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Original Clinical Science—Liver

Liver Transplantation in Cryptogenic Cirrhosis

Outcome Comparisons Between NASH, Alcoholic, and AIH Cirrhosis

Thuluvath, Paul Joseph MD, FRCP1,2; Hanish, Steven MD2; Savva, Yulia PhD1

Author Information
doi: 10.1097/TP.0000000000002030

Cryptogenic cirrhosis (CC) is a diagnosis of exclusion when there is no other known identifiable etiology.1 Although it has been suggested that many patients with CC may have evolved from nonalcoholic steatohepatitis (NASH), autoimmune hepatitis (AIH), or occult alcoholism, we believe that most patients currently listed as CC have truly unknown liver disease.2-10 The listing diagnosis in United Network for Organ Sharing (UNOS) database suggests that the number of patients with CC has decreased since 2000, whereas those with NASH cirrhosis have increased.11-13 During the study period, from 2002 to 2016, patients with a listing diagnosis of NASH increased from 1% to 16%, whereas CC declined from 8% to 4%, stabilizing at that level by 2011, raising a suspicion that some patients with NASH were listed as CC during the early part of the study period. A significant number of patients are currently being listed for liver transplantation (LT) with UNOS (400-600 per year) and the European LT registry (~4%) with a diagnosis of CC.11-14 We believe that it is important to maintain CC as a separate entity when outcomes are reported, and not combine CC and NASH cirrhosis because these 2 groups may have different natural history and post-LT outcomes.11,15,16

There have been few small single center studies that had examined the p ost-LT outcomes of CC, and these studies have reported discordant outcomes.17-21 Although some studies have indicated worse outcomes in CC compared to other indications,21 others have reported better outcomes. Small sample size, unadjusted for multiple confounders, could easily explain these conflicting results. The objective of our study was to examine the post-LT outcomes of CC, using UNOS data sets, and to compare them with cirrhosis from NASH, alcohol and AIH. It has been previously suggested that some patients with CC may have evolved from NASH, occult alcoholism (alcoholic cirrhosis, AC) or AIH, and hence we compared CC with these disease groups.

MATERIALS AND METHODS

We analyzed the UNOS database from February 27, 2002, to September 30, 2016, for all adults (≥18 years) who received their first liver transplant. We selected 2002 since the UNOS introduced Model for End-Stage Liver Disease (MELD) scores for organ allocation in February 2002, and we assumed that the data collection may have improved since then, and additionally, examination of the annual data variability by diagnosis code showed that the data collection was perhaps done more systematically since 2002. The 4 groups were defined based on their primary diagnosis at the time of the first transplant. For a minority of patients, the diagnosis had changed from the time of listing to the time of transplant, but we did not account for this change while defining our groups since the number of patients with a change in primary diagnosis was a very small, and we felt that it would have no impact on the study findings.

During the study period, 4346 patients with CC, 6075 with NASH, 10675 with AC and 1733 with AIH were transplanted (Table 1). About 2.9% to 5.5% had retransplantation, 4.1% to 9.9% had multiorgan transplantation, and 13.4% to 23.8% had hepatocellular carcinoma (HCC). HCC was present in 741 CC, 1448 NASH, 1944 AC, and 232 AIH. After excluding the patients with multiple-organ transplant and HCC, and keeping only first transplant data (for those who received retransplantation), our study included 3241 recipients with CC, 4089 transplanted individuals with NASH, 7837 with AC, and 1435 with AIH. The demographic and clinical characteristics of these patients are shown in Table 1.

TABLE 1
TABLE 1:
No. patients included in the study

We collected following potential risk factors and confounders at the time of the transplant including race, age, gender, body mass index (BMI), MELD score at transplant, diabetes mellitus (DM), serum creatinine, albumin, and functional status (Karnofsky Performance Status [KPS] score). Based on the KPS score at the time of transplant, we grouped patients into 3 groups: severely disabled if KPS score was between 10% (moribund) and 30% (severely disabled), mild to moderate disability if KPS score was 40% to 60%, and minimal or no disability if KPS score was 70% and above. For the purpose of this study, we compared those who are severely disabled (30% or less on KPS score) with those with KPS score 40% and above. The functional status was recorded by KPS score in most patients, but in some, it was scored as level 1, 2, or 3 (performing activities of daily living with no assistance [level 1], with some assistance [level 2], and with total assistance [level 3]). We combined “level 3” with those with KPS score 30% or less. We also collected data on the prevalence of complications of cirrhosis including ascites, encephalopathy, portal vein thrombosis or renal dialysis. We also collected data for causes of death and summarized them into groups as numerous codes were used to report cause of death. For example, graft failure could be from acute arterial thrombosis, acute or chronic rejection or rarely biliary complications. For infection, we combined viral and bacterial infections, and uncommon causes were grouped under “others’.

STATISTICAL ANALYSIS

The descriptive statistics was presented for all 4 groups. The differences between the groups were tested by using logistic regressions for categorical variables, and 2-sample t tests for continuous variables. Although several continuous variables were not normally distributed, considering a large sample size, t tests were used. The differences in causes of death between the 4 groups were tested by using χ2 tests.

For the analysis of graft survival, recipients were followed up until graft loss or death (whichever came first). Lost-to-follow-up patients were censored at the time of the last follow-up. Kaplan-Meier estimator was used to construct survival curves for the 4 groups followed by a nonparametric log-rank test to assess the equality of survival functions among the groups. Cox proportional hazard regressions were used to study the association between the risk factors, including demographic variables, KPS, complications of cirrhosis, and primary diagnosis, and graft or patient survival. For this we used univariate Cox regressions to identify potential risk factors and included the significant covariates (at P < 0.1) in multivariate Cox regression to estimate the hazard ratios (HR) adjusted for the other covariates.

RESULTS

There were significant demographic differences among the groups as shown in Table 2. Patients with AIH were predominantly women and those with AC were mostly men. Patients with AIH were younger than other groups and had a relatively higher proportion of blacks. Diabetes and obesity were more common in NASH. There were differences in KPS status as well with relatively lower proportion of patients with KPS score of 30% or less in CC group. Portal vein thrombosis was lowest in AC and highest in NASH, and dialysis was less common in AIH and CC.

TABLE 2
TABLE 2:
Demographics and clinical characteristics of patients after excluding HCC and multiorgan transplantation

Despite many differences in demographic and clinical characteristics, graft and patient survival probabilities derived from Kaplan-Meier survival estimates were similar (log rank-test for graft, P = 0.49; patient, P = 0.28) in all 4 groups (Table 3). Kaplan Meier survival curves also showed similar graft (Figure 1) and patient survival (Figure 2) except for a trend toward a better survival in AIH group. AIH group had higher (N = 87, 6.1%) retransplantation rates compared with CC (N = 164, 5.1%), NASH (N = 149, 3.6%) or AC (N = 303, 3.9%). Based on the above analyses, 25% of the grafts will fail at 4.4 years in CC, 5 years in NASH, and 5.1 years in AC and 4.9 years in AIH groups. Similarly, 25% of patients will die at 5.6 years in CC, 5.7 years in NASH, 5.8 years in AC and 6.7 years in AIH groups.

TABLE 3
TABLE 3:
Graft and patient survival
FIGURE 1
FIGURE 1:
Kaplan-Meier graft survival.
FIGURE 2
FIGURE 2:
Kaplan-Meier patient survival.

Considering that several studies had reclassified CC patients with BMI above 30 as NASH patients, we did a sensitivity analysis of CC patients with BMI of 30 or less and greater than 30 and compared them with NASH. This analysis confirmed that there were no significant differences for patient (P = 0.55) and graft (P = 0.19) survival probabilities between the 3 groups (Figure S1, S2 and Table S1, SDC,http://links.lww.com/TP/B509). In addition, we compared the survival of CC and NASH patients transplanted between 2012 and 2015 since the listing diagnosis with CC stabilized during this period. This also confirmed that there are no survival differences between CC and NASH (Figure S3, S4, SDC,http://links.lww.com/TP/B509).

The causes of death are shown in Table 4. In 16.2% to 20.8% of patients, the cause of death was not known or missing. The most common causes of death were infection, cardiovascular events, multiorgan failure, graft failure, and malignancy. In 5.1% to 6.7%, death was attributed to pulmonary embolism. Many uncommon causes of death were combined together as “others.” The only significant differences among the group were noted in graft failure, multi organ failure and suicides. Graft failure as a cause of death was most common in AIH and lowest in NASH. Multiorgan failure was lowest in AC, but suicide rates were higher in AC (Table 4).

TABLE 4
TABLE 4:
Causes of death

Univariate and multivariate Cox regression analysis for graft and patient survival is shown in Tables 5 and 6. Older age, male sex, severe disability (KPS score of 30% or less), presence of hepatic encephalopathy (HE) or portal vein thrombosis, and being on dialysis were negative predictors of survival on multivariate analysis for both graft and patient survival. Those with severe disability as defined by KPS scores had 33% higher risk of death after adjusting for all other risk factors. Hispanics had better graft and patient survival (24% reduction in risk of death compared with whites) on multivariate analysis. Presence of DM was associated with lower patient survival on multivariate analysis, and BMI had only marginal effect in these combined cohorts. Interestingly, when adjusted for other confounders, MELD score was not a predictor of patient survival.

TABLE 5
TABLE 5:
Cox regressions for the graft survival after the first transplant
TABLE 6
TABLE 6:
Cox regressions for the patient survival after the first transplant

The diagnosis had no association with graft or patient survival when adjusted for other confounders on multivariate analysis.

DISCUSSION

This study, using a large data set from UNOS, showed that those with CC have similar graft and patient survival as those with NASH, AC, and AIH despite many differences in their clinical characteristics. In addition to the well-known risk factors for poor survival,22-26 we found that Hispanics have 24% lower risk of death (HR, 0.76) when compared with whites. Although the presence of DM was associated with a lower survival, patients with NASH had similar graft and patient survival as the other 3 groups. We also found that the presence of moderate to severe HE or portal vein thrombosis decreased graft and patient survival independent of other comorbidities and risk factors. One of the most important predictors of poor graft and patient survival was poor KPS score (30% or less) at the time of LT with a 33% higher risk of death (HR, 1.33) in that group after adjusting for all other confounders.

There have been few small single-center studies that had examined the liver transplant outcomes in CC.17-21 Although an earlier study from Mayo Clinic in 39 patients with CC reported 1-year and 5-year survivals of 72% and 58%, respectively,17 3 other single-center studies (total number of 172 patients) have reported favorable outcomes.18-20 Except 1 study, all these studies were done before NASH cirrhosis was established as a distinct entity, and therefore may have included many patients with NASH in the CC group. To our knowledge, our study is the most comprehensive examination of liver transplant outcomes in those with CC, and we believe that this information is important for one main reason. We recently have suggested that CC, listed with UNOS since 2002, is probably distinct from NASH based on their clinical characteristics (Table 2). In recent studies, investigators have combined CC with NASH, especially those CC who are obese,11,15,16 and we do not feel it is justified and suggest that the outcomes of CC are reported separately. We had hypothesized that CC patients may have different outcomes compared to NASH, AC or AIH. Our results, however, suggest that those with CC have similar outcomes as compared to other groups even after adjusting for the known confounders. Moreover, when CC patients with BMI less than 30 were compared with those CC patients with BMI more than 30 or NASH, there were no differences in graft or patient survival between the 3 groups. This is reassuring and indicates that because of the technological advances in the past 2 decades in liver transplant surgery, anesthesia and critical care, outcomes are less likely to be influenced by the comorbidities in this population.

When causes of death are reported, there were no major differences among the groups. There were higher suicides among AC, but the numbers were very small (15 of 7837 recipients). Graft failures were more common in AIH, and perhaps, this was an expected observation. Interestingly, multiorgan failures were lowest in AC.

One of the interesting findings of this study is better survival in Hispanics. Previously, we and others had suggested that blacks had lower adjusted graft and patient survival.23 With regard to Hispanics in the United States, it has been suggested that Hispanics were less likely to be listed, have a lower waitlist mortality but more likely to be removed from the waitlist, less likely to receive transplant or more likely to receive poor quality organs.27-29 Despite these potential disadvantages, our study shows that they have the best outcomes in these combined cohorts. Although one study had suggested that whites and Hispanics had similar outcomes after LT,30 in another study, Hispanics had better survival rates despite receiving poor quality donor graft.29 In patients with HCC, Surveillance, Epidemiology and End Results database showed that Hispanics had the best outcomes.30 Our study confirms previous observations of better post-LT survival in Hispanics.29,31 Although it is possible that Hispanics had more rigorous pretransplant evaluation, and possibly higher nonlisting or removal rates, our observations in this large data set merit further research to better understand the reasons for better survival in Hispanics despite all the disadvantages.

Some studies had suggested that portal vein thrombosis does not influence waitlist mortality or liver transplant outcomes,32,33 but our study clearly shows that it is an independent predictor of survival after LT, and corroborates previous UNOS data analysis results.34-36

HE is not a component of MELD, but had been used previously as part of Child-Pugh score for organ allocation. Covert HE is associated with higher mortality, and HE is also associated with a higher waitlist mortality and 1-year post-LT mortality.37,38 In this study, the presence of HE was an independent predictor of survival.39 It is possible that HE is a surrogate marker of lower muscle mass (sarcopenia) or intestinal dysbiosis. This is also an area we should explore further.

KPS score has been shown to be a predictor for waiting list mortality40 and postdischarge mortality in hospitalized patients with cirrhosis.41 In our study, patients with severely disability at the time of transplant (KPS score 30% or less) had 33% higher risk of death after adjusting for all other risk factors, and our observations confirm the findings of a previous report on KPS score and short-term post-LT mortality.42

There are few limitations with our study, and it is mostly because of lack of granularity in the UNOS datasets regarding some important variables, such as components of metabolic syndrome and other cardiovascular risk factors, and causes of graft loss. These are inherent problems of large administrative datasets, but the strength is large sample size that allowed to adjust for many confounders and ability to report real-life outcomes from all transplant centers in the United States.

In summary, we have shown that patients with CC are clinically distinct from NASH, AC, or AIH, but they have similar short and long-term survival. Survival is dependent on many factors including performance status at the time of transplant as determined by KPS scores.

REFERENCES

1. Greeve M, Ferrell L, Kim M, et al. Cirrhosis of undefined pathogenesis: absence of evidence for unknown viruses or autoimmune processes. Hepatology. 1993;17:593–598.
2. Poonawala A, Nair SP, Thuluvath PJ. Prevalence of obesity and diabetes in patients with cryptogenic cirrhosis: a case-control study. Hepatology. 2000;32:689–692.
3. Caldwell SH, Oelsner DH, Iezzoni JC, et al. Cryptogenic cirrhosis: clinical characterization and risk factors for underlying disease. Hepatology. 1999;29:664–669.
4. Ayata G, Gordon FD, Lewis WD, et al. Cryptogenic cirrhosis: clinicopathologic findings at and after liver transplantation. Hum Pathol. 2002;33:1098–1104.
5. Powell EE, Cooksley WG, Hanson R, et al. The natural history of nonalcoholic steatohepatitis: a follow-up study of forty-two patients for up to 21 years. Hepatology. 1990;11:74–80.
6. Hübscher SG. Histological assessment of non-alcoholic fatty liver disease. Histopathology. 2006;49:450–465.
7. Czaja AJ, Carpenter HA, Santrach PJ, et al. The nature and prognosis of severe cryptogenic chronic active hepatitis. Gastroenterology. 1993;104:1755–1761.
8. Kaymakoglu S, Cakaloglu Y, Demir K, et al. Is severe cryptogenic chronic hepatitis similar to autoimmune hepatitis? J Hepatol. 1998;28:78–83.
9. Heringlake S, Schütte A, Flemming P, et al. Presumed cryptogenic liver disease in Germany: high prevalence of autoantibody-negative autoimmune hepatitis, low prevalence of NASH, no evidence for occult viral etiology. Z Gastroenterol. 2009;47:417–423.
10. Duclos-Vallée JC, Yilmaz F, Johanet C, et al. Could post-liver transplantation course be helpful for the diagnosis of so called cryptogenic cirrhosis? Clin Transplant. 2005;19:591–599.
11. Charlton MR, Burns JM, Pedersen RA, et al. Frequency and outcomes of liver transplantation for nonalcoholic steatohepatitis in the United States. Gastroenterology. 2011;141:1249–1253.
12. Wong RJ, Aguilar M, Cheung R, et al. Nonalcoholic steatohepatitis is the second leading etiology of liver disease among adults awaiting liver transplantation in the United States. Gastroenterology. 2015;148:547–555.
13. Kim WR, Lake JR, Smith JM, et al. OPTN/SRTR 2013 annual data report: liver. Am J Transplant. 2015;15:1–28. 22.
14. Adam R, Karam V, Delvart V, et al. Evolution of indications and results of liver transplantation in Europe. A report from the European Liver Transplant Registry (ELTR). J Hepatol. 2012;57:675–688.
15. Younossi ZM, Otgonsuren M, Henry L, et al. Association of nonalcoholic fatty liver disease (NAFLD) with hepatocellular carcinoma (HCC) in the United States from 2004 to 2009. Hepatology. 2015;62:1723–1730.
16. Wong RJ, Cheung R, Ahmed A. Nonalcoholic steatohepatitis is the most rapidly growing indication for liver transplantation in patients with hepatocellular carcinoma in the US. Hepatology. 2014;59:2188–2195.
17. Charlton MR, Kondo M, Roberts SK, et al. Liver transplantation for cryptogenic cirrhosis. Liver Transpl Surg. 1997;3:359–364.
18. Heneghan MA, Zolfino T, Muiesan P, et al. An evaluation of long-term outcomes after liver transplantation for cryptogenic cirrhosis. Liver Transpl. 2003;9:921–928.
19. Sanjeevi A, Lyden E, Sunderman B, et al. Outcomes of liver transplantation for cryptogenic cirrhosis: a single-center study of 71 patients. Transplant Proc. 2003;35:2977–2980.
20. Masior Ł, Grąt M, Krasnodębski M, et al. Liver transplantation in patients with cryptogenic cirrhosis provides excellent long-term outcome. Ann Transplant. 2016;21:160–166.
21. Álamo JM, Bernal C, Barrera L, et al. Liver transplantation in patients with cryptogenic cirrhosis: long-term follow-up. Transplant Proc. 2011;43:2230–2232.
22. John PR, Thuluvath PJ. Outcome of liver transplantation in patients with diabetes mellitus: a case control study. Hepatology. 2001;34:889–895.
23. Nair S, Eustace J, Thuluvath PJ. Effect of race on outcome of orthotopic liver transplantation: a cohort study. Lancet. 2002;359:287–293.
24. Nair S, Verma S, Thuluvath PJ. Obesity and its effect on survival in patients undergoing orthotopic liver transplantation in the United States. Hepatology. 2002;35:105–109.
25. Nair S, Verma S, Thuluvath PJ. Pretransplant renal function predicts survival in patients undergoing orthotopic liver transplantation. Hepatology. 2002;35:1179–1185.
26. Yoo HY, Thuluvath PJ. The effect of insulin-dependent diabetes mellitus on outcome of liver transplantation. Transplantation. 2002;74:1007–1012.
27. Volk ML, Choi H, Warren GJ, et al. Geographic variation in organ availability is responsible for disparities in liver transplantation between Hispanics and Caucasians. Am J Transplant. 2009;9:2113–2118.
28. Ahn J, Liu B, Bhuket T, et al. Race/ethnicity-specific outcomes among chronic hepatitis C virus patients listed for liver transplantation. Dig Dis Sci. 2017;62:1051–1057.
29. Mathur AK, Schaubel DE, Zhang H, et al. Disparities in liver transplantation: the association between donor quality and recipient race/ethnicity and sex. Transplantation. 2014;97:862–869.
30. Quillin RC 3rd, Wilson GC, Wima K, et al. Independent effect of black recipient race on short-term outcomes after liver transplantation. Surgery. 2015;157:774–784.
31. Ananthakrishnan AN, Saeian K. Racial differences in liver transplantation outcomes in the MELD era. Am J Gastroenterol. 2008;103:901–910.
32. John BV, Konjeti R, Aggarwal A, et al. Impact of untreated portal vein thrombosis on pre and post liver transplant outcomes in cirrhosis. Ann Hepatol. 2013;12:952–958.
33. Karvellas CJ, Cardoso FS, Senzolo M, et al. Clinical impact of portal vein thrombosis prior to liver transplantation: a retrospective cohort study. Ann Hepatol. 2017;16:236–436.
34. Ghabril M, Agarwal S, Lacerda M, et al. Portal vein thrombosis is a risk factor for poor early outcomes after liver transplantation: analysis of risk factors and outcomes for portal vein thrombosis in waitlisted patients. Transplantation. 2016;100:126–133.
35. Englesbe MJ, Schaubel DE, Cai S, et al. Portal vein thrombosis and liver transplant survival benefit. Liver Transpl. 2010;16:999–1005.
36. Montenovo MI, Rahnemai-Azar A, Reyes J, et al. Clinical impact and risk factors of portal vein thrombosis for patients on wait list for liver transplant. Exp Clin Transplant. 2017. DOI:10.6002/ect 2016.0277.
37. Patidar KR, Thacker LR, Wade JB, et al. Covert hepatic encephalopathy is independently associated with poor survival and increased risk of hospitalization. Am J Gastroenterol. 2014;109:1757–1763.
38. Wong RJ, Gish RG, Ahmed A. Hepatic encephalopathy is associated with significantly increased mortality among patients awaiting liver transplantation. Liver Transpl. 2014;20:1454–1461.
39. Wong RJ, Aguilar M, Gish RG, et al. The impact of pretransplant hepatic encephalopathy on survival following liver transplantation. Liver Transpl. 2015;21:873–880.
40. Orman ES, Ghabril M, Chalasani N. Poor performance status is associated with increased mortality in patients with cirrhosis. Clin Gastroenterol Hepatol. 2016;14:1189–1195.
41. Tandon P, Reddy KR, O'Leary JG, et al. A Karnofsky Performance Status-based score predicts death after hospital discharge in patients with cirrhosis. Hepatology. 2017;65:217–224.
42. Dolgin NH, Martins PN, Movahedi B, et al. Functional status predicts postoperative mortality after liver transplantation. Clin Transplant. 2016;30:1403–1410.

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