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INDEX
ABSTRACT ... v
1. INTRODUCTION ... 1
1.1 General ... 1
1.1.1 The possible policies for organ allocation ... 3
1.1.2 Strategies and techniques to expand the donor organ pool ... 8
1.1.3 Sources of organ. ... 8
1.1.4 Types of OLT ... 8
1.2 Selection of recipients and organ allocation ... 9
1.2.1 The US model for liver allocation ... 9
1.2.2 The European model for liver allocation ... 10
1.3 Scoring systems ... 11
1.3.1 The Child-Turcotte-Pugh (CTP) score ... 11
1.3.2 CTP limitations ... 12
1.3.3 MELD score: “sickest first policy” ... 13
1.3.4 MELD calculation: ... 14
1.3.5 Upgrading of MELD score for Hepatocellular Carcinoma (HCC) ... 15
1.3.6 MELD limitations ... 15
1.3.7 Classification of Candidates for Liver Transplants According to Old UNOS 18 1.3.8 Other Scoring Systems ... 18
1.4 Indications and Contraindications for Liver Transplantation ... 22
1.4.1 Indication of liver transplantation in adults ... 23
1.4.2 Indications in children ... 24
1.4.3 Variant syndromes requiring liver transplantation ... 24
1.4.4 Transplantation For Acute Liver Failure (ALF) ... 24
1.4.5 Criteria for liver transplantation in acute liver failure (ALF) ... 26
1.4.6 Transplantation For Alcoholic Liver Disease (ALD) ... 27
1.4.7 Transplantation for Chronic Liver Disease ... 27
1.4.8 Transplantation For Hepatic Malignancy ... 29
1.4.9 Transplantation For Metabolic Liver Disease ... 32
1.4.10 Transplantation For Vascular Disorders ... 32
1.4.12 Contraindications to Liver Transplantation ... 33
1.4.13 Retransplantation ... 35
1.4.14 Delisting Criteria ... 36
1.4.15 Living Donor Liver Transplantation ... 36
1.4.16 Contraindications for LDLT ... 38
1.5 Patient Evaluation ... 38
1.5.1. Evaluation Aim And Purpose ... 38
1.5.2 Timing of referral for liver transplantation evaluation ... 40
1.5.3 The Process of Liver Transplant Evaluation ... 41
1.5.4 Evaluation of potential donors for living donor liver transplantation ... 45
1.5.5 Listing for transplantation and organ allocation ... 45
1.5.6 Medical issues to be considered during evaluation ... 45
1.5.7 Specific Consideration For Liver Transplantation ... 49
1.6 Management While Waiting for Transplantation ... 58
1.6.1 Lab values Recertification schedule of Meld data ... 59
1.6.2 Disease-Specific Considerations ... 59
1.7 The Donor ... 73
1.7.1 Brain Death ... 73
1.7.2 Strategies and techniques to expand the donor organ pool include ... 76
1.7.3 Donor age ... 80
1.7.4 Influence Of Hepatic steatosis ... 84
1.7.5 Non–heart-beating donor (NHBD) livers ... 90
1.7.6 Orthotopic Liver Transplantation with partial allografts ... 97
1.7.7 Other risk factors ... 101
1.7.8 Donor-transmitted diseases ... 104
1.8 Living donor liver transplantation ... 108
1.9 Immunology ... 116
1.9.1 Hyperacute rejection ... 121
1.9.2 Acute rejection ... 121
1.9.3 Chronic rejection ... 123
1.9.4 Immunosuppressive therapy general considerations ... 124
1.10 Post-liver transplantation complications ... 128
1.10.1 The main complications in the immediate postoperative period ... 132
1.10.3 Graft Monitoring and Post Transplant Pathology ... 161
1.10.4 Early New Onset Diseases/Injuries in the Liver Allograft ... 165
1.10.5 Later new-onset disease/injuries in the liver allograft ... 199
1.11 Cell Therapy ... 211
1.11.1 Hepatocytes ... 212
1.11.2 Embryonic stem cells ... 215
1.11.3 Mesenchymal stromal cells ... 217
1.11.4 Amnion epithelial (AE) cell transplantation ... 219
1.11.5 Induced Pluripotent Cells ( iPSC) ... 221
1.12 Biomarkers of liver fibrosis ... 223
1.13 γ-Glutamyltransferase ... 231
1.13.1 Generalities and tissue distribution ... 231
1.13.2 Physiological functions of γ-glutamyltransferase ... 233
1.13.3 Serum GGT: origin and chemical and physical characteristics ... 240
1.13.4 Predictive value of serum GGT in hepatobiliary diseases ... 242
1.13.5 Serum γ-glutamyltransferase: cardio - vascular diseases ... 244
1.13.6 Fractional GGT analysis ... 250
1.13.7 GGT fractions in the Framingham Heart Study ... 251
2. AIM ... 255
3. MATERIALS AND METHODS ... 257
3.1 Patient selection ... 257
3.2 Laboratory analysis ... 258
3.3 Total and fractional GGT determination ... 258
3.4 Statistical analysis ... 260
3.5 Patient selection for immunohistochemical analysis ... 261
3.6 Tissue Microarray Technique (TMA) ... 261
3.7 Immunohistochemical analysis ... 261
3.8 Collection of samples of primary human bile and analysis of the fractions ... 262
3.9 Half-life activity of bile GGT ... 262
3.10 Activation of papain ... 262
4. RESULTS AND DISCUSSION ... 265
4.1 Accuracy of bGGT fraction for the diagnosis of NAFLD ... 265
4.2 Cirrhotic patient evaluation – pretransplant ... 271
4.3 Characterization of GGT fractions in primary human bile ... 289
4.4 Fractional GGT evaluation after liver transplant ... 297
5. CONCLUSION ... 315
ABSTRACT
The aim of this study is test the diagnostic power of GGT fraction for hepatic diseases in comparison with that of total GGT and its usefulness in the setting of liver transplantation. Cirrhosis and chronic liver failure, and HCC are leading causes of morbidity and mortality worldwide. The diagnosis of cirrhosis and the determination of the etiology remain complex, in fact, no serologic test or radiological study can accurately diagnose cirrhosis. Besides, assays in most standard liver panels do not reflect the function of the liver correctly. With appropriately selected patients, liver transplantation is a definitive curative therapy for long-term survival and good quality of life for patients with end stage liver disease facing death. Accurate diagnosis and prognosis are essential for patients management pre and post-transplant, and for patients prioritization for organ allocation for liver transplantation. This requires the choice of biomarkers that provide adequate diagnostic information, at the minimum cost to more accurately select candidates for liver transplantation, to monitor post-transplant outcome and provide an optimal treatment regimen.
Serum gamma-glutamyltransferase (GGT) activity is a sensitive marker of liver dysfunction, but its specificity is modest, in fact, its value increases in all liver dysfunctions. GGT has been already included in diagnostic algorithm (i.e.: the Fatty Liver Index, FLI), its specificity was high if considered with other markers, but low if considered alone. The currently used laboratory GGT assays do not allow discriminating among the different causes of GGT increase, thus reducing the clinical value and specificity of this otherwise sensitive disease biomarker. A new method based on molecular-size exclusion chromatography, followed by a GGT-specific post-column reaction, allowed to identify and quantify, in healthy subjects, 4 plasma GGT fractions with high sensitivity, specificity and reproducibility. These fractions, named big-GGT (b-big-GGT), medium-big-GGT (m-big-GGT), small-big-GGT (s-big-GGT), and free-big-GGT (f-big-GGT) showed different molecular weight (MW), i.e. 2000, 1000, 250 and 70 kDa, respectively. It has been previously shown that in healthy subjects f-GGT is the most abundant fraction, while b-GGT showed the highest degree of correlation with established cardiovascular risk factors. Interestingly b-GGT has been found in atherosclerotic plaques together with products deriving from the pro-oxidant reactions catalysed by the enzyme, The liver is one of the main organs that generates free radicals, one of the mechanisms of hepatocyte injury in response to diverse insults occurring in different pathological conditions. For example, oxidative stress has been demonstrated to be
implicated as a cause of hepatic fibrosis. Besides, liver damage is characterized by increased iron storage which elicits a free-radical mediated peroxidation.
In the period between February 2008 and April 2011, 264 patients during evaluation for liver transplant [215 men; median (25th – 75th percentile); age 54.5 (50-60 years)] were enrolled at the Department of Surgery, Liver Transplantation Unit of the University Hospital of Pisa. At the visit, attendees underwent anamnestic-physical examination and blood sampling for the laboratory assessment of liver function. In this cohort: 39 patients were diagnosed with metabolic cirrhosis (MC), 96 with viral cirrhosis (VC) 129 with viral cirrhosis and hepatocellular carcinoma (HCC). As control 200 blood donors were selected and studied for the determination of fractional GGT reference values. Blood samples were also collected from 14 LT recipients preoperatively before native liver hepatectomy (T0), and for 10 consecutive days post-transplant. Bile samples were collected intra-operatively during duct anastomosis (T0) and 10 days following the surgical procedure of transplantation through Kehr-tube. Standard assay of all blood tests were simultaneously performed according to the standard clinical laboratory procedures by automated analysers at the Clinical Laboratories of the University Hospital of Pisa.
Analysis of total and fractional GGT was performed using an FPLC (fast protein liquid chromatography) system. Separation of fractional GGT was obtained by gel filtration chromatography and the enzymatic activity was quantified by post-column injection of the fluorescent substrate for GGT. The area under chromatogram peak is proportional to fractional GGT activity. Total area and fractional GGT area was calculated by a MatLab program. Localization of GGT protein in liver biopsies was performed by automated indirect immunohistochemical analysis, using a polyclonal antibody directed against the C-terminal 20 amino acids of GGT heavy chain. Histological sections were analysed using the image software MetaAnalisys.
Different GGT fraction patterns were observed in cirrhotic patients and within the three sub cohorts (VC, MC, HC). s-GGT showed a broader and double profile not seen in controls, defined as s1-GGT and s2-GGT. The b/s ratio was lower in patients than controls. The diagnostic value of the b/s ratio was independent of the absolute values of total GGT and from the aetiology of the cirrhosis and the presence of liver cancer. Variations of the GGT fractions reflect different aspects of the liver cirrhosis: b-GGT
behaves as a positive index of liver function, and reflects the progression of portal hypertension and splenomegaly; s2-GGT fraction reflects hepatocellular damage.
GGT activity in human bile is higher than that found in plasma, showing only two peaks corresponding to plasma b-GGT and f-GGT fractions, while m- and s-GGT fractions were not detectable. Regarding the nature and characteristics of biliary complex corresponding to the plasma b-GGT, the part of b-GGT fraction insensitive to the direct action of papain can be released into the bile associated with membrane vesicles such as exosomes. Immunolocalization of GGT in patients and control biopsy demonstrated different abundance and tissue distribution all over the section and quantification of GGT in liver tissue suggest that there is not a direct relationship between tissue and circulating GGT enzyme levels.
The post-operative course of the selected 14 patients was uneventful and there were no events of acute rejection. Soon after transplantation (24h), a sharp decline in total plasma GGT is observed and reflected on all fractions, in particular b-GGT. In 5-6 days after there has been a gradual increase in total plasma GGT. Plasma f-GGT fraction shows minor alterations, while other fractions have a similar trend as total GGT. In bile sample T0 GGT is present mainly as b-GGT and in less extent as f-GGT. The first 24 h post-transplant bile b-GGT activity is decreased followed by a sudden increase in its activity with a peak observed in the fourth day while bile f-GGT fraction shows minimal changes. An increase of bile GGT activity and an apparent peak of f-GGT preceded by an abrupt drop in b-GGT activity a day before is observed at days 6 and 10 in two patients: and a reversal of the proportions between the bile b-and f-GGT fractions in favour of b-GGT fraction has been observed in one of these patient at day 10 (T10) and in another patient on days 7 (T7) and 8 (T8). All fractions behave as positive index of cholestasis and liver function. Interestingly all fractions showed a positive correlation with direct bilirubin apart from s1-GGT, which showed a strict negative correlation. Unexpectedly, all fractions were negative associated with LDH, and b-GGT and m-GGT showed a negative correlation also with transaminases AST and ALT. Thus plasma GGT fractions, in particular b-GGT and m-GGT, were primarily related to ischemic-type biliary lesions following liver transplantation.
1) patients with NAFLD and CHC display different GGT fraction patterns, despite similar total GGT activity values.
2) Collected data showed that the b/s ratio, independently of the absolute values of total GGT and its fractions, displays a high sensitivity and specificity for liver cirrhosis, and the values of the b/s ratio were lower than controls independently of the cause of the cirrhosis (viral or cryptogenetic) or the presence of associated liver cancer. This suggests that the b/s ratio is a specific biomarker of architectural and functional damage of the liver.
3) the elution profile of bile GGT activity showed the presence of only two forms corresponding to plasma fractions b-GGT and f-GGT, respectively. Similar to that found in plasma GGT fractions, the biliary f-GGT fraction consists of soluble protein and b-GGT fraction of exosomes. But, unlike plasma b-b-GGT, biliary b-b-GGT fraction is in part sensitive ti papain action; likely, the portion of biliary b-GGT sensitive to the proteolytic action might be consistuted of bile acids micelles.
4) Plasma b-GGT and m-GGT levels, in the first 10 days after liver transplant, were primarily related to ischemic-type biliary lesions following liver transplantation
The precise nature of GGT fractions has not yet been established, and at present it is not possible to speculate on the possible reasons conducting to different GGT fraction patterns in NAFLD and CHC and cirrhosis. Data collected suggest that GGT fraction pattern specificity might depend on its ability to reflect the different extents of inflammatory, structural and functional derangement in liver disease.
Further study on the nature and biological significance of plasma GGT fractions in health and disease might allow to improve the use of this sensitive but otherwise poorly specific biomarker in the numerous contexts in which it is employed, including multimarker algorithms comprising plasma GGT for the assessment of liver steatosis and fibrosis. Extensive investigation on the diagnostic value of GGT fractions might provide a novel diagnostic tool for liver diseases; understanding the nature, properties, and pathophysiological variations of GGT fraction pattern might allow a better understanding of the pathogenesis of the diseases associated with increased GGT.
1. INTRODUCTION
1.1 General
Liver transplantation is not a palliative but a definitive, curative therapy for a wide range of diseases. The aim is not only to prolong survival but also to improve the quality of life of recipients. The procedure has undergone major improvements. Continuous advances in surgical techniques, improvement of intra-operative management, better management of complications, immunosuppressions, and better organ preservation together with better selection of candidates for transplantation and allocation of donor organs according to more objective criteria have led to a great success to the procedure. It is now a routine, safe, standardized procedure performed in many transplant centers with a substantially improved graft and patient survival and accepted morbidity rates. Currently, survival rates of over 90-95% and 70% at one year and five years post-transplantation, respectively are expected (Roberts MS, et al. 2004; Lucey MR, et al. 1997; Belle SH, et al. 1997; Demetris r AJ, et al. 2009), three-year patient and graft survival rates in liver transplant recipients are currently 79% and 74%, respectively (Freeman RB, et al. 2008) and 1-year graft survival rates now exceed 80% (Waki K 2008) with good quality of life. This great success has resulted in one hand first, broadening of the indications to include previously contraindicated conditions, second, provided innovations to the field of complex hepatobiliary surgery, laparoscopic liver procedures, trauma surgery, surgical intensive care, and surgical education. In the other hand, it is challenged by many obstacles that need to be surpassed and problems to be resolved. The most important being the shortage of donors in face of great number of patients awaiting for transplantation and prolonged waiting list time, the need of timely availability of suitable livers, and the need for an expanded number of useable donor organs make from liver allocation a true challenge. In addition, the need for improved therapies to treat recurrent hepatitis C after transplantation, and the need for improved detection, and risk stratification to combat hepatocellular carcinoma. Liver grafts for transplantation can be obtained either from deceased donors (DDs) or living donors (LDs). Living donor liver transplantation (LDLT) was introduced to overcome the increasing demand for donor organs and to tight the widening gap between the resource (deceased donor) and demand (recipient) and is the main procedure in countries where there was virtually no deceased donor programme due to particular reasons. In deceased donor liver transplantation (DDLT) programme, prioritization of
patients for organ allocation is crucial. Living donor liver transplantation (LDLT) programe is different where the prospective donor is usually a close relation. In both situations, a measure such as a scoring system is important in prognosticating the outcome following transplantation. There has to be equilibrium between the patient’s medical reserves to endure or withstand the complex major surgical procedure of liver transplantation and its probable outcome. A patient is considered too healthy to undergo LT if the expected survival is greater without LT. Therefore, criteria are needed in order to select patients who can most benefit from transplantation. Prioritization for liver transplantation (LT) has evolved over the past 20 years (Adam R, et al. 2009). The objective of the allocation system is to minimize the total number of deaths to the patient population. Allocation policies must serve the patients most in need and achieve the best post-transplant results (Patrizia Burra, et al. 2006). In the context of deceased donor livers; medical urgency, utility and transplant benefit are the three frequently discussed organ allocation schemes (Merion RM, et al. 2005, Schaubel DE, et al. 2009). In the urgency policy (sickest first), patients with worse outcomes on the waiting list are given higher priority for transplantation. DDLT organ allocation was initially based on whether the patient is at home, in hospital or in an intensive care unit, and the time length on the waiting list (United Network for Organ Sharing-UNOS status), then based on their United Network of Organ Sharing (UNOS) status (2A, 2B and 3) based on their Child Turcotte Pugh (CTP) classification system and its variations to stratify patients with chronic liver disease to predict the mortality and morbidity. Since 2002, the Organ Procurement and Transplantation Network, along with the United Network of Organ Sharing (UNOS), developed a new system based on the model for end-stage liver disease (MELD for adults and PELD for paediatric recipients) adopting the sickest first policy for organ allocation (Freeman RB, et al. 2008, Durand F, 2008) to prioritize patients on the waiting list. These are mathematical regression models which objectively assess the need for liver transplantation and more accurately predict the short-term mortality while on the transplantation waiting list (Merion RM, et al. 2005, Kamath PS, et al. 2001, Longheval G, et al. 2003). In the Eurotransplant countries, the Child-Pugh Turcotte score was replaced by the MELD score in December 2006. In UK the UK organ allocation defines donor pools based on patient-specific characteristics, but organ allocation to individual patients remains at the center’s discretion. United Kingdom model for End-stage Liver Disease (UKELD) score has been adopted for many years
and published (Neuberger J, et al. 2008). MELD and UKELD scores poorly predict outcomes after liver transplantation due to the absence of donor factors.
1.1.1 The Possible Policies For Organ Allocation a) Medical urgency models
1. Child- Turcotte- Pugh score 2. MELD score
3. Modifications of MELD score 4. UKMELD
b) Utility-based score 1. Donor risk index(DRI) 2. D-MELD
3. Model based on ELTR c) Transplant Benefit models
Child-Turcotte-Pugh (CTP) Scoring System to Assess Severity of Liver Disease
Points 1 2 3
Encephalopathy grade None 1 and 2 3 and 4
Ascites Absent Slight Moderate
Bilirubin(mg/dl) 1-2 2-3 >3
For primary biliary cirrhosis Bil.(mg/dl) 1-4 4-10 >10
Albumin (g/dl) 3.5 2.8-3.5 >2.8
Prothrombine Time ( seconds prolonged) 1-4 4-6 >6
Or, INR >1.7 1.7-2.3 >2.3
According to grading of Trey, Burns, and Saunders.21 Trey C, Burns DG, Saunders SJ. Treatment of hepatic coma by exchangeblood transfusion. New Engl J Med 1966; 274:473-481.
MELD score according to the UNOS database:
MELD score (UNOS current version) =
9.57 × ln(creatinine) (mg/dl) + 3.78 × ln(Tot.Bil.) (mg/dl) + 11.20 × ln(INR) + 6.43.
- Any value < 1 is considered equal to 1
- If the patient has been dialyzed twice within the last 7 day => serum creatinine = 4.0 mg/dL - Creatinine >4 was automatically calculated as 4
- Patients with a diagnosis of HCC will be assigned a MELD score based on how advanced the cancer is
United Kingdom Model for End-stage Liver Disease (UKELD).
UKELD = 5 x{1.5 x ln(INR) + 0.3 x ln(Creat) + 0.6 x ln(Br) x13 x ln (Na) + 70}. Where
INR = international normalized ratio Creat = serum creatinine (lmol/l) Br = serum bilirubin (lmol/l) Na = serum sodium (mmol/l)
Donors meeting specific criteria offering the liver for splitting is obligatory, the left lateral segment going to a child at one of three national paediatric centers and the remaining right liver to the retrieving center.
Splitting criteria.
Donor livers should be split if not required for super urgent transplantation or multivisceral grafting and the following criteria are met:
1. Donor age <40 2. Weight >50 kg
3. ICU stay less than 5 days
The decision to split is based solely on these criteria and if a segmental graft is required for a child in any paediatric center the splitting process should be initiated independent of any decision on allocation of the right liver to an adult patient.
The utility-based systems are based on post-transplant outcome taking into account donor and recipient characteristics. The transplant benefit models rank patients according to the net survival benefit that would derive from transplantation. These models would be based on the maximization of the lifetime gained through liver transplantation. Regarding survival benefit, there are several methods to characterize the survival benefit associated with liver transplantation. One method calculates the covariate-adjusted ratio of post- to pre-transplant mortality rates, and is the direct output of a standard Cox regression model. Using such a model and with a maximum of 1 year of post-transplant follow-up, transplant recipients with a MELD score ≥17 derived significant survival benefit, including patients at the maximum MELD score of 40 (Merion RM, et al. 2005). In contrast, patients at low MELD scores had lower mortality risk on the waiting list and hence did not derive a survival benefit from liver transplantation. No current model has all the best characteristics. The lab MELD score is a numerical scale using the three laboratory parameters and ranging from 6 (less ill) to 40 (severely ill). In a large study (Merion RM, et al. 2005) investigating the survival benefit of LT candidates, those transplanted with a MELD score <15 had a significantly higher mortality risk as compared to those remaining on the waiting list, while candidates with a MELD score of 18 or higher had a significant transplant benefit. However, the MELD score does not accurately predict mortality in approximately 15-20% of patients. Therefore, MELD-based allocation allows exceptions for patients whose score may not reflect the severity of their liver disease. These exceptions include hepatocellular carcinoma (HCC), non-metastatic hepatoblastoma, adult polycystic liver
degeneration, primary hyperoxaluria type 1, small for size syndrome, cystic fibrosis, familial amyloid polyneuropathy, hepatopulmonary syndrome, portopulmonary hypertension, urea cycle disorders, hereditary hemorrhagic telangiectasia (Osler-Weber-Rendu disease), hemangioendothelioma of the liver, biliary sepsis, primary sclerosing cholangitis (PSC) and cholangiocarcinoma. Patients with standard exceptions will be assigned a higher MELD score (match MELD) than patient’s laboratory test results (lab MELD), consequently, resulting in an increasing number of patients transplanted for HCC and other exceptions over time (Massie 2011). MELD has proved to be accurate as a predictor of waiting list mortality, but has shown to be less accurate to predict post-transplant outcome. For instance, MELD allocation resulted in decreased waiting list mortality; whereas post-transplant morbidity has increased due to transplantation of a higher proportion of sicker recipients with MELD scores >30 (Dutkowski 2011). Moreover, since the introduction of MELD, the quality of donor organs has been impaired and the threshold for organ allocation has increased from a match MELD of 25 to 34 (Schlitt 2011). A potential modification of the MELD allocation system currently under investigation is to allocate organs by not only taking into account pretransplant mortality but also donor-related factors for estimation of the donor risk index (DRI) (Feng 2006) and post-transplant mortality. Furthermore, standardization of laboratory assays and variants of MELD including incorporation of parameters such as sodium or cholinesterase have been proposed to overcome the limitations of the current scoring system (Choi 2009; Weissmüller 2008). Additional parameters also include serum ferritin (SF) (Walker NM, et al. 2010). Na, Fe are easily determined and available in routine clinical chemistry laboratories. They can also indicate patient morbidity, which may influence prognosis and outcome following LT. This has been described for impaired renal function (as a part of MELD parameters), serum sodium (Londono MC, et al. 2006), as well as for elevated SF and prognosis in hemodialysis patients, (Hasuike Y, et al. 2010; Jenq CC, et al. 2009; Kalantar-Zadeh K, et al. 2001), hematological diseases (Lim ZY, et al. 2010; Mahindra A, et al. 2009), and iron overload prior to LT(Tung BY, et al. 1999). Several studies have analyzed data to define prognostic models associated with outcome following LT, which include only pre-LT recipient factors (age, serum creatinine, cholinesterase; SALT [survival after LT] score) (Weismuller TJ, et al. 2008), or recipient, donor, and surgery-related data (survival outcomes following LT [SOFT] score) (Rana A, et al. 2008). SALT reached a c-statistic of 0.79 (MELD ¼ 0.57; 6-month post-LT survival) in an LT cohort with a mean MELD of
14.5. This score identified a high-risk group and a low-risk group with a specificity of 87.3% and a sensitivity of 68.75% (Weismuller TJ, et al. 2008). SOFT, developed in a large cohort with a mean MELD of 20.6, showed superior outcome prediction than MELD (c-statistic for SOFT ¼ 0.7; for MELD ¼ 0.63; 3-month post-LT survival) with the main variables being previous LT and pre-LT life support (Rana A, et al. 2008). In 2010, SF was reported as a prognostic parameter in patients on the waiting list (Walker NM, et al. 2010). Well-designed prospective studies and simulation models are necessary to establish the optimal allocation system in liver transplantation, as no current model has all the best characteristics.
Preallocation score to predict survival outcomes following liver transplantation (P-SOFT)
Risk factor points
Age >60 4
BMI>35 2
One previous transplant 9
Two previous transplants 14
Previous abdominal surgery 2
Albumin < 2.0 g/dL 2
Dialysis prior to transplantation 3
Intensive care unit pretransplant 6
Admitted to hospital pretransplant 3
MELD score >30 4
Life support pretransplant 9
Encephalopathy 2
Portal vein thrombosis 5
Ascites pretransplant 3
Score to predict survival outcomes following liver transplantation (SOFT)
risk points
P-SOFT score Total
Portal bleed 48 h pretransplant 6
Donor age 10–20 years -2
Donor age > 60 years 3
Donor cause of death from cerebral vascular accident 2
Donor creatinine > 1.5 mg/dL 2
National allocation 2
Cold ischemia time 0–6 h -3
Low risk 0-5 points, low moderate 6-15 points, high moderate 16-35 points, high 36-40 points, futile >40 points.
SALT score
was calculated as ‘SALT = 0.04 age (years) + 0.003 CREA (lmol/l) ) 0.349*CHE (kU/l)’ ‘SALT = 0.04*age (years) + 0.003*CREA (µmol/l) − 0.349*CHE (kU/l).
Calculation: Donor risk index
Donor risk index = exp[(0.154 if 40≤ age <50) + (0.274 if 50≤ age <60) + (0.424 if 60≤ age <70) + (0.501 if 70 ≤ age) + (0.079 if COD = anoxia) + (0.145 if COD = CVA) + (0.184 if COD = other) + (0.176 if race = African American) + (0.126 if race = other) + (0.411 if DCD)+(0.422 if partial/split)+(0.066 ((170–height)/10))+(0.105 if regional share)+(0.244 if national share)+(0.010×cold time)].
In order to expand the donor pool, strategies and techniques have been adopted as well as legislative measures, mass media campaigns, and optimization of available organ allocation. Extended criteria donors ECD or marginal donors are accepted to overcome the organ shortage. The hypothesis supporting EDC utilization is that the benefit of earlier access to transplantation afforded by an EDC allograft outweighs the combined risk associated with the specific allograft and the risk of additional waiting for LTX. The definition of ECD are somewhat center-based but in general term they are defined as those with greater risk of initial poor function IPF or graft failure, and the presence of a disease within the donor that may be transmitted to the recipient and therefore associated with an increase risk for recipient morbidity and mortality (Busuttil RW, et al. 2003). Currently, some marginal donors are being routinely used: elderly donors, steatotic grafts, non-heart beating donors (livers from donation after cardiac death DCD), hepatitis C virus-positive (HCV+) or hepatitis B core antibody-positive. Although these organs may not be optimal, they represent an alternative to decrease waiting list mortality. Other alternatives include living-donor liver transplantation, reuse of grafts as domino transplantation, ex situ and in situ (Rogiers X, et al. 1996) split liver transplantation, reduced-size liver transplantation. Other potential alternatives to liver transplantation including bioartificial liver for acute liver failure patients awaiting for transplantation, cell-based therapies (Ctx) using cell sources from humans or animals are under investigations in an attempt to decrease waiting list mortality due to scarcity of donors. Ctx has shown a great deal of promise, and the progress made over the past several decades of preclinical and clinical studies provides a growing amount of rationale for its use to treat a variety of liver disorders. The most promising cells types are hepatocytes, embryonic stem cells (ESC), mesenchymal stromal cells (MSC),
amnion epithelial (AE) cells, and induced pluripotent stem cells (iPSC). Each cell type has its own associated risks and benefits. Improvement of cell engraftment remains the single biggest challenge to overcome. New methods to modulate the immune reaction and relieve changes in vascular pressures after cell transplant are currently being investigated to enhance engraftment and improve patient outcome. Preconditioning protocols of the recipient liver, such as hepatic irradiation, portal vein embolization, and surgical resection, may also help to improve engraftment by giving donor cells selected growth advantage (Soltys et al. 2010; Puppi et al. 2011). Future work is required to enhance utility of this novel branch of regenerative medicine. Xenotransplantation is investigated as well but no clinical relevant system of xenotransplantation exist.
1.1.2 Strategies And Techniques To Expand The Donor Organ Pool Use of donor livers with extended criteria
Use of steatotic donor organs
HCV-positive donor organs for HCV-positive recipients Use of high-risk CDC donor organs
Donation after cardiac death Split liver transplantation
Living donor liver transplantation Domino liver transplantation
1.1.3 Sources of Organ
Excluding xeno-transplantation, The majority of livers are procured from cadaveric donors they can be: Brain-dead donors, Non-heart-beating donors, and living donors.
1.1.4 Types of OLT Conventional LTx, Living-donor LTx,
Reuse of grafts as domino transplantation, Ex situ as well as in situ split LTx,
Reduced-size LTx.
Most liver transplants are performed using a whole liver from a deceased donor. Types of liver transplantation include Orthotopic liver transplantation: where donor liver is placed in the orthotopic position, Split liver transplantation donor organs can be divided and the separate parts transplanted into two recipients (Keeffe EB. 2001). A portion of the left lobe of an adult donor organ can be transplanted into a child and the remaining
portion used to transplant the liver into an adult. (Otte JB, et al. 1998; Malago M, et al. 2002; Gridelli B, et al. 2003; Renz JF, et al. 2003). In living donor transplantation where only a portion of the donor liver is removed for transplantation; a portion of the left lobe, is a well-established procedure for children (Otte JB, et al. 1998; Malago M, et al. 2002) while for adults, the donor right lobe is transplanted but donor safety remains an ongoing concern. (Trotter JF, et al. 2002; Surman OS, et al. 2002). Under ideal circumstances, a deceased donor organ also can be split and transplanted into two adult recipients (Renz JF, et al. 2004). Perioperative complications are higher but long-term patient survival are comparable with that of deceased orthotopic liver transplantation (Renz JF, et al. 2004; Settmacher U, et al. 2004) Liver transplantation is a complex, time-consuming operation that requires vascular reconstruction of the hepatic artery, the portal vein, and the hepatic venous drainage to the inferior vena cava. Biliary reconstruction usually is accomplished using an end-to-end anastomosis of the proximal donor bile duct to the distal recipient duct; however, in recipients with diseased ducts, the donor duct is usually anastomosed to the jejunum using a Roux-en-Y loop. A number of complications can be anticipated after liver transplantation, including perioperative and surgical complications, immunologic and infectious disorders, and a variety of medical complications.
1.2 Selection of recipients and organ allocation.
Selection of recipients and organ allocation vary in different countries.
1.2.1 The US model for liver allocation
The model of organ allocation in the USA was set to be patient-based due to heterogeneity among more than 118 centers, in the size of the waiting list and organ availability, as well as large distances. For more than 20 years the Organ Procurement and Transplantation Network of the United States (OPTN) suggested to use Child– Turcotte–Pugh (CTP) score (Brown Jr RS, et al. 2002) ABO blood type and time on the waiting list the concept of “first come, first served” in managing the waiting list to establish the priority of organ allocation. In 2000 the Model for End Stage Liver Disease (MELD) was developed. Further studies established that model for end-stage liver disease (MELD) scoring system was superior to the CTP score in predicting the 3-month survival of cirrhotic patients a waiting for liver transplantation. (Wiesner RH, et al. 2003). Since 2002 MELD was implemented in the USA, and subsequently many other
countries, modifying the liver allocation system and started to use the MELD score to list candidates for liver transplantation (Kamath PS, et al. 2001). The corresponding scoring system in children is called PELD.
1.2.2 The European model for liver allocation
There are no uniform rules or systems for organ allocation in Europe or within European Union. The organ exchange organizations for different geographical areas include Eurotransplant (ET; Germany, The Netherlands, Belgium, Luxembourg, Austria, Slovenia, and Croatia), United Kingdom Transplant, Organizacion Nacional de Transplantes in Spain, Scandiatransplant (Sweden, Finland, Norway, Denmark, and Iceland), North Italian transplant, and Etablissement francais des Greffes in France. The organs are allocated and transplanted within each organization, and in collaboration among these organizations. The organ allocation within Eurotransplant is patient-based as in the USA but, in Spain, Scandiatransplant, and UK, is center-directed. Italy has no single unique allocation policy but MELD is currently used in many Transplant Centres. Greece and Scandinavian countries have no formal agreement on listing criteria and allocation is left to the discretion of clinicians (Neuberger J, et al. 2008). Recently, the United Kingdom and France started to manage patients waiting for LT with a new scoring system. The British model Liver allocation in the UK was initially based on each center being allocated a portion of the nation’s donor pool reflecting its previous transplant activity and its nationally contracted (and funded) activity with the National Specialist Commissioning Advisory Group (NSCAG). Units were required to target recipients with an expected post transplant survival of more than 50% at 5 years (Neuberger J, et al. 1999). Predictably, waiting times and waiting list mortality varied widely. Therefore agreed national minimal listing criteria (Neuberger J, et al. 2008) were introduced with a minimum disease severity based on the United Kingdom Model for End-stage Liver Disease (UKELD) Additionally for donors meeting specific criteria offering the liver for splitting is obligatory, the left lateral segment going to a child at one of three national paediatric centers and the remaining right liver to the retrieving center. Thus UK organ allocation defines donor pools based on patient-specific characteristics, but organ allocation to individual patients remains at the center’s discretion In UK they use UKMELD, in France, L’ “Agence de la Biomedicine” utilizes an allocation system (liver score) based on specific variables for each liver disease, which has not yet been validated (Jacquelinet C, et al. 2008). In ET, allocation is directed by different national
laws. The Eurotransplant Liver Allocation System (ELAS) from 2000 to the end of 2006, the selection of potential recipients was based on the medical urgency, donor weight, ABO blood group, waiting time, and donor region. The selected potential recipients were ranked using a scoring system, and the higher the scores the priority to receive the organ. Some urgency categories within ET were given based on the respective medical urgencies and not scoring system. Due to increasing waiting list mortality under ELAS and because of the positive experience with the implementation of MELD/PELD scores in 2002 in the USA, the board of ET decided to acquire the MELD score system for listing and prioritizing the potential recipients as of December 16th 2006 (Eurotransplant International Foundation 2008). In Italy, where there is no formal priority score for patients in the waiting list (Burra P, et al. 2000) precedence for LT was assigned conventionally according to UNOS statuses in view of the fact that the specifications for MELD usage were established by UNOS Policy 3.6, released on February 2002 (United Network for Organ Sharing. Allocation of Livers Proposed Amended UNOS Policy 3.6. 2002. Available at http://www.unos.org). In Italy, in the second half of 2002, the MELD model came into use because of a growing number of Italian transplantation centers side by side with UNOS statuses only. For this reason, the MELD score was not included in the parameters meanwhile adopted by the Italian Ministry of Health (IMH) to evaluate retrospectively the quality of the national liver transplantation activity referred to the previous two-year period (Liver Transplant Activities. Available at: http://www.ministerosalute.it/trapianti [accessed February], 2003).
1.3 Scoring Systems
1.3.1 The Child-Turcotte-Pugh (CTP) Score
The Child and Turcotte classification (1964) and the Pugh’s modification (1973) (Child-Turcotte-Pugh [CTP] score) (Pugh R, et al. 1973) were originally deviced for the assessment of the severity of liver disease in predicting the outcome of patients with cirrhosis in whom surgical therapy for portal hypertension was planned. It was then extended for endoscopic treatment of varices or transjugular intrahepatic portosystemic shunt therapy (TIPS), for prognosis in general, and more recently to stratify patients on the waiting list for LT. (Christensen E, et al. 2004; Cholongitas E, et al. 2005). CTP provides accurate prognostic information of various cirrhosis-related complications (Merkel C, et al. 2000; Shetty Ket, et al. 1997) and is very usefull as a prognostic tool to assess the mortality risk of patients with end-stage liver disease (Huo TI, et al. 2004).
Until 2002, the CTP score and the time on the waiting list, although never formally validated, was used to stratify the risk of death of patients awaiting LT in most Liver Transplant Centres worldwide (Rudow DL, et al. 2008).
1.3.2 CTP Limitations
The use of CTP, particularly for prioritizing potential liver transplant recipients, has several limitations and drawbacks (Rudow DL, et al. 2008; Durand F, et al. 2005). The variables, ascites and encephalopathy, are subjective and assessed by physical examination alone; and when other methods are used (ultrasonography, psychometric testing, EEG), a different degree of severity is diagnosed. Ascites and encephalopathy are influenced by therapy such as diuretics, albumin, and lactulose. Measurement of prothrombin time in different laboratories is variable and depends on the sensitivity of the thromboplastin reagent used (Robert A, et al. 1996). Serum bilirubin of 3 or 13 mg/dL or prothrombin time increased by 6 or 16 seconds will not alter CTP score (Kamath PS, et al. 2001). In addition, the “ceiling” and “floor” effect in terms of the limits set to the laboratory parameters of bilirubin, albumin, and prothrombin time in the grades A, B, and C and changes of serum bilirubin concentrations with therapy (e.g., with ursodeoxycholic acid) do not allow assessment using a continuous scale of severity. The absence of an assessment of renal function, which is a well-established prognostic marker in cirrhosis (Durand F, et al. 2005) is another limitation of the CTP score. The Child-Turcotte-Pugh (CTP) places the patient in a class A (good, 4% 3-month mortality), B (intermediate, 14% 3-3-month mortality), or C (poor, 51% 3-3-month mortality). For patients on the waiting list for LT, CTP score is within a narrow range of 7-15 (Child B or C), and some patients may have identical CTP score; in such case, the waiting time on the waiting list is then taken as a tie-breaker, which is unreliable (Freeman RB Jr, et al. 2000). Up to 1996, allocation of organ for deceased donor liver transplant (DDLT), was based on CTP score, time on the waiting list and whether the patient is at home, in hospital or intensive care unit (ICU). However, the minimal criteria for registering in the waiting list and for admission in an ICU, are not well defined and hence these parameters – longest on the waiting list or in an ICU, are not useful. Furthermore, these parameters do not accurately identify, the sickest patient on the waiting list for LT (Freeman RB Jr, et al. 2000).
1.3.3 MELD SCORE: “sickest first policy”
In 1999, the controversial state of the United Network for Organ Sharing waiting list for liver transplantation and the resulting pressure to formulate a more objective and temporally discriminatory assessment tool led to the development of the Model for End-Stage Liver Disease (MELD) score. This tool was developed by physicians at the Mayo Clinic and was validated for predicting survival in 3 months in cirrhotic patients, initially for 231 patients undergoing Transjugular Intrahepatic Portosystemic Shunt (TIPS) (Malinchoc M, et al. 2000), a short-term bridge therapy to liver transplantation and later for those on the waiting list for LT (United Network for Organ Sharing (UNOS: Feb. 27, 2002) (Kamath PS, et al. 2001). MELD is calculated from a validated predictive equation based on the patient’s serum bilirubin (mg/dL), serum creatinine (mg/dL), International Normalised Ratio (INR) for prothrombin time and also included the aetiology of liver disease: (zero for cholestatic or alcoholic, one score for other aetiology) (Kamath PS, et al. 2001, Wiesner RH, et al. 2001). In 2000, the aetiology of liver failure was dropped from the MELD score because it proved prognostically insignificant (Pagliaro L, et al. 2002), but the coefficient of this variable 6,4 remained in the formula. Many clinical studies have compared CTP and MELD in various populations either undergoing TIPS, orthotopic liver transplantation, or no surgery at all (del Olmo JA, et al. 2003; Jakab F, et al. 1993; Malinchoc M, et al. 2000) These studies have shown MELD to be at least comparable and perhaps slightly better at predicting short-term mortality. The differences between CTP and MELD are that MELD includes renal functions. Liver and renal function are strictly dependent on each other in advanced cirrhosis, and the severity of the liver disease correlates directly with the severity of the renal disease and renal function influence as well the course of liver disease (Huo TI, et al. 2004; Kamath S, et al. 2007). MELD score utilizes only laboratory values, making it a continuous score, more objective, and possessing a wide range of scores which is more accurate in discriminating among patients in similar clinical conditions (Kamath S, et al. 2007) making the listing process more precise and without biases related to subjective or personal opinions. MELD is superior to CTP in predicting short and mid-term survival among cirrhotic patients (Botta F, et al. 2003), and has been shown to predict the 3-month survival more accurately than CTP for both UNOS status 2A (e.g. CTP score ≥10 plus cirrhosis-related complications such as active variceal haemorrhage, hepato-renal syndrome, refractory ascites/hepatic hydrothorax, or stage 3 or 4 hepatic encephalopathy) and status 2B (e.g. CTP score ≥10, or score ≥7 plus complications)
(Wiesner RH, et al. 2003). Nevertheless, a recent review showed that of 11 studies, only four (4512 patients) demonstrated a statistical superiority of the MELD in comparison with the CTP system, whereas seven studies (8020 patients) showed no statistical difference. However, no studies reported the MELD to be statistically inferior to the CTP system (Wiesner RH, et al. 2003). Since February 2002, most Liver Transplant Centres in the USA have adopted the MELD score to allocate livers to the sickest recipients rather than to those who had been on the waiting list for a longer time (Rudow DL, et al. 2008). The MELD score is currently used in many countries. To classify patients awaiting LT according to the severity of their liver disease, with the exception of fulminant MELD seems to be more reliable in predicting survival in patients with higher scores (Huo TI, et al. 2005) and data analysis has shown that MELD is effective in reducing waiting list mortality (Wiesner RH, et al. 2001; Freeman RB, et al. 2004) without changing patient and graft survival. MELD score, almost always gave a c-statistic for 3-month survival > 0.80 in all groups of patients with cirrhosis, without any significant improvement by adding complications such as ascites, encephalopathy, variceal bleeding, and spontaneous bacterial peritonitis. c- statistic >0.80 implies excellent diagnostic accuracy, but still means that there will not be an accurate prediction in approximately 20% of occasions (Kamath PS, et al. 2001)
1.3.4 MELD Calculation MELD is calculated from:
3.8x ln(bilirubin mg/dL) + 11.2x ln(INR) + 9.6x ln(creatinine mg/dL) + 6.4
(creatinine value is assumed 4 for patients on dialysis if dialyzed within last week twice; values<1 are considered 1)
MELD MORTALITY % in next three month
40 or more 71.3%
30-39 52.6%
20-29 19.6%
10-19 6%
<9 1.9%
If the MELD score is >25, 19-24, 11-18, ≤ 10, it is recalculated every 7 days, 1, 3, 12 months respectively. As shown in the table above, in cirrhotic liver patients MELD score is more accurate than CTP score, (MELD score >40: 71% mortality, <10: 2%), in predicting mortality in next 3 months (Wiesner RH et al 2001).
1.3.5 Upgrading of MELD score for Hepatocellular Carcinoma (HCC)
Most USA and European LT Centres currently use additional points for HCC patients that are set according to tumour size. This policy has significantly reduced the number of drop-outs among HCC patients awaiting LT and today more than the 25% of donated livers are used for these candidates (Ioannou G, et al. 2008). Patients with HCC who fulfill the Milan criteria (1 nodule <= 5 cm in diameter, or <=3 nodules and <= 3 cm in diameter) are indicated for liver transplantation (Mazzaferro V, et al. 1996) Patients with HCC are likely to develop intrahepatic and/ or extrahepatic complications and hence were allotted additional fixed points (approved by regional review board: RRB) as follows: (Wiesner RH, 2001, Sharma P, et al. 2004) patients with a single lesion <2 cm: 20 points, patients with a single lesion 2-5 cm or ≤ 3 lesions which are not greater than 3 cm: 24 points, and for every 3 months on the waiting list : 10% additional; now these additional fixed points have been reduced to 22 points for stage 2 (T2), and no priority score to stage 1 score (Wiesner RH, et al. 2004). Following the upgrading of MELD score for HCC patients, the number of DDLT performed for HCC have increased and their waiting list period significantly reduced (2.3 to 0.7 years) (Sharma P, et al. 2004). Eighty-seven per cent of HCC patients received LT within 3 months of wait listing, indicating excessive priority for HCC especially for small HCC which have a low risk of progression to advanced disease or complications, for the first year (Yao FY, et al. 2002). Furthermore following LT, 5 year survival is 60% (Europe), 45% (US) and 10 year survival is 47% (Europe) (Pelletier SJ, et al. 2009; Dutkowski P, et al. 2010).
1.3.6 MELD Limitations
MELD score is a good predictor of survival prior to LT but in 15% of patients MELD score does not accurately predict survival (Kamath S, et al. 2007). Limitations of MELD have been emphasized by a few authors (Neuberger J, et al. 2004, Freeman RB et al 2005). The laboratory test values included in the equation are subject to inter laboratory variability. Regarding serum creatinine; the use of different laboratory methodology (O’Leary modified Jaffe, compensated kinetic Jaffe, enzymatic and standard kinetic Jaffe) for determination of serum creatinine resulted in marked variations in measurements and investigators found that there is poor agreement among different assays for creatinine (Cholongitas E. 2007). The raised serum creatinine (as a late event) is a known predictor of poor prognosis in liver cirrhosis (Ruf AE, et al. 2005) but
serum creatinine values may be lowered due to reduced muscle mass, selection of one creatinine value amongst the few fluctuating values in a decompensated cirrhotic on diuretic therapy, and the arbitrarily selected value of 4 for dialysis patients. Serum creatinine is also influenced by age and gender as well as ethnicity, which may lead to discrimination against women, white, or malnourished patient. Female patients with liver disease have lower glomerular filtration rates than males for the same creatinine levels in cohorts with abnormal liver function tests, as well as candidates for liver transplantation (Cholongitas E, et al 2007). Correcting the creatinine in females for the same glomerular filtration rate in males showed that the current MELD scoring may generate significantly lower MELD scores in females despite a similar renal function, and thus a lower priority for liver transplantation compared with males. Various methods for creatinine measurement have introduced to overcome this interference but there is little concordance between different assays and no accepted consensus on the best method (Cholongitas E, et al. 2005). Regarding, total serum bilirubin: MELD score includes total bilirubin, which is a sum of direct (hepatic) and indirect (non-hepatic) bilirubin. In cirrhosis, increased indirect bilirubin may result from glucose-6 phosphate deficiency (G6PD), thalessaemia trait, spur cell anaemia, ribavirin, anti-retroviral drugs. Whether inclusion of direct bilirubin instead of total bilirubin for measuring the MELD score, improves its accuracy or not, is still not clear that the direct fraction could be a more accurate predictor of survival than the total value (Kamath S, et al. 2007). In addition, the accuracy of INR in representing the coagulative status of the patient has been questioned, considering that coagulopathy in cirrhosis affects different sites of the coagulation pathway (Kamath S, et al. 2007) and that it is designed to standardize the anticoagulate effect of warfarin and may not reflect the severity of the disease (Cholongitas E, et al. 2005). The most common severe cirrhosis complications, such as hepatic encephalopathy, oesophageal variceal bleeding, and spontaneous bacterial peritonitis, are not scored by MELD, and patients high mortality is not properly rated by MELD (Huo TI, et al. 2005). Other clinical conditions in which MELD cannot adequately predict short-term survival and hence to manage patients on the waiting list include: polycystic liver disease, Budd–Chiari syndrome, malnutrition, hepato-pulmonary syndrome, hereditary haemorrhagic telangectasia, cystic fibrosis, recurrent biliary sepsis, and unusual tumours (Freeman Jr RB. 2008). It has been reported also that MELD may not be reliable in predicting survival of HIV infected patients, indeed to give additional points to these candidates can be appropriate (Samuel D, et al. 2008). MELD
accuracy in predicting survival also seems to be lower for patients awaiting re-transplantation. In general, re-transplantation has a worse outcome than first transplant, mainly because of surgical technical difficulties (Zhu ZJ, et al. 2007; Onaca N, et al. 2006). Moreover, the MELD score failed to predict patient or graft survival in living donor liver transplant recipients (Hayashi PH, et al. 2003) and it did not correlate with the severity of the disease of patients affected by malignancy or metabolic disorders (Llado L, et al. 2002) or with the degree of encephalopathy and ascites (Yoo HY, et al. 2003). Additionally, studies carried out in patients undergoing TIPS, the original source of the MELD score, found that MELD model and CTP can be used with equal accuracy for prognosis (Angermayr B, et al 2003; Schepke M, et al. 2003) and that mortality was unpredictable in patients with refractory ascites by using pretransplant variables (Thuluvath PJ, et al. 2003). The use of MELD for allocation is a ‘justice’ and not a ‘utility’ score, as it does not consider outcome after liver transplantation (LT), and donor factors are not considered (Adam R, et al. 2000). As a result, both pre-LT MELD and change in MELD in the course of the disease (Northup PG, et al 2004) do not correlate with post-LT survival, with only a c-statistic of 0.58 in the UK (Jacob M, et al. 2004). C-statistic for 3-month survival on the waiting list is as low as 0.75 (Heuman D, et al. 2003). Use of MELD outside the USA, has also given poor predictive accuracy in individual patients and poor generalisability (Llado L, et al. 2002).
1.3.7 Classification of Candidates for Liver Transplants According to Old UNOS System United network for organ-sharing (UNOS) liver status classification.
Status 1
Fulminant liver failure with life expectancy <7 days (i) Fulminant hepatic failure as traditionally defined (ii) Primary graft nonfunction <7 days of transplantation (iii) Hepatic artery thrombosis <7 days of transplantation (iv) Acute decompensated Wilson’s disease
Status 2a
Hospitalized in ICU for chronic liver failure with life expectancy <7 days, with a Child-Pugh score of ≥10 and one of the following:
(i) unresponsive active variceal hemorrhage (ii) hepatorenal syndrome
(iii) refractory ascites/hepatic hydrothorax, (iv) Stage 3 or 4 hepatic encephalopathy
Status 2B
Requiring continuous medical care, with a Child-Pugh score of ≥10, or a Child-Pugh score ≥7 and one of the following:
(i) unresponsive active variceal hemorrhage (ii) hepatorenal syndrome
(iii) spontaneous bacterial peritonitis (iv) refractory ascites/hepatic hydrothorax, or presence of hepatocellular carcinoma Status 3
Requiring continuous medical care, with a Child-Pugh score of ≥7, but not meeting criteria for Status 2B
Status 7 Temporary inactive
The MELD score is calculated. If the MELD score is ≥30 the patient’s UNOS listing status is 2a, if it is 24–29, it is 2b, and if it is less than 24, it is 3. A Status 1 patient is given priority following which those with a MELD/PELD score ≥15 and later those having a score of ≤14
From http://www.unos.org/ initially implemented in July 1997 later modified in January 1998 and August 1998.
1.3.8 Other Scoring Systems
The model for end-stage liver disease (MELD) scoring System does not include any parameter correlated with complications of cirrhosis in its formula. Liver cirrhosis alter vascular haemodynamics resulting in dilutional hyponatraemia associated with refractory ascites, hepato-renal syndrome and increased mortality (Porcel A, et al. 2002; Arroyo V, et al. 2003; Sersté T, et al. 2008; Fernández-Esparrach G, et al. 2001; Borroni G, et al. 2000). Dilutional hyponatremia (free water retention) results from a higher rate of renal retention of water despite increased total body sodium due to antidiuretic hormone mediated reduction in free water clearance (Schrier RW, et al. 1988; Gines P, et al. 1998). Free water retention positively correlate with the severity of portal hypertension (Freeman RB, et al. 2004) and serum sodium (SNa) level may inversely reflect the severity of portal hypertension. Hyponatremia in this setting has been correlated with increased mortality (Llach J, et al. 1988; Biggins SW, et al. 2006),
consequently patients with low MELD scores who have persistent ascites and low SNa are at a disadvantage and at a higher risk of mortality than that predicted by the MELD score alone (Srikureja W, et al. 2005) Some studies have indicated that serum sodium is an independent predictor of mortality in patients with cirrhosis (Wang YW, et al. 2007; Selcuk H, et al. 2007) and the incorporation of Na into the MELD may enhance its prognostic accuracy (Biggins SW, et al. 2005; Ruf AE, et al. 2005). Consequently new scoring systems have been proposed with new mathematical equations based on both MELD and Na, known as the MELD with the incorporation of serum sodium (MELD-Na) (Biggins SW, et al. 2006) the integrated MELD (iMELD) score (Luca A, et al. 2007) and the MELD to sodium (MESO) index (Huo TI, et al. 2007). Serum sodium <126 mEq/L in cirrhotic patients listed for LT is an independent predictor of 3- and 6-month mortality (Biggins SW, et al. 2005). Persistent ascites (including hydrothorax) and low serum sodium are independent predictors of 6-month survival, especially in patients with MELD below 21, and concurrent ascites and serum sodium <135 mEq/L is more predictive of survival than MELD score alone (Heuman DM, et al. 2005). It was reported that hyponatraemia (≤130mEq/L) was an excellent predictor of outcome in cirrhotic patients awaiting LT (Ruf AE, et al. 2005). For values between 120 and 135mEq/L for each unit decrease in serum sodium concentration there is an increased mortality risk increase by 12% (Londo˜no MC, et al. 2007) addition of serum sodium to the MELD score in this study did not seem to significantly improve MELD prognostic accuracy. Considering these preliminary results, Biggins et al. (Biggins SW, et al. 2007) and subsequently Kim et al. (Kim SY, et al. 2007) proposed a new MELD-based score, called MELD-Na, obtained through the integration of serum sodium and traditional MELD parameters using the following formula:
[MELD-Na =MELD + 1.59 (135−Na)].
Compared to the traditional MELD score, the MELD-Na score showed a more accurate 6-month survival for cirrhotic patients awaiting LT.
Kim WR, et al. (2008) reported another equation:
[MELDNa =MELD-Na−(0.025)×MELD×(140−Na) + 140],
suggesting that MELD-Na may provide better short-term mortality prediction for candidates awaiting LT. In this study, the majority of the patients showed serum sodium concentrations above 135 mmol/L; for those patients, the MELD-Na score was essentially equal to the MELD score. Moreover, for candidates with MELD scores above
30, the effect of hyponatraemia was quite small. However, for patients with moderate MELD scores, the effect may be considerable. Luca et al proposed a score called iMELD, calculated considering age, serum sodium and MELD. According to the reported data, the iMELD was better than MELD in predicting three, 6- and 12-month survival of enrolled patients (Luca A, et al. 2007).
United Kingdom Model for end-stage liver disease. The UK Liver Transplant Units (Barber KM, et al. 2007) described the UKELD (United Kingdom Model for end-stage liver disease) calculated using serum bilirubin, INR, creatinine and serum sodium.
Delta MELD. Delta MELD (D-MELD) is the difference between the MELD score calculated at two separate time points. The rate of increase in D-MELD is calculated by dividing D- MELD in the interval in months between the first and the second determination. In an attempt to measure the dynamic change in residual liver function over time. Patients with a D-MELD greater than 5 points showed a higher waiting list mortality risk than those for whom the MELD score increased more gradually.
MELD-XI. In certain clinical situations e.g. patients with Budd–Chiari syndrome, or other thrombophilic syndromes managed by using anticoagulants e.g. warfarin and/or low molecular weight heparins (Horton JD, et al. 2008) which may interfere with vitamin K-dependent gamma carboxylation of clotting factors resulting in an increasing INR in the MELD modifying the final MELD score (Suttie JW.1987). A new score has been proposed omitting INR and the equation is as follow: [MELDXI = 5.11 Ln(B) + 11.76 Ln(Cr) + 9.44]. (Heuman, et al. 2007).
MELD modified by gender. Female cirrhotic patients usually have a lower glomerular filtration rate than male patients with comparable creatinine values (Cholongitas E, et al 2007). In this setting another new MELD score has been obtained by correcting creatinine according to gender (MELD modified by gender) to provide an equal priority to female patients on the waiting list as male patients (Huo, et al. 2007). Its predictive efficacy is more reliable for mid-term survival (9 and 12 months).
MESO Index. Another score called the MESO index has been proposed. MESO index had a higher significant predictive value than the traditional MELD score.
MESO index = (MELD Score/SNa mEq/L) x 10.
Updated MELD. Another modification of MELD score called updated MELD, assigning a lower weight to creatinine and INR and a higher weight to bilirubin. This score was reported to be a better survival predictor than traditional MELD at all time points.
(Sharma, et al. 2008).
Artificial neural network (ANN). ANN application permits correlating simultaneously many different variables which can provide a more complete analysis of prognostic factors than traditional statistical techniques (Cross S, et al. 1995) The variables included in the ANN were: aspartate aminotransferase (IU/L), total serum bilirubin (mg/dL), gamma-glutamyl transpeptidase (GGT) (IU/L), alkaline phosphatase (IU/L) serum creatinine (mg/dL), serum albumin value (g/dL), INR value, platelet count (×103/mm3), white cell count (×103/mm3) and haemoglobin concentration (g/dL). The ANN analysis was shown to be superior to MELD in predicting the 3-month survival in patients awaiting LT (Cucchetti A, et al 2007). Specific software is required for calculation. Some other scoring models have been developed to predict the survival of patients with cirrhosis not eligible for LT such as Modified CTP Score (Huo et al 2006), MESO Index.
Modified CTP Score (Huo, et al. 2006). An additional class is introduced (class D) giving an additional point to patients with serum albumin <2.3 g/dL, bilirubin >8 mg/dL or prothrombin time prolongation >11 to overcome the ceiling effect of the original CTP system.
Modified Child–Turcotte–Pugh (modified CTP) scoring system
Score 1 2 3 4
Ascites None Not controlled Severe
Encephalopathy Grade None Grade I-II Grade III-IV
Bilirubin (mg/dL) <2 2-3 3.1-8 >8
Albumin g/dL >3.5 3.5-2.8 2.3-2.7 <2.3
Prothrombine Time Prolongation (sec) <4 4-6 6-11 >11 Scores 5–6 = Class A Scores 16-18 = Class C
Scoring
system Score Formula
MELD-Na= MELD-Na−(0.025)×MELD×(140−Na)+140 iMELD = MELD+ (age×0.3)−(0.7×Na) + 100
UKELD= =[(5.395×ln(INR))+(1.485×ln(creatinine))+(3.13×ln(bilirubin))−(81.565×ln(Na))] + 435 Delta MELD = MELD2 −MELD1
MELD-XI = 11.2×ln(INR)+9.57×ln[(186×(Age)−0.203/female GFR(1/1.154)]+3.78×ln[bilirubin]+6.43 ANN = Specific software required for calculation
Updated
MELD = 1.266×ln(1+creatinine)+0.939×ln(1+bilirubin)+1.658×ln(1+INR) ANN = Specific software required for calculation
Notes: MELD: Mayo clinic model for end stage liver disease; Na: serum sodium; INR:
international normalized ratio; GFR: glomerular filtration rate; Bilirubin and Creatinine are expressed in mg/dL.
1.4 Indications For Liver Transplantation:
The list of indications for liver transplantation includes all the causes of end stage liver disease, which are irreversible and curable by the procedure. In 1997 the American Society of Transplant Physicians and the American Association for the Study of the Liver Disease put forward the minimal listing criteria for patients with end stage liver disease. To qualify for the listing, the patient’s expected survival should be ≤90% within 1 year without transplantation. Liver transplantation should lead to prolonged survival and an improved quality of life (M. R. Lucey, et al. 1997). Hepatitis C virus (HCV) or alcohol-induced liver disease account for the most common disease indications in adults with liver cirrhosis (http://www.eltr.org). Other indications include cholestatic liver disorders (primary biliary cirrhosis, primary sclerosing cholangitis) (PBC, PSC), hepatitis B virus (HBV) infection, autoimmune hepatitis (AIH), inherited metabolic diseases (Wilson’s Disease, hemochromatosis, α-1-antitrypsin deficiency), nonalcoholic steatohepatitis, HCC, and acute or acute - on chronic hepatic failure. In children, biliary atresia and metabolic liver diseases are the most common indications.
