti HB-core positive), hepatitis C serology, or advanced age are already used selectively by all transplant centers. For example, a liver from a 83-year old donor can be acceptable for a 60-year old recipient, but most centers would be reluctant to accept such a liver for a child. Also, a liver from an anti-hepatitis C positive donor can be used in a recipient who is transplanted for hepatitis C cirrhosis or in high urgency situations (provided there is normal histology), but would not be acceptable for a stable recipient without hepatitis C [15]. The donor characteristics listed above would not cause much debate. The problem arises with donors with a combination of less obvious and relative risk factors. A liver graft may be withheld from a given recipient in one center, while it would have been accepted for a similar patient in another center. This implies a lack of homogeneity of criteria in organ allocation. At this time no well conducted studies are available on the number and reasons regarding organs declined for specific recipients.

Not only organ allocation but also organ acceptance should be evidence-based and transparent.

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4. The rationale for developing an allocation system based on donor and recipient matching 

The arguments for developing an allocation system based on donor and recipient matching are summarized in Table 1. As outlined above, the current selection/allocation systems are based on the risk of death on the waiting list and do not recognize variations in “donor organ quality” [16]. Efforts to increase the number of organ donations have resulted in a high proportion of “expanded-criteria donors” (see article by Merion in this Forum). There is currently no consensus on the definition of an “expanded criteria donor”, hampering a direct comparison among studies. Although candidates who are most ill may have poorer outcomes with higher risk grafts, the interactions between donor quality and recipient disease severity are still poorly-defined [17]. Interestingly, emerging evidence suggests that an increasing use of compromised organs does not necessarily lead to an overall lower rate of graft and patient survival, as long as donor–recipient combinations are carefully selected [18]. The development of an allocation system in which these combined effects are taken into consideration could improve the overall outcome after transplantation by improving utility, while avoiding futility, and by maintaining equal chances for survival. In other words, when carefully selected, more patients could be transplanted successfully with similar overall survival rates despite the increasing use of compromised donor livers. This, however, would require an allocation system that is not only based on the risk of death on the waiting list for a potential recipient, but also weighs the risk of a given donor graft for a specific recipient.

Table 1. Arguments for a liver allocation system based on donor and recipient matching
(1) Current selection/allocations systems are based on the risk of death on the waiting list and do not recognize distinctions in “donor organ quality”.
(2) Efforts to increase the number of organ donations are likely to result in a relatively high proportion of “expanded-criteria donors”.
(3) Livers from expanded-criteria donors carry a higher risk of graft dysfunction and failure.
(4) Matching donor and recipients may offer the prospect of predicting outcome at the time when a specific donor liver is allocated to a specific recipient.
(5) Differences in local acceptance rates and policies may be diminished.
(6) Overall outcome and utility may improve.

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5. The requirements for an allocation system with donor and recipient matching 

The most relevant requirements for an allocation system based on donor and recipient matching are summarized in Table 2.

Table 2. Requirements for an organ allocation system with donor and recipient matching
(1) Adherence to the sickest-first policy, while limiting the risk of futility.
(2) The lowest acceptable post-transplant survival benefit should be defined and agreed upon (avoidance of futility).
(3) Identification of all donor factors which are associated with worse outcome.
(4) Consensus on the definition of “expanded criteria donors”.
(5) Identification of combinations of donor and recipient profiles which have an impact on outcome.
(6) Variables identified under (3) and (4) should be objective and available at the time of organ offer.
(7) Not only severity of liver disease, but also specific etiologies should be considered.
(8) Development of a new allocation model which includes all the above-mentioned principles and knowledge.
(9) Continuous re-evaluation and validation after the allocation system has come into practice.

5.1. Basic principle: the sickest first while avoiding futility 

First of all, we should adhere to the current policy in which the sickest patients are transplanted first. At the same time, we should limit the risk of futility. There is currently no world-wide consensus on what constitutes futility. In the United Kingdom, a 5 year survival rate of at least 50% should be achieved to justify liver transplantation [19].

5.2. Donor factors associated with bad outcome 

This topic has been covered by B. Merion et al. in the previous article in this Forum. We would like to point out that it is critical to define “outcome”, and we should not only focus on one- or two-year patient survival, but also on graft survival and the need for retransplantation. More importantly, when defining outcome, we should adhere to the principles of intention-to-treat analysis and, therefore, also include mortality on the waiting list. Some variables such as human leukocyte antigen (HLA) matching and gender matching have received particular attention [20], [21], for example in kidney transplantation. Several studies have addressed the potential benefit of HLA matching in liver transplantation [23]. Although the results of older studies have been contradictory, HLA compatibility is now considered to have no clinically relevant effect on outcome after liver transplantation. This has recently been reaffirmed by a careful examination of the Organ Procurement and Transplantation Network (OPTN) database in the United States, with respect to HLA match or mismatch and liver-graft survival [23]. Studies on the impact of gender matching between donor and recipient have not always led to the same conclusions, depending on the chosen outcome parameter [22], [24] (see article by Merion in this Forum).

In contrast to the ideal and low-risk grafts, which form a relatively homogeneous group, marginal (or expanded criteria) grafts are quite heterogeneous, including a broad spectrum of graft failure risks. Donor variables that have previously been identified as risk factors for graft and patient survival include age (>60 years), female donor (especially in male recipients), obesity, elevated liver function tests, hypotension/increased vasopressor use, non-heart-beating donor, partial or split liver grafts, elevated serum sodium levels, and prolonged cold ischemia time (>12h) [1]. While the length of cold and warm ischemia are critical factors determining outcome after transplantation, it should be realized that these factors are not known at the time of organ allocation and are, therefore, of limited relevance when considering an allocation model with donor and recipient matching. The length of warm ischemia at the time of implantation is dependent on surgical and anatomical factors. Only the cold ischemia time could be estimated at the time of organ allocation on the basis of travel distance between the donor and recipient centers. However, many other factors, including logistics (i.e. availability of a surgical team and an operating room) and anatomical factors (i.e. unexpected difficult native hepatectomy) may influence cold ischemia time as well [23], [24].

Although the qualitative effect of individual donor variables are well-documented, the quantitative risk associated with combinations of characteristics are much less clear. In an attempt to develop a quantitative donor risk index, Feng et al. [17] have recently used the Scientific Registry of Transplant Recipients (SRTR) to study data from 20,023 transplants, using livers from diseased donors, performed in the United States between January 1, 1998, and December 31, 2002, into adult recipients (⩾18 years of age) (see previous article by Merion in this Forum). Using Cox regression models, these investigators were able to identify seven donor characteristics that independently predict a significantly increased risk of graft failure. Donor age over 40 years (and particularly over 60 years), non-heart-beating donation, and split/partial grafts were strongly associated with graft failure, while African–American race, less height, cerebrovascular accident and ‘other’ causes of brain death were more modestly but still significantly associated with graft failure. This quantitative assessment of the risk of graft failure using a donor risk index is useful not only to inform the process of organ acceptance, but is also an essential first element in the development of an allocation system that takes both recipient and donor variables into consideration. However, several other donor-related variables than those included in the donor risk score developed by Feng and co-workers may be relevant in this regard, including variables such as length of stay in the ICU and degree of steatosis.

5.2.1. Impact of the combinations of donor and recipient characteristics on outcome? 

While few studies have focused on defining the combinations of donor and recipient profiles, most centers would traditionally not use an expanded criteria donor liver for a high risk candidate. Several studies have shown, for example, that outcome after split liver transplantation is much worse when split grafts are used for very sick patients, whereas good results can be obtained when used in stable recipients [14]. Many recent studies have challenged the conventional wisdom that high risk donor livers should not be used for high risk patients [3]. This debate is supported by the following dilemma: “What is better? Accepting a “marginal” donor liver with an increased risk, or waiting for another “normal” donor liver with the risk of dying on the waiting list [17]. The answer to this question is difficult, but key information could come from either mathematical models or studies using large databases.

5.2.2. Not only severity of liver disease, but also specific etiologies should be considered 

Apart from the severity of sickness, the etiology of liver disease may play a role when matching donors and recipients. For example, there is accumulating evidence that the risk of re-infection and subsequent fibrosis, or even cirrhosis in patients transplanted for hepatitis C virus (HCV)-related cirrhosis, is strongly associated with the degree of initial graft injury [25]. Pre-injured or compromised grafts [26] from expanded criteria donors, such as donors with advanced age, are associated with more aggressive recurrence of HCV-related liver disease and subsequently lower graft survival rates [27]. Therefore, it may be advisable not to use some “expanded criteria donors” for recipients with HCV. However, such a strategy would immediately result in another dilemma with the risk of inequality among recipients, because other recipients with different etiologies of liver disease would also prefer to have a young donor. This exemplifies the complexity of developing an allocation system that considers in detail both recipient and donor profiles. On the other hand, specific compromised donor livers could be well used for a specific group of recipients, whereas one should be very reluctant to offer such a liver to other potential recipients. For example, livers from hepatitis B core-positive or HCV-positive donors can be used under certain conditions to treat patients with end-stage liver disease due to HBV or HCV, respectively, however, giving those livers to other potential recipients with non-viral liver disease will add to the morbidity in these patients.

Another group of liver transplant candidates that may warrant special consideration are recipients with hepatocellular carcinoma (HCC). The urgency for transplantation in these patients is rarely reflected by liver disease severity scores. To give patients with HCC equal opportunity for transplantation, they currently receive additional points in the MELD system [28]. However, a critical issue remains the difficulty to predict the risk of progression and dropout [29]. Interestingly, patients with cryptogenic cirrhosis presenting with obesity have recently been reported to carry a major risk of developing HCC, but this is not considered in any scoring system so far. In this context, a wider discussion should also be dedicated to living donor liver transplantation which permits pre-emptive operation before the development of serious complications associated with cirrhosis and portal hypertension [30].

Another aspect to consider when developing alternative allocation models is the natural history of some types of liver disease, as well as the consequences of concomitant therapies. For example, patients with HBV-related cirrhosis should preferably be transplanted when HBV DNA (by molecular hybridization) is undetectable. In cases found positive for HBV-DNA, adequate treatment, e.g. with lamivudine, is needed. However, long-term treatment with lamivudine carries the potential risk of developing drug resistance, a condition which should be avoided before transplantation, illustrating the dilemma of optimal timing of transplantation in certain patients with specific etiologies of liver disease [31].

5.3. Development of new allocation models based on donor and recipient matching 

Some groups have used mathematical models in an attempt to identify the influence of various combinations of donor and recipient profiles on outcome after liver transplantation [19], [32], [33]. These types of models are based on assumptions and, unfortunately, the results of these analytic models are not always unequivocal. Using a Markovian decision analysis, Amin et al. [33] estimated the 1-year survival rate of candidates who accept a hypothetical expanded criteria donor liver today versus those who refuse the offer and continue to wait for a standard criteria donor. These authors suggest that candidates at a high risk of death on the waiting list (MELD score>30) would be wise to accept an expanded criteria donor liver, even if the probability of primary graft dysfunction is high. Moreover, the authors suggest that patients at a low risk of death on the waiting list (MELD 11–20) should also accept expanded criteria donor livers, unless the risk of primary graft failure is greater than 23% [3]. In another simulation study, Avolio et al. [18] concluded that livers from high-risk donors should be used for low-risk recipients only, whereas high-risk recipients should only be transplanted with low-risk organs. Differences in the mathematical methods and the various assumptions used in the various models explain the different conclusions. This emphasizes the importance of validation of these models using virtual patient data. The best information concerning this subject is expected to come from analyses of large databases. Such analyses should ideally also consider the recently proposed donor risk index, as described by Feng et al. [17] In fact, as pointed out in their article in this Forum, this group is currently extending their work to formally examine the interaction between donor risk index and recipient risk factors.

The value of large patient databases has also been shown by studies based on the European Liver Transplant Registry (ELTR) [1], [2]. The ELTR is a database governed by the European Liver and Intestine Transplant Association (ELITA) and currently contains data of over 60,000 liver transplants performed in Europe. Although voluntary, the accuracy of the database is continuously checked by site audits and it has previously been shown to have a high validity [34]. Recently the ELTR was used to identify the main risk factors for 3-month and 12-month mortality in adults undergoing a first liver transplant and to develop a model to assess the likelihood of early mortality in patients undergoing transplantation [2]. The proposed model includes recipient characteristics as well as potential donor and transplant-related characteristics. The model can also be used by centers to assess their past performance and compare it with the performance of other European centers over a similar period. In this study the following variables were identified as risk factors for mortality: transplantation prior to the period 2000–2003, acute liver failure as indication for transplantation, donor age older than 60 years, compatible or incompatible donor–recipient blood group, older recipient age, split or reduced graft, total ischemia time of longer than 13h, and low United Network for Organ Sharing score. An important point to consider is that a larger size of transplant center (>70 transplants per year) was found to be associated with improved early outcome [2].

In conclusion, the current allocation systems, such as the one based on MELD-score, give the highest priority to the sickest patients on the waiting list. These allocation systems, however, do not integrate the large differences that may exist in the quality of donor organs and the associated risk of graft dysfunction or failure. The extent of ad hoc “extra” donor/recipient matching by individual decisions of surgeons and physicians at the time of a donor liver offer, is unknown, even in patient oriented allocation systems [33]. The lack of evidence-based guidelines for accepting or rejecting the offer of an organ tailored on recipient’s characteristics may further exaggerate geographical differences in the policy of liver transplantation with equal chances for patients on the waiting list. More transparent and objective allocation systems using donor and recipient characteristics must be developed in the future. Such a selection process should, however, still adhere to the basic policy of current allocation systems of treating the sickest patients first. Not only the individual patient may benefit from such an approach, but in fact the overall success rate and benefits of liver transplantation may increase due to enhanced utility and avoidance of futility in the continued presence of organ shortage.

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PII: S0168-8278(06)00401-6

doi:10.1016/j.jhep.2006.07.021

Journal of Hepatology
Volume 45, Issue 4 , Pages 488-494, October 2006

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