- Email: [email protected]
Liver Transplant Waitlist Outcomes and the Allocation of Hepatocellular Carcinoma Model for End-Stage Liver Disease Exception Points at a Low-Volume Center
Liver Transplant Waitlist Outcomes and the Allocation of Hepatocellular Carcinoma Model for End-Stage Liver Disease Exception Points at a Low-Volume Center E.K. Tana,*, B.K.P. Goha, S.Y. Leea, T.L. Krishnamoorthyb, C.K. Tanb, and P.R. Jeyaraja a
Department of Hepato-pancreato-biliary and Transplant Surgery, Singapore General Hospital, Bukit Merah, Singapore; and Department of Gastroenterology & Hepatology, Singapore General Hospital, Bukit Merah, Singapore
b
ABSTRACT Background. Organ scarcity continues to be the main problem limiting the number of liver transplants performed. Outcomes of patients waitlisted for an organ in an Asian country with low organ donation rate have not been well evaluated. Our current policy of allocating 15 exception points to patients with hepatocellular carcinoma (HCC) to render them competitive for a transplant also requires review. Methods. The waiting list registry and the organ transplant registry of a single institution in Asia were reviewed from December 2005 to June 2016 for all patients who underwent liver transplantation. Patient characteristics and outcomes of waitlist dropouts were evaluated. Statistical analyses were performed using SPSS version 20.0. Results. One hundred seventy-three patients were waitlisted for a deceased donor liveronly transplant. The most common etiology of liver disease was hepatitis B, followed by cholestatic diseases. Approximately half of the patients had HCC (45.6%). Priority listing for transplant comprised 15.6% of cases. Median Model for End-Stage Liver Disease (MELD) at listing was 15, and median waiting time to transplant was 17 weeks (interquartile range ¼ 6.5e43.5). Overall, 89 (51.4%) patients underwent liver transplantation and 68 (39.3%) dropped out. For patients with HCC, the most common cause of dropout was progression beyond University of California San Francisco transplant criteria (62.5%). The cumulative incidence of dropout at 3 months among patients with HCC who received exception MELD scores was 11%. This was higher than those listed with physiologic MELD of 14e16 points (7%) but lower than those with 17e19 points (16%). Conclusions. Hepatitis B-related liver disease and HCC comprise the majority of patients listed for liver transplant. Dropout rates are high and this is due to the lack of donor organs. The current policy of allocating 15 exception MELD points to patients with HCC within transplant criteria may underestimate the dropout risk of patients with HCC in our population.
O
UR institution’s liver transplant program and registry began in 2005 and has been steadily growing in terms of the complexity of cases transplanted. Having accumulated a decade’s worth of experience it was timely to audit and review our waitlist registry. With expanding indications for liver transplantation and acceptance as a treatment option for end-stage liver disease and hepatocellular carcinoma (HCC), we recognize that referral patterns and
0041-1345/18 https://doi.org/10.1016/j.transproceed.2018.08.032
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*Address correspondence to Ek Khoon Tan, Department of Hepato-pancreato-biliary and Transplant Surgery, Singapore General Hospital, 20 College Road, Academia Level 5, Outram Road, S(169856), Bukit Merah, Singapore. Tel: þ65-6326-5564. E-mail: [email protected] ª 2018 Elsevier Inc. All rights reserved. 230 Park Avenue, New York, NY 10169
Transplantation Proceedings, 50, 3564e3570 (2018)
MODEL FOR END-STAGE LIVER DISEASE EXCEPTION POINTS
indications for transplantation evolve over time. Unfortunately, organ scarcity continues to be a major problem and the number of patients added to the waitlist annually outstrips the number of transplantations done, resulting in a growing waitlist registry [1,2]. The Human Organ Transplant Act mandates that all Singapore citizens and permanent residents of sound mind aged 21 years and above are automatically enrolled as organ donors unless they opt out. Despite that, organ donation rates remain low at 7e9 per million population (pmp) [2]. Candidacy for transplantation is expanding, and treatment of HCC is now widely accepted to involve transplantation as a treatment modality [3]. Therefore, we can expect the waitlist registry to continue to grow. The significant number of patients in the waitlist with HCC poses a separate challenge for organ allocation. Patients with HCC have a low physiologic Model for EndStage Liver Disease (MELD) score when they have compensated liver disease. Therefore, those who meet transplant criteria are given exception MELD points to allow them a chance of being allocated an organ as compared to patients with end-stage liver disease [4]. The traditional method has been to equilibrate the 3 month rate of dropout or death of waitlisted patients with HCC to those waitlisted based on their physiologic MELD. The corresponding physiologic MELD score would thereby be the MELD exception score for HCC. The alternative would be to allocate exception points based on the tumor characteristics [5]. Worldwide, there is no consensus and the policy of MELD exception points vary widely [6,7]. This is because each country has different disease demographics, and the MELD exception policy essentially assists in balancing the demand and supply of available organs to patients with HCC and those with chronic liver disease [8]. This balance is not easy to identify, and varies over time as well. For example, it has been recognized that in the United States, the previous system of points allocated may have preferentially benefited patients with HCC at the expense of those without HCC [8]. As a result, the Organ Procurement and Transplantation Network of the United States revised their policy of exception points for HCC in 2015. Presently in the United States, MELD exception points are only assigned 6 months after acceptance, starting with 28 and increasing every 3 months to a maximum score of 34 [9]. Here, in Singapore, patients with HCC within University of California, San Francisco (UCSF) transplant criteria [10] immediately receive 15 MELD exception points with no increment over time. Due to the lack of local data at the start of the transplant program, 15 points were allocated based on the premise that survival benefit of transplant occurs when patients have a MELD score greater than 15 [11], and that patients with HCC within Milan or UCSF criteria have good outcomes after liver transplantation [10]. In the setting of a low-volume center with limited availability of donor organs, it is challenging to find the equipoise between allocating organs to patients with and without
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HCC. In order to better understand organ waitlist outcomes, we decided to review our waitlist registry from the inception of the program to determine the dropout rates, causes of dropout, and determine if there is a disparity in organ allocation between patients with and without HCC. This will allow us to further ascertain if the MELD exception policy is starting at the right value, and whether incremental points should be given over time. METHODS Data Collection The waitlist registry at our institution was retrospectively reviewed from December 2005 to June 2016 for all patients who were accepted onto the waiting list for a liver transplant. Patient records were reviewed up to June 2017 for changes to the transplant status. The study was approved by the SingHealth Institutional Review Board.
Patient Characteristics All patients who were included on the waiting list were evaluated. Only patients who were listed for a liver-alone transplantation were included for analysis. Patients who were nonadherent to waitlist protocols or withdrew from the waitlist due to nonmedical reasons were excluded from analysis. Patient demographic characteristics, indication for transplant, and clinical and laboratory data including MELD score were reviewed. Patients with HCC had to fulfill UCSF criteria to be accepted into the national transplant waitlist for a Deceased Donor Liver Transplant [10]. Salvage liver transplant was defined as liver transplantation performed for recurrent HCC or deterioration of liver function after primary liver resection [12].
Outcome Measures Dates of entry into the waitlist, transplantation, dropout, and reasons for dropout from the waitlist were recorded. Dropout was defined as removal from the waiting list as a result of poor medical condition (ie, too sick for transplantation), death, or in patients with HCC progression to beyond transplant criteria [13]. Patients within the waitlist would therefore end up in 1 of 4 groups: a. underwent transplantation, b. dropped off waitlist, c. still on the waitlist, d. removed from waitlist as condition had improved and patient did not need a transplant. The primary outcome studied was dropout rate at 3 months. The secondary outcome studied was dropout rate at 1 year.
Statistical Analysis As there were 3 different scenarios for censorship while on the waitlist (ie, dropout, transplant, and improvement of condition), using the Kaplan-Meier method to analyze time-to-event data would yield misleading results by overestimating the cumulative probabilities for each of the event outcomes. Instead, the method of competing risk analysis should be applied. In this study, the method of Cumulative Incidence of Competing Risk (CICR) analysis as described by Verduijn et al was used [14]. To determine if the MELD exception score of 15 was appropriate, we used CICR analysis to determine the dropout rates of patients with HCC utilizing MELD exception scores and compared that with patients who were listed based on their physiological MELD. Statistical computation was performed on SPSS version 20.0 (IBM
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Corporation, Armonk, NY, United States). Results of continuous variables were presented as median (interquartile range [IQR]). The Mann-Whitney U test and c2 analysis were used to compare continuous and categorical variables. All the P values reported were 2-sided and P values of less than .05 were considered statistically significant.
RESULTS Demographics
Between December 1, 2005, and June 30, 2016, a total of 189 patients were identified on the institutional liver transplant registry. Of these, 173 were placed on the national waitlist for a deceased donor liver-alone transplant. Excluded patients include a patient who was listed for simultaneous heart-liver transplant, 7 patients with HCC that were beyond UCSF criteria and were on the living donor liver transplant waitlist, and 8 patients who were either nonadherent with waitlist follow-up or changed their minds about transplantation while on the waitlist. The overall demographics of the patients are described in Table 1. The median age at listing was 57 years (IQR Table 1. Demographics of Waitlisted Candidates Variable
Overall (n ¼ 173)
Median age, years (IQR) 57 (51e61) Male sex 121 (69.9) Ethnicity Chinese 143 (82.7) Malay 15 (8.7) Indian 8 (4.6) Others 7 (4.0) Etiology of liver disease Hepatitis B 77 (44.5) Hepatitis C 13 (7.5) NASH 17 (9.8) Alcohol-related 10 (5.8) Cryptogenic 15 (8.7) PBC/AIC/PSC 21 (12.1) Other 20 (11.6) First transplant 172 (99.4) Priority listing for 27 (15.6) transplant MELD at listing 35 22 (12.7) 30e34 10 (5.8) 25e29 6 (3.5) 20e24 15 (8.7) 17e19 25 (14.5) 14e16 83 (48.0) <14 12 (6.9) Median MELD at 15 (15e23) listing (IQR)
HCC (n ¼ 79)
Non-HCC (n ¼ 94)
P Value
59 (54e63) 55 (46e59) <.001 73 (92.4) 48 (51.1) <.001 67 7 3 2
(84.8) (8.9) (3.8) (2.5)
76 8 5 5
(80.9) (8.5) (5.3) (5.3)
.77
50 8 11 7 3 0 0 79 2
(63.3) (10.1) (13.9) (8.9) (3.8) (0) (0) (100) (2.5)
27 5 6 3 12 21 20 93 25
(28.7) (5.3) (6.4) (3.2) (12.8) (22.3) (21.) (98.9) (26.6)
<.001
3 2 0 0 4 66 4 15
(3.8) (2.5) (0) (0) (5.1) (83.5) (5.1) (15e15)
19 8 6 15 21 17 8 20
(20.2) <.001* (8.5) (6.4) (16.0) (22.3) (18.1) (8.5) (16e31) <.001
51e61). There was a predominance of male patients (69.9%). The most common etiology of liver disease was hepatitis B (44.5%), followed by cholestatic diseases (12.1%). Nonalcoholic steatohepatitis comprised 9.8% of all cases. The median MELD at listing was 15 (IQR 15e23). Overall, 45.6% of patients had HCC. Comparing patients with and without HCC who were waitlisted, we found that they were significantly older with a median age of 59 versus 55 years (P < .001), of male sex (92.4% vs 51.1%, P < .001), less likely to be associated with a priority transplant (2.5% vs 26.6%, P < .001), and had a lower median MELD score at listing (15 vs 20, P < .001). Etiology of liver disease of patients with HCC was significantly different from those without HCC (P < .001). Waitlist Outcomes
Figure 1 shows the status of the waitlisted patients (as of June 2017) stratified by the year they were waitlisted. Therefore, there were on average, 16.3 candidates added to the waitlist each year. At the time of review, 89 (51.4%) patients had undergone a liver transplant, 68 (39.3%) patients had dropped out of the waiting list, 7 (4.0%) patients were still on the waiting list, and 9 (5.2%) patients had been removed as they did not need a transplant. Comparing the 2 groups: those that received a transplant, and those that dropped out of the waiting list, we found that they were comparable based on demographic data and underlying disease (data not shown). Of the 27 patients listed for a priority transplant, 9 (33.3%) underwent liver transplantation, 15 (55.6%) dropped out due to death, and, 3 (11.1%) were removed due to improvement in medical condition. The median waiting time to transplant was 17.0 weeks (IQR 6.5e43.5), while the median time to dropout was 9.5 weeks (IQR 1e53.5). The median MELD at dropout was higher than that at transplant (25 vs 17, P ¼ .044). Patients with HCC
1.0 <.001
Results expressed as n (%) unless specified. Proportions and medians were compared with the data analyzed with the Pearson chi-square test and Mann-Whitney U test, respectively. Abbreviations: AIC, autoimmune cholangiopathy; HCC, hepatocellular carcinoma; IQR, interquartile range; MELD, model for end-stage liver disease; NASH, nonalcoholic steatohepatitis; PBC, primary biliary cirrhosis; PSC, primary sclerosing cholangitis. *Linear-by-linear association.
Of the 79 patients with HCC, 64 (81.0%) patients received MELD exception points of 15. The remaining patients with HCC had physiologic MELD scores higher than 15. At the time of review, 32 patients (40.5%) had dropped out, 41 patients (51.9%) were transplanted, and 6 patients (7.6%) were still on the waitlist. The proportion of patients with HCC who dropped out was similar to that of patients without HCC (P ¼ 1.0). Comparing patients with HCC who were transplanted with those that dropped out, we found that both groups were similar in terms of factors that would affect their likelihood of transplant, such as priority status, MELD score, and whether it was a salvage transplant (Table 2). Tumor characteristics such as serum alphafetoprotein (AFP), number of HCC nodules, and size of largest nodule were similar between both groups. The dropout group, however, was more likely to have received bridging therapy for HCC while on the waitlist (58.1% vs 31.7%, P ¼ .03). The most common reason for dropout was progression of HCC (62.5%), followed by death while on
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Fig 1. Patient status by year entered into waitlist from December 2005 - June 2016 at closure of study in June 2017.
Table 2. Characteristics of Waitlisted Patients With HCC Characteristic
Median age, years (IQR) Male sex Ethnicity Chinese Malay Indian Others Priority listing for transplant Median MELD at listing (IQR) Median MELD at transplant/dropout (IQR) Median AFP (ng/mL) Number of nodules 0 1 2 3 Size of largest HCC nodule, mm (IQR) Salvage transplant Bridging therapy while on waiting list Time to transplant/dropout, weeks (IQR) Cause of dropout Cancer progression Death Medically unsuitable
Transplanted (n ¼ 41)
Dropout (n ¼ 32)
P Value
60 (54.5e63) 58.5 (54e63.75) 37 (90.2) 30 (93.8)
.89 .69
34 5 1 1 1 15 15
.72
(82.9) (12.2) (2.4) (2.4) (2.4) (15e15) (15e17)
7.1 (0.8e708) 16 18 5 2 9
(39.0) (43.9) (12.2) (4.9) (0e22.5)
27 2 2 1 1 15 15
(84.4) (6.2) (6.2) (3.1) (3.1) (15e15) (15e18)
1.0 .35 .58
7.3 (1.3e3095)
.78
6 21 3 2 14.5
(18.8) (65.6) (9.4) (6.3) (6.5e24.3)
*.281
.20
14 (34.1) 13 (31.7)
11 (35.5) 18 (58.1)
24 (10e49)
32 (9.3e84.8)
.34
20 (62.5) 7 (21.9) 5 (15.6)
NA
NA
the waiting list (21.9%). Five patients (15.6%) were deemed medically too ill for transplant and removed from the list.
1.0 .03
Results expressed as n (%) unless specified. Proportions and medians were compared with the use of the Pearson chi-square test and Mann-Whitney U test, respectively. Abbreviations: AFP, alpha-fetoprotein; HCC, hepatocellular carcinoma; IQR, interquartile range; NA, not applicable. *Linear-by-linear association.
Dropout Analyses
Using the CICR method, the cumulative incidence of dropout at 3 months and 1 year was 21% (95% confidence interval [CI]: 16%e28%) and 29% (95% CI: 23%e37%), respectively. The cumulative incidence of transplant at 3 months and 1 year was 20% (95% CI: 15%e27%) and 42% (95% CI: 35%e50%), respectively (Fig 2A). For patients with HCC, the cumulative incidence of dropout was 13% (95% CI: 7%e23%) and 22% (95% CI: 14%e33%) at 3 months and 1 year, while the cumulative incidence of transplant was 16% (95% CI: 10%e27%) and 41% (95% CI: 31%e53%) at 3 months and 1 year (Fig 2B). For patients without HCC, the cumulative incidence of dropout was 29% (95% CI: 21%e39%) and 36% (95% CI: 28% e47%) at 3 months and 1 year, while the cumulative incidence of transplant was 23% (95% CI: 16%e34%) and 44% (95% CI: 35%e55%) at 3 months and 1 year (Fig 2C). We segregated patients with HCC who were listed using MELD exception points (15 points) and compared their cumulative incidence of dropout over time with patients who were listed based on their physiologic MELD (Fig 3). There were 63 patients (36.4%) in the HCC group listed using MELD exception points, and 110 patients (63.6%) using physiologic MELD scores. The cumulative incidence of dropout of HCC patients was 11% (95% CI: 5%e22%) at 3 months. In contrast, the cumulative incidence of dropout of waitlisted patients with MELD score of 14e16 (n ¼ 20) was 7% (95% CI: 1%e47%) while that of MELD scores 17e19 (n ¼ 25) was 16% (95% CI: 7%e39%). At 1 year, the cumulative risks of drop out for patients with HCC patients,
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Fig 2. (A) Likelihood of dropout and transplant over time. (B) Cumulative incidences of events in patients with HCC. (C) Cumulative incidences of events in patients without HCC. Abbreviation: HCC, hepatocellular carcinoma.
MELD 14e16, and MELD 17e19, were 22% (95% CI: 14% e35%), 29% (95% CI: 12%e65%), and 24% (95% CI: 12% e48%), respectively. Thus, the cumulative incidence of dropout of these patients with HCC with MELD exception points did not exceed that of MELD 17e19 even up to 1 year. DISCUSSION
The liver transplantation scene in Singapore is small, however, our center continues to see a steady stream of referrals annually. The volume of cases limits the depth of analysis in our study here. Nevertheless, analysis of the waiting list reveals disease patterns and trends, of which HCC continues to be a major indication for transplantation in Singapore. The main etiology of liver disease remains to be hepatitis B. This is consistent with the disease epidemiology in
Singapore [15]. Alcoholic liver disease, autoimmune hepatitis, primary biliary cirrhosis, and sclerosing cholangitis were rare indications for deceased donor liver transplant. Patients who had HCC tended to be older (P < .001), and of the male sex (P < .001). There were no significant differences in the sex and ethnicity in the transplant or dropout groups. The glaring issue is a 39.3% dropout while on the waiting list. Patients had a higher median MELD at the time of dropout than at initial listing. This meant that they accumulated physiological MELD points, but no organs were available despite moving up on the waiting list. For patients who were listed for a priority transplant, only 33.3% of them successfully underwent a transplant, while 55.6% of them died without a transplant. Next, we observed that, of the patients with HCC waitlisted who dropped out, about half of them (62.5%) dropped out due to progression of HCC.
MODEL FOR END-STAGE LIVER DISEASE EXCEPTION POINTS
Fig 3. Risk of dropout: patients with HCC on MELD exception points versus patients listed on physiological MELD (stratified by MELD score). Abbreviations: HCC, hepatocellular carcinoma; MELD, Model for End-Stage Liver Disease.
Waitlisted candidates for a salvage liver transplant did not have higher dropout rates compared to those waitlisted for a primary liver transplant (P ¼ 1.0). Thus, patients who are candidates for both should consider resection first, since there is limited availability of deceased donor organs [16,17]. The finding that the likelihood of dropout was associated with bridging therapy for HCC while on the waitlist does not necessarily mean that bridging is not a good strategy for patients with HCC within UCSF criteria. It is recommended that bridging therapy for HCC is advised if the waiting time is more than 6 months [18]. This observation is another reflection of the overarching problem of organ shortage hereddespite being bridged in order to “buy time,” they may still not be allocated a liver. The MELD score continues to be a useful tool in the allocation of available liver grafts [19]. Those with the highest MELD had the highest cumulative risk of dropout at 3 months while those with lower MELDs had lower dropout risk while on the waitlist and this is clearly shown in Fig 3. Due to our population size that directly affects the paucity of patients listed for transplantation, we had to group patients into meaningful MELD categories to perform the analysis. Since the primary focus was the HCC MELD of 15, we used a bracketing technique to group those with MELD 14e16 together as the lower bracket, and MELD 17e19 as the higher bracket. The remaining patients on physiological MELDs were grouped at increments of 5. We found that patients with HCC and who were listed based on MELD exception points (15 points) had a 3 month risk of dropout that was higher than those with a physiological MELD score of 14e16, but less than that of 17e19. We may interpret this as HCC patients within transplant criteria at our center “behave” as if they have a physiological MELD greater than those with a MELD of 14e16, yet less than those with a MELD of 17e19. In addition, we observed that
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the cumulative risk of dropout of these patients with HCC did not increase at an increasing rate compared to those of a higher MELD. The graph shows that the interpolated line for these patients with HCC does not cross and exceed that of the next higher MELD category, that is, MELD 17e19. This data suggests that incremental points do not need to be given over time while on the waitlist. While the “true” exception MELD score for HCC was not elucidated in this study, this is supportive evidence that the current system of 15 exception points is marginally lower than what it should be. In addition, the data shows that the dropout rate of these patients with HCC do not increase over time. This implies that these patients in our population should not receive incremental MELD exception points over time while on the waitlist, contrary to the current MELD exception points system practiced in the United States. As this study only encompasses data from 1 of the 2 academic transplant centers in Singapore, representing approximately half of the overall national deceased donor liver transplant volume, we expect that with the complete national data, we may be able to find the exact equipoise of MELD exception points to be assigned for patients with HCC waiting for liver transplant in Singapore. This study also confirms the relevance of ongoing and periodic review of policies pertaining to the allocation of MELD exception points, as has been best demonstrated by the evolving policies of the Organ Procurement and Transplantation Network. CONCLUSION
End-stage liver disease remains an important disease in the region. Unfortunately, there is a paucity of available deceased donor organs for liver transplantation. Hepatitis B remains the prevalent form of viral hepatitis in the region. HCC comprises almost half of the cases waitlisted for liver transplantation. The proportions of patients who dropout are high at 39%, suggesting there is an urgent need to increase the availability of donor organs. The current policy of allocating 15 MELD exception points (with no increment over time) to patients with HCC within transplant criteria may slightly underestimate the dropout risk of patients with HCC. REFERENCES [1] Low HC, Da Costa M, Prabhakaran K, Kaur M, Wee A, Lim SG, et al. Impact of new legislation on presumed consent on organ donation on liver transplant in Singapore: a preliminary analysis. Transplantation 2006;82:1234e7. [2] Kwek TK, Lew TW, Tan HL, Kong S. The transplantable organ shortage in Singapore: has implementation of presumed consent to organ donation made a difference? Ann Acad Med Singapore 2009;38:346e8. [3] Goh GB, Chang PE, Tan CK. Changing epidemiology of hepatocellular carcinoma in Asia. Best Pract Res Clin Gastroenterol 2015;29:919e28. [4] Wald C, Russo MW, Heimbach JK, Hussain HK, Pomfret EA, Bruix J. New OPTN/UNOS policy for liver transplant allocation: standardization of liver imaging, diagnosis, classification,
3570 and reporting of hepatocellular carcinoma. Radiology 2013;266: 376e82. [5] Bhat M, Ghali P, Dupont B, Hilzenrat R, Tazari M, Roy A, et al. Proposal of a novel MELD exception point system for hepatocellular carcinoma based on tumor characteristics and dynamics. J Hepatol 2017;66:374e81. [6] De Carlis L, Di Sandro S, Centonze L, Lauterio A, Buscemi V, De Carlis R, et al. Liver-allocation policies for patients affected by HCC in Europe. Curr Transplant Rep 2016;3:313e8. [7] Alcorn JB. United Network for Organ Sharing: Changes to OPTN bylaws and policies from actions at November board of directors meeting. 2014. [8] Toso C, Mazzaferro V, Bruix J, Freeman R, Mentha G, Majno P. Toward a better liver graft allocation that accounts for candidates with and without hepatocellular carcinoma. Am J Transplant 2014;14:2221e7. [9] Organ Procurement and Transplantation Network. Revised liver policy regarding HCC exception scores. https://optn.transplant. hrsa.gov/news/revised-liver-policy-regarding-hcc-exception-scores/; 2015 [accessed date]. [10] Yao FY, Ferrell L, Bass NM, Watson JJ, Bacchetti P, Venook A, et al. Liver transplantation for hepatocellular carcinoma: expansion of the tumor size limits does not adversely impact survival. Hepatology 2001;33:1394e403. [11] Merion RM, Schaubel DE, Dykstra DM, Freeman RB, Port FK, Wolfe RA. The survival benefit of liver transplantation. Am J Transplant 2005;5:307e13. [12] Li HY, Wei YG, Yan LN, Li B. Salvage liver transplantation in the treatment of hepatocellular carcinoma: a meta-analysis. World J Gastroenterol 2012;18:2415e22.
TAN, GOH, LEE ET AL [13] Toso C, Dupuis-Lozeron E, Majno P, Berney T, Kneteman NM, Perneger T, et al. A model for dropout assessment of candidates with or without hepatocellular carcinoma on a common liver transplant waiting list. Hepatology 2012;56:149e56. [14] Verduijn M, Grootendorst DC, Dekker FW, Jager KJ, le Cessie S. The analysis of competing events like cause-specific mortalitydbeware of the Kaplan-Meier method. Nephrol Dial Transplant 2011;26:56e61. [15] Hong WW, Ang LW, Cutter JL, James L, Chew SK, Goh KT. Changing seroprevalence of hepatitis B virus markers of adults in Singapore. Ann Acad Med Singapore 2010;39: 591e8. [16] Poon RT, Fan ST, Lo CM, Liu CL, Wong J. Long-term survival and pattern of recurrence after resection of small hepatocellular carcinoma in patients with preserved liver function: implications for a strategy of salvage transplantation. Ann Surg 2002;235: 373e82. [17] Adam R, Azoulay D, Castaing D, Eshkenazy R, Pascal G, Hashizume K, et al. Liver resection as a bridge to transplantation for hepatocellular carcinoma on cirrhosis: a reasonable strategy? Ann Surg 2003;238:508e18. discussion 518-509. [18] Llovet JM, Mas X, Aponte JJ, Fuster J, Navasa M, Christensen E, et al. Cost effectiveness of adjuvant therapy for hepatocellular carcinoma during the waiting list for liver transplantation. Gut 2002;50:123e8. [19] Wiesner R, Edwards E, Freeman R, Harper A, Kim R, Kamath P, et al. Model for end-stage liver disease (MELD) and allocation of donor livers. Gastroenterology 2003;124:91e6.
Department of Hepato-pancreato-biliary and Transplant Surgery, Singapore General Hospital, Bukit Merah, Singapore; and Department of Gastroenterology & Hepatology, Singapore General Hospital, Bukit Merah, Singapore
b
ABSTRACT Background. Organ scarcity continues to be the main problem limiting the number of liver transplants performed. Outcomes of patients waitlisted for an organ in an Asian country with low organ donation rate have not been well evaluated. Our current policy of allocating 15 exception points to patients with hepatocellular carcinoma (HCC) to render them competitive for a transplant also requires review. Methods. The waiting list registry and the organ transplant registry of a single institution in Asia were reviewed from December 2005 to June 2016 for all patients who underwent liver transplantation. Patient characteristics and outcomes of waitlist dropouts were evaluated. Statistical analyses were performed using SPSS version 20.0. Results. One hundred seventy-three patients were waitlisted for a deceased donor liveronly transplant. The most common etiology of liver disease was hepatitis B, followed by cholestatic diseases. Approximately half of the patients had HCC (45.6%). Priority listing for transplant comprised 15.6% of cases. Median Model for End-Stage Liver Disease (MELD) at listing was 15, and median waiting time to transplant was 17 weeks (interquartile range ¼ 6.5e43.5). Overall, 89 (51.4%) patients underwent liver transplantation and 68 (39.3%) dropped out. For patients with HCC, the most common cause of dropout was progression beyond University of California San Francisco transplant criteria (62.5%). The cumulative incidence of dropout at 3 months among patients with HCC who received exception MELD scores was 11%. This was higher than those listed with physiologic MELD of 14e16 points (7%) but lower than those with 17e19 points (16%). Conclusions. Hepatitis B-related liver disease and HCC comprise the majority of patients listed for liver transplant. Dropout rates are high and this is due to the lack of donor organs. The current policy of allocating 15 exception MELD points to patients with HCC within transplant criteria may underestimate the dropout risk of patients with HCC in our population.
O
UR institution’s liver transplant program and registry began in 2005 and has been steadily growing in terms of the complexity of cases transplanted. Having accumulated a decade’s worth of experience it was timely to audit and review our waitlist registry. With expanding indications for liver transplantation and acceptance as a treatment option for end-stage liver disease and hepatocellular carcinoma (HCC), we recognize that referral patterns and
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*Address correspondence to Ek Khoon Tan, Department of Hepato-pancreato-biliary and Transplant Surgery, Singapore General Hospital, 20 College Road, Academia Level 5, Outram Road, S(169856), Bukit Merah, Singapore. Tel: þ65-6326-5564. E-mail: [email protected] ª 2018 Elsevier Inc. All rights reserved. 230 Park Avenue, New York, NY 10169
Transplantation Proceedings, 50, 3564e3570 (2018)
MODEL FOR END-STAGE LIVER DISEASE EXCEPTION POINTS
indications for transplantation evolve over time. Unfortunately, organ scarcity continues to be a major problem and the number of patients added to the waitlist annually outstrips the number of transplantations done, resulting in a growing waitlist registry [1,2]. The Human Organ Transplant Act mandates that all Singapore citizens and permanent residents of sound mind aged 21 years and above are automatically enrolled as organ donors unless they opt out. Despite that, organ donation rates remain low at 7e9 per million population (pmp) [2]. Candidacy for transplantation is expanding, and treatment of HCC is now widely accepted to involve transplantation as a treatment modality [3]. Therefore, we can expect the waitlist registry to continue to grow. The significant number of patients in the waitlist with HCC poses a separate challenge for organ allocation. Patients with HCC have a low physiologic Model for EndStage Liver Disease (MELD) score when they have compensated liver disease. Therefore, those who meet transplant criteria are given exception MELD points to allow them a chance of being allocated an organ as compared to patients with end-stage liver disease [4]. The traditional method has been to equilibrate the 3 month rate of dropout or death of waitlisted patients with HCC to those waitlisted based on their physiologic MELD. The corresponding physiologic MELD score would thereby be the MELD exception score for HCC. The alternative would be to allocate exception points based on the tumor characteristics [5]. Worldwide, there is no consensus and the policy of MELD exception points vary widely [6,7]. This is because each country has different disease demographics, and the MELD exception policy essentially assists in balancing the demand and supply of available organs to patients with HCC and those with chronic liver disease [8]. This balance is not easy to identify, and varies over time as well. For example, it has been recognized that in the United States, the previous system of points allocated may have preferentially benefited patients with HCC at the expense of those without HCC [8]. As a result, the Organ Procurement and Transplantation Network of the United States revised their policy of exception points for HCC in 2015. Presently in the United States, MELD exception points are only assigned 6 months after acceptance, starting with 28 and increasing every 3 months to a maximum score of 34 [9]. Here, in Singapore, patients with HCC within University of California, San Francisco (UCSF) transplant criteria [10] immediately receive 15 MELD exception points with no increment over time. Due to the lack of local data at the start of the transplant program, 15 points were allocated based on the premise that survival benefit of transplant occurs when patients have a MELD score greater than 15 [11], and that patients with HCC within Milan or UCSF criteria have good outcomes after liver transplantation [10]. In the setting of a low-volume center with limited availability of donor organs, it is challenging to find the equipoise between allocating organs to patients with and without
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HCC. In order to better understand organ waitlist outcomes, we decided to review our waitlist registry from the inception of the program to determine the dropout rates, causes of dropout, and determine if there is a disparity in organ allocation between patients with and without HCC. This will allow us to further ascertain if the MELD exception policy is starting at the right value, and whether incremental points should be given over time. METHODS Data Collection The waitlist registry at our institution was retrospectively reviewed from December 2005 to June 2016 for all patients who were accepted onto the waiting list for a liver transplant. Patient records were reviewed up to June 2017 for changes to the transplant status. The study was approved by the SingHealth Institutional Review Board.
Patient Characteristics All patients who were included on the waiting list were evaluated. Only patients who were listed for a liver-alone transplantation were included for analysis. Patients who were nonadherent to waitlist protocols or withdrew from the waitlist due to nonmedical reasons were excluded from analysis. Patient demographic characteristics, indication for transplant, and clinical and laboratory data including MELD score were reviewed. Patients with HCC had to fulfill UCSF criteria to be accepted into the national transplant waitlist for a Deceased Donor Liver Transplant [10]. Salvage liver transplant was defined as liver transplantation performed for recurrent HCC or deterioration of liver function after primary liver resection [12].
Outcome Measures Dates of entry into the waitlist, transplantation, dropout, and reasons for dropout from the waitlist were recorded. Dropout was defined as removal from the waiting list as a result of poor medical condition (ie, too sick for transplantation), death, or in patients with HCC progression to beyond transplant criteria [13]. Patients within the waitlist would therefore end up in 1 of 4 groups: a. underwent transplantation, b. dropped off waitlist, c. still on the waitlist, d. removed from waitlist as condition had improved and patient did not need a transplant. The primary outcome studied was dropout rate at 3 months. The secondary outcome studied was dropout rate at 1 year.
Statistical Analysis As there were 3 different scenarios for censorship while on the waitlist (ie, dropout, transplant, and improvement of condition), using the Kaplan-Meier method to analyze time-to-event data would yield misleading results by overestimating the cumulative probabilities for each of the event outcomes. Instead, the method of competing risk analysis should be applied. In this study, the method of Cumulative Incidence of Competing Risk (CICR) analysis as described by Verduijn et al was used [14]. To determine if the MELD exception score of 15 was appropriate, we used CICR analysis to determine the dropout rates of patients with HCC utilizing MELD exception scores and compared that with patients who were listed based on their physiological MELD. Statistical computation was performed on SPSS version 20.0 (IBM
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Corporation, Armonk, NY, United States). Results of continuous variables were presented as median (interquartile range [IQR]). The Mann-Whitney U test and c2 analysis were used to compare continuous and categorical variables. All the P values reported were 2-sided and P values of less than .05 were considered statistically significant.
RESULTS Demographics
Between December 1, 2005, and June 30, 2016, a total of 189 patients were identified on the institutional liver transplant registry. Of these, 173 were placed on the national waitlist for a deceased donor liver-alone transplant. Excluded patients include a patient who was listed for simultaneous heart-liver transplant, 7 patients with HCC that were beyond UCSF criteria and were on the living donor liver transplant waitlist, and 8 patients who were either nonadherent with waitlist follow-up or changed their minds about transplantation while on the waitlist. The overall demographics of the patients are described in Table 1. The median age at listing was 57 years (IQR Table 1. Demographics of Waitlisted Candidates Variable
Overall (n ¼ 173)
Median age, years (IQR) 57 (51e61) Male sex 121 (69.9) Ethnicity Chinese 143 (82.7) Malay 15 (8.7) Indian 8 (4.6) Others 7 (4.0) Etiology of liver disease Hepatitis B 77 (44.5) Hepatitis C 13 (7.5) NASH 17 (9.8) Alcohol-related 10 (5.8) Cryptogenic 15 (8.7) PBC/AIC/PSC 21 (12.1) Other 20 (11.6) First transplant 172 (99.4) Priority listing for 27 (15.6) transplant MELD at listing 35 22 (12.7) 30e34 10 (5.8) 25e29 6 (3.5) 20e24 15 (8.7) 17e19 25 (14.5) 14e16 83 (48.0) <14 12 (6.9) Median MELD at 15 (15e23) listing (IQR)
HCC (n ¼ 79)
Non-HCC (n ¼ 94)
P Value
59 (54e63) 55 (46e59) <.001 73 (92.4) 48 (51.1) <.001 67 7 3 2
(84.8) (8.9) (3.8) (2.5)
76 8 5 5
(80.9) (8.5) (5.3) (5.3)
.77
50 8 11 7 3 0 0 79 2
(63.3) (10.1) (13.9) (8.9) (3.8) (0) (0) (100) (2.5)
27 5 6 3 12 21 20 93 25
(28.7) (5.3) (6.4) (3.2) (12.8) (22.3) (21.) (98.9) (26.6)
<.001
3 2 0 0 4 66 4 15
(3.8) (2.5) (0) (0) (5.1) (83.5) (5.1) (15e15)
19 8 6 15 21 17 8 20
(20.2) <.001* (8.5) (6.4) (16.0) (22.3) (18.1) (8.5) (16e31) <.001
51e61). There was a predominance of male patients (69.9%). The most common etiology of liver disease was hepatitis B (44.5%), followed by cholestatic diseases (12.1%). Nonalcoholic steatohepatitis comprised 9.8% of all cases. The median MELD at listing was 15 (IQR 15e23). Overall, 45.6% of patients had HCC. Comparing patients with and without HCC who were waitlisted, we found that they were significantly older with a median age of 59 versus 55 years (P < .001), of male sex (92.4% vs 51.1%, P < .001), less likely to be associated with a priority transplant (2.5% vs 26.6%, P < .001), and had a lower median MELD score at listing (15 vs 20, P < .001). Etiology of liver disease of patients with HCC was significantly different from those without HCC (P < .001). Waitlist Outcomes
Figure 1 shows the status of the waitlisted patients (as of June 2017) stratified by the year they were waitlisted. Therefore, there were on average, 16.3 candidates added to the waitlist each year. At the time of review, 89 (51.4%) patients had undergone a liver transplant, 68 (39.3%) patients had dropped out of the waiting list, 7 (4.0%) patients were still on the waiting list, and 9 (5.2%) patients had been removed as they did not need a transplant. Comparing the 2 groups: those that received a transplant, and those that dropped out of the waiting list, we found that they were comparable based on demographic data and underlying disease (data not shown). Of the 27 patients listed for a priority transplant, 9 (33.3%) underwent liver transplantation, 15 (55.6%) dropped out due to death, and, 3 (11.1%) were removed due to improvement in medical condition. The median waiting time to transplant was 17.0 weeks (IQR 6.5e43.5), while the median time to dropout was 9.5 weeks (IQR 1e53.5). The median MELD at dropout was higher than that at transplant (25 vs 17, P ¼ .044). Patients with HCC
1.0 <.001
Results expressed as n (%) unless specified. Proportions and medians were compared with the data analyzed with the Pearson chi-square test and Mann-Whitney U test, respectively. Abbreviations: AIC, autoimmune cholangiopathy; HCC, hepatocellular carcinoma; IQR, interquartile range; MELD, model for end-stage liver disease; NASH, nonalcoholic steatohepatitis; PBC, primary biliary cirrhosis; PSC, primary sclerosing cholangitis. *Linear-by-linear association.
Of the 79 patients with HCC, 64 (81.0%) patients received MELD exception points of 15. The remaining patients with HCC had physiologic MELD scores higher than 15. At the time of review, 32 patients (40.5%) had dropped out, 41 patients (51.9%) were transplanted, and 6 patients (7.6%) were still on the waitlist. The proportion of patients with HCC who dropped out was similar to that of patients without HCC (P ¼ 1.0). Comparing patients with HCC who were transplanted with those that dropped out, we found that both groups were similar in terms of factors that would affect their likelihood of transplant, such as priority status, MELD score, and whether it was a salvage transplant (Table 2). Tumor characteristics such as serum alphafetoprotein (AFP), number of HCC nodules, and size of largest nodule were similar between both groups. The dropout group, however, was more likely to have received bridging therapy for HCC while on the waitlist (58.1% vs 31.7%, P ¼ .03). The most common reason for dropout was progression of HCC (62.5%), followed by death while on
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Fig 1. Patient status by year entered into waitlist from December 2005 - June 2016 at closure of study in June 2017.
Table 2. Characteristics of Waitlisted Patients With HCC Characteristic
Median age, years (IQR) Male sex Ethnicity Chinese Malay Indian Others Priority listing for transplant Median MELD at listing (IQR) Median MELD at transplant/dropout (IQR) Median AFP (ng/mL) Number of nodules 0 1 2 3 Size of largest HCC nodule, mm (IQR) Salvage transplant Bridging therapy while on waiting list Time to transplant/dropout, weeks (IQR) Cause of dropout Cancer progression Death Medically unsuitable
Transplanted (n ¼ 41)
Dropout (n ¼ 32)
P Value
60 (54.5e63) 58.5 (54e63.75) 37 (90.2) 30 (93.8)
.89 .69
34 5 1 1 1 15 15
.72
(82.9) (12.2) (2.4) (2.4) (2.4) (15e15) (15e17)
7.1 (0.8e708) 16 18 5 2 9
(39.0) (43.9) (12.2) (4.9) (0e22.5)
27 2 2 1 1 15 15
(84.4) (6.2) (6.2) (3.1) (3.1) (15e15) (15e18)
1.0 .35 .58
7.3 (1.3e3095)
.78
6 21 3 2 14.5
(18.8) (65.6) (9.4) (6.3) (6.5e24.3)
*.281
.20
14 (34.1) 13 (31.7)
11 (35.5) 18 (58.1)
24 (10e49)
32 (9.3e84.8)
.34
20 (62.5) 7 (21.9) 5 (15.6)
NA
NA
the waiting list (21.9%). Five patients (15.6%) were deemed medically too ill for transplant and removed from the list.
1.0 .03
Results expressed as n (%) unless specified. Proportions and medians were compared with the use of the Pearson chi-square test and Mann-Whitney U test, respectively. Abbreviations: AFP, alpha-fetoprotein; HCC, hepatocellular carcinoma; IQR, interquartile range; NA, not applicable. *Linear-by-linear association.
Dropout Analyses
Using the CICR method, the cumulative incidence of dropout at 3 months and 1 year was 21% (95% confidence interval [CI]: 16%e28%) and 29% (95% CI: 23%e37%), respectively. The cumulative incidence of transplant at 3 months and 1 year was 20% (95% CI: 15%e27%) and 42% (95% CI: 35%e50%), respectively (Fig 2A). For patients with HCC, the cumulative incidence of dropout was 13% (95% CI: 7%e23%) and 22% (95% CI: 14%e33%) at 3 months and 1 year, while the cumulative incidence of transplant was 16% (95% CI: 10%e27%) and 41% (95% CI: 31%e53%) at 3 months and 1 year (Fig 2B). For patients without HCC, the cumulative incidence of dropout was 29% (95% CI: 21%e39%) and 36% (95% CI: 28% e47%) at 3 months and 1 year, while the cumulative incidence of transplant was 23% (95% CI: 16%e34%) and 44% (95% CI: 35%e55%) at 3 months and 1 year (Fig 2C). We segregated patients with HCC who were listed using MELD exception points (15 points) and compared their cumulative incidence of dropout over time with patients who were listed based on their physiologic MELD (Fig 3). There were 63 patients (36.4%) in the HCC group listed using MELD exception points, and 110 patients (63.6%) using physiologic MELD scores. The cumulative incidence of dropout of HCC patients was 11% (95% CI: 5%e22%) at 3 months. In contrast, the cumulative incidence of dropout of waitlisted patients with MELD score of 14e16 (n ¼ 20) was 7% (95% CI: 1%e47%) while that of MELD scores 17e19 (n ¼ 25) was 16% (95% CI: 7%e39%). At 1 year, the cumulative risks of drop out for patients with HCC patients,
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Fig 2. (A) Likelihood of dropout and transplant over time. (B) Cumulative incidences of events in patients with HCC. (C) Cumulative incidences of events in patients without HCC. Abbreviation: HCC, hepatocellular carcinoma.
MELD 14e16, and MELD 17e19, were 22% (95% CI: 14% e35%), 29% (95% CI: 12%e65%), and 24% (95% CI: 12% e48%), respectively. Thus, the cumulative incidence of dropout of these patients with HCC with MELD exception points did not exceed that of MELD 17e19 even up to 1 year. DISCUSSION
The liver transplantation scene in Singapore is small, however, our center continues to see a steady stream of referrals annually. The volume of cases limits the depth of analysis in our study here. Nevertheless, analysis of the waiting list reveals disease patterns and trends, of which HCC continues to be a major indication for transplantation in Singapore. The main etiology of liver disease remains to be hepatitis B. This is consistent with the disease epidemiology in
Singapore [15]. Alcoholic liver disease, autoimmune hepatitis, primary biliary cirrhosis, and sclerosing cholangitis were rare indications for deceased donor liver transplant. Patients who had HCC tended to be older (P < .001), and of the male sex (P < .001). There were no significant differences in the sex and ethnicity in the transplant or dropout groups. The glaring issue is a 39.3% dropout while on the waiting list. Patients had a higher median MELD at the time of dropout than at initial listing. This meant that they accumulated physiological MELD points, but no organs were available despite moving up on the waiting list. For patients who were listed for a priority transplant, only 33.3% of them successfully underwent a transplant, while 55.6% of them died without a transplant. Next, we observed that, of the patients with HCC waitlisted who dropped out, about half of them (62.5%) dropped out due to progression of HCC.
MODEL FOR END-STAGE LIVER DISEASE EXCEPTION POINTS
Fig 3. Risk of dropout: patients with HCC on MELD exception points versus patients listed on physiological MELD (stratified by MELD score). Abbreviations: HCC, hepatocellular carcinoma; MELD, Model for End-Stage Liver Disease.
Waitlisted candidates for a salvage liver transplant did not have higher dropout rates compared to those waitlisted for a primary liver transplant (P ¼ 1.0). Thus, patients who are candidates for both should consider resection first, since there is limited availability of deceased donor organs [16,17]. The finding that the likelihood of dropout was associated with bridging therapy for HCC while on the waitlist does not necessarily mean that bridging is not a good strategy for patients with HCC within UCSF criteria. It is recommended that bridging therapy for HCC is advised if the waiting time is more than 6 months [18]. This observation is another reflection of the overarching problem of organ shortage hereddespite being bridged in order to “buy time,” they may still not be allocated a liver. The MELD score continues to be a useful tool in the allocation of available liver grafts [19]. Those with the highest MELD had the highest cumulative risk of dropout at 3 months while those with lower MELDs had lower dropout risk while on the waitlist and this is clearly shown in Fig 3. Due to our population size that directly affects the paucity of patients listed for transplantation, we had to group patients into meaningful MELD categories to perform the analysis. Since the primary focus was the HCC MELD of 15, we used a bracketing technique to group those with MELD 14e16 together as the lower bracket, and MELD 17e19 as the higher bracket. The remaining patients on physiological MELDs were grouped at increments of 5. We found that patients with HCC and who were listed based on MELD exception points (15 points) had a 3 month risk of dropout that was higher than those with a physiological MELD score of 14e16, but less than that of 17e19. We may interpret this as HCC patients within transplant criteria at our center “behave” as if they have a physiological MELD greater than those with a MELD of 14e16, yet less than those with a MELD of 17e19. In addition, we observed that
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the cumulative risk of dropout of these patients with HCC did not increase at an increasing rate compared to those of a higher MELD. The graph shows that the interpolated line for these patients with HCC does not cross and exceed that of the next higher MELD category, that is, MELD 17e19. This data suggests that incremental points do not need to be given over time while on the waitlist. While the “true” exception MELD score for HCC was not elucidated in this study, this is supportive evidence that the current system of 15 exception points is marginally lower than what it should be. In addition, the data shows that the dropout rate of these patients with HCC do not increase over time. This implies that these patients in our population should not receive incremental MELD exception points over time while on the waitlist, contrary to the current MELD exception points system practiced in the United States. As this study only encompasses data from 1 of the 2 academic transplant centers in Singapore, representing approximately half of the overall national deceased donor liver transplant volume, we expect that with the complete national data, we may be able to find the exact equipoise of MELD exception points to be assigned for patients with HCC waiting for liver transplant in Singapore. This study also confirms the relevance of ongoing and periodic review of policies pertaining to the allocation of MELD exception points, as has been best demonstrated by the evolving policies of the Organ Procurement and Transplantation Network. CONCLUSION
End-stage liver disease remains an important disease in the region. Unfortunately, there is a paucity of available deceased donor organs for liver transplantation. Hepatitis B remains the prevalent form of viral hepatitis in the region. HCC comprises almost half of the cases waitlisted for liver transplantation. The proportions of patients who dropout are high at 39%, suggesting there is an urgent need to increase the availability of donor organs. The current policy of allocating 15 MELD exception points (with no increment over time) to patients with HCC within transplant criteria may slightly underestimate the dropout risk of patients with HCC. REFERENCES [1] Low HC, Da Costa M, Prabhakaran K, Kaur M, Wee A, Lim SG, et al. Impact of new legislation on presumed consent on organ donation on liver transplant in Singapore: a preliminary analysis. Transplantation 2006;82:1234e7. [2] Kwek TK, Lew TW, Tan HL, Kong S. The transplantable organ shortage in Singapore: has implementation of presumed consent to organ donation made a difference? Ann Acad Med Singapore 2009;38:346e8. [3] Goh GB, Chang PE, Tan CK. Changing epidemiology of hepatocellular carcinoma in Asia. Best Pract Res Clin Gastroenterol 2015;29:919e28. [4] Wald C, Russo MW, Heimbach JK, Hussain HK, Pomfret EA, Bruix J. New OPTN/UNOS policy for liver transplant allocation: standardization of liver imaging, diagnosis, classification,
3570 and reporting of hepatocellular carcinoma. Radiology 2013;266: 376e82. [5] Bhat M, Ghali P, Dupont B, Hilzenrat R, Tazari M, Roy A, et al. Proposal of a novel MELD exception point system for hepatocellular carcinoma based on tumor characteristics and dynamics. J Hepatol 2017;66:374e81. [6] De Carlis L, Di Sandro S, Centonze L, Lauterio A, Buscemi V, De Carlis R, et al. Liver-allocation policies for patients affected by HCC in Europe. Curr Transplant Rep 2016;3:313e8. [7] Alcorn JB. United Network for Organ Sharing: Changes to OPTN bylaws and policies from actions at November board of directors meeting. 2014. [8] Toso C, Mazzaferro V, Bruix J, Freeman R, Mentha G, Majno P. Toward a better liver graft allocation that accounts for candidates with and without hepatocellular carcinoma. Am J Transplant 2014;14:2221e7. [9] Organ Procurement and Transplantation Network. Revised liver policy regarding HCC exception scores. https://optn.transplant. hrsa.gov/news/revised-liver-policy-regarding-hcc-exception-scores/; 2015 [accessed date]. [10] Yao FY, Ferrell L, Bass NM, Watson JJ, Bacchetti P, Venook A, et al. Liver transplantation for hepatocellular carcinoma: expansion of the tumor size limits does not adversely impact survival. Hepatology 2001;33:1394e403. [11] Merion RM, Schaubel DE, Dykstra DM, Freeman RB, Port FK, Wolfe RA. The survival benefit of liver transplantation. Am J Transplant 2005;5:307e13. [12] Li HY, Wei YG, Yan LN, Li B. Salvage liver transplantation in the treatment of hepatocellular carcinoma: a meta-analysis. World J Gastroenterol 2012;18:2415e22.
TAN, GOH, LEE ET AL [13] Toso C, Dupuis-Lozeron E, Majno P, Berney T, Kneteman NM, Perneger T, et al. A model for dropout assessment of candidates with or without hepatocellular carcinoma on a common liver transplant waiting list. Hepatology 2012;56:149e56. [14] Verduijn M, Grootendorst DC, Dekker FW, Jager KJ, le Cessie S. The analysis of competing events like cause-specific mortalitydbeware of the Kaplan-Meier method. Nephrol Dial Transplant 2011;26:56e61. [15] Hong WW, Ang LW, Cutter JL, James L, Chew SK, Goh KT. Changing seroprevalence of hepatitis B virus markers of adults in Singapore. Ann Acad Med Singapore 2010;39: 591e8. [16] Poon RT, Fan ST, Lo CM, Liu CL, Wong J. Long-term survival and pattern of recurrence after resection of small hepatocellular carcinoma in patients with preserved liver function: implications for a strategy of salvage transplantation. Ann Surg 2002;235: 373e82. [17] Adam R, Azoulay D, Castaing D, Eshkenazy R, Pascal G, Hashizume K, et al. Liver resection as a bridge to transplantation for hepatocellular carcinoma on cirrhosis: a reasonable strategy? Ann Surg 2003;238:508e18. discussion 518-509. [18] Llovet JM, Mas X, Aponte JJ, Fuster J, Navasa M, Christensen E, et al. Cost effectiveness of adjuvant therapy for hepatocellular carcinoma during the waiting list for liver transplantation. Gut 2002;50:123e8. [19] Wiesner R, Edwards E, Freeman R, Harper A, Kim R, Kamath P, et al. Model for end-stage liver disease (MELD) and allocation of donor livers. Gastroenterology 2003;124:91e6.