MELD scoring in chronic liver disease

1. MELD scoring
By – Dr. Rohit K. Saini
Moderator – Dr. Neha Garg

2. Pre MELD era
• In early 1990s, there was no priority-setting policy.
• Waiting time was the main criterion for allocating the graft.
• UNOS (1998) - integrate CTP classification to assess the
urgency of LT.
• classifies into three groups: A, B and C a/w 100%, 80% and
45% one-year mortality, respectively.
• Several limitations
• Abandoned

3. Pre MELD era
Categories for liver allocation :
• Status 1 patients priority for liver allocation over all patients
with CLD.
1. ALF/FHF or
2. primary graft dysfunction or HAT within 1st week post Tx, or
3. pediatric patients who decompensate and require
continuous care in ICU.
• Patients with CLD were ranked as status 2A, 2B, or 3

4. MELD
• The score was developed in 2000 at Mayo Clinic, first as a
model to predict short-term prognosis following TIPS in CLD in
place of the CTP classification
• MELD is based on 3 biochemical variables, which are readily
available, reproducible, inexpensive, objective: main strength.
9.57 Xlog (creat) + 3.78Xlog (total bil) + 11.2Xlog (INR) + 6.43
• Score range : 6 - 40

5. MELD
• In 2001, Kamath et al showed that MELD also predicted a 3-
month survival in patients with CLD.
• In 2002 (Feb. 27), the MELD score was adopted and approved
by UNOS as a tool for allocating organs to patients waiting for
LT.
• Turning point in the history of LT: “the sickest first” allocation
policy
Kamath PS, et al. Hepatology 2001

6. MELD - Etiology
Initially, the formula for the MELD score is
• 3.8*log(bilirubin) + 11.2*log(INR) + 9.6*log(creatinine) +
6.4*(etiology: 0 if cholestatic or alcoholic, 1 other causes)
• Etiology does not increase predictability.
Kamath PS, Wiesner RH, Malinchoc M, et al. A model to predict survival in patients with
end-stage liver disease. Hepatology 2001

7. Wiesner RH, et al. MELD and PELD: application of survival models to liver allocation.
Liver Transpl 2001 – prospective study
Linear correlation between MELD
score and 3-month survival
AUROC of MELD score and CTP
score: 0.83 vs. 0.76 (p < 0.001)

8. Since 2002, following the implementation of the MELD score
in US, waiting list mortality has decreased by 12%
Asrani SK, Model for end-stage liver disease score and MELD exceptions: 15 years later.
Hepatol Int 2015

9. MELD - limitations
• interlaboratory variability of the components.
• Serum creatinine is also a contested component, as it is
directly related to the patient’s muscle mass.
• Does not cover decompensation state.

11. MELD Na+
• Numerous studies showed that sodium reflects the intensity
of PHTN, as low sodium level is a/w ascites and HRS.
• independent predictor of mortality who are listed for liver Tx
• In 2006, Biggins et al included sodium level
MELD-Na = MELD + 1.59 X (135–Na)
[Na range 135 to 120 mEq/L]
• Evaluated: up to 27% of grafts could be redirected to patients
on the waiting list favored by “MELD Na” (instead of MELD)
Biggins SW, et al. Evidence-based incorporation of serum sodium concentration
into MELD. Gastroenterology 2006

12. MELD Na+
• In 2008, new version of MELD-Na was proposed by Kim et al,
incorporated different sodium levels (125 to 140) and
validates better predicted mortality at 3 months
MELD-Na = MELD Score - Na – [0.025 x MELD x (140-Na)] + 140
• Since January 2016, UNOS began using MELD-Na instead of
the original MELD.
• In 2018, Nagai et al showed significantly lower mortality and
higher transplant probability during the MELD-Na period
Kim WR, et al. N Engl J Med 2008
Nagai S, et al. Gastroenterology 2018

13. Integrated MELD (iMELD)
• Luca et al (2007): integrated MELD or iMELD :
MELD + age (years) X 0.3–0.7 X Na (mmol/L) + 100
• demonstrated its superiority in prediction by improving
AUROC by 13.4% (in TIPS) and 8% (in awaiting LTx).
Luca A, et al. An integrated MELD model including serum sodium and age improves
the prediction of early mortality in patients with cirrhosis. Liver Transpl 2007

14. Integrated MELD (iMELD)
• In 2016, the iMELD score showed superiority in predicting
posttransplant mortality in patients enrolled for liver failure
compared with MELD, MELD-Na, and UK End-Stage Liver
Disease (UKELD) scores
Luca A, et al.. Liver Transpl 2007
Jurado-García J, et al. Impact of MELD allocation system on waiting list and early post-
liver transplant mortality. PLoS One 2016

15. MELD - sarcopenia
• MELD-sarcopenia developed in Canada
• Sarcopenia: L3 SMI: ≤41 cm2/m2 (F), ≤53 cm2/m2 (M) with
BMI ≥25 kg/m2 and ≤43 cm2/m2 (all) with BMI ≤25 kg/m2
• Overall, c-statistics for 3-month mortality were 0.82 for MELD
and 0.85 for MELD-sarcopenia (P=0.1).
• In MELD ≤ 15, c-statistics for 3-month mortality (0.85 vs. 0.69,
P=0.02) and refractory ascites (0.74 vs. 0.71, P=0.01) were
significantly higher for MELD-sarcopenia.
• improved prediction of mortality esp in low MELD patients
MELD +(beta[sarcopenia]/beta[MELD]) × sarcopenia
Montano-Loza AJ, et al. Inclusion of sarcopenia within MELD (MELD-Sarcopenia) and the
prediction of mortality in patients with cirrhosis. Clin Transl Gastroenterol 2015

16. MELD - sarcopenia
• Two major limitations to include sarcopenia in allocation
policy:
1. MELD-sarcopenia: not showed its statistical power to
discriminate patients on the waiting list over MELD
2. no standardized measuring process : even most frequently
used CT scan determination of psoas muscle, presents a large
operator variability
• However, it may be a predictive factor for post transplant
complication and mortality, as Masuda et al showed in LDLT
Van Vugt JLA, et al. J Hepatol 2018
Masuda T, et al. Sarcopenia is a prognostic factor in living donor liver transplantation.
Liver Transpl 2014

17. MELD - gender
• Gender disparity in LT: women higher mortality rate on the
waitlist although women were listed with lower median MELD
scores, compared with men (14 vs. 15, p < 0.001).
• Reason: lower creatinine level in women at same GFR.
• Following introduction of MELD score to LT allocation system,
race was no longer a/w receipt of LT or death on waiting list,
but disparities based on sex remain
Moylan CA, et al. Disparities in liver transplantation before and after introduction of
the MELD score. JAMA 2008

18. Delta MELD
• In 2005, Huo et al prospectively studied delta-MELD score:
AUROC curve for delta-MELD/month (>2.5) was 0.78 and 0.72
for MELD (p = 0.13) at 6months; the area was 0.82 and 0.74,
resp. (p = 0.018) at 12 months.
• Bambha et al failed to show the utility of this score and its
superiority compared with MELD score on a larger cohort to
predict waiting list mortality.
Bambha K, et al. Predicting survival among patients listed for liver transplantation:
an assessment of serial MELD measurements. Am J Transplant 2004

19. Delta MELD - validation
• Eurotransplant registry (2016): analysed nearly 6,000 patients
showed effect of delta-MELD on post Tx survival
• Delta-MELD > 10 showing a 1.6-fold increased risk of death
after transplantation.
• concept of Delta MELD was validated in a large, prospective
data set.
Györi GP, et al; Impact of dynamic changes in MELD score
on survival after liver transplantation - a Eurotransplant
registry analysis. Liver Int 2016

20. Newer biomarkers
Several new biomarkers are correlated with cirrhosis mortality:
• plasma cystatin C
• plasma renin
• plasma von Willebrand factor
not yet been integrated into the MELD or in various current
allocation systems.
Markwardt D, et al. Hepatology 2017
Paternostro R, et al. J Gastroenterol Hepatol 2017
Prasanna KS, et al. Indian J Gastroenterol 2016

21. MELD plus
• Nine variables (MELD-Na’s components + albumin, total
cholesterol, WBC, age and LOS)
• yielded improved levels of discrimination, with AUROCs that
significantly outperformed the traditional scores to predict 90
day mortality.
• Several limitations
Kartoun U, et al. The MELD-Plus: a generalizable prediction risk score in cirrhosis.
PLoS One 2017

22. UKELD
• In 2008, UK set up its own allocation system derived from
MELD to ensure equity: the UKELD score.
5 X [1.5 X (INR) + 0.3 X (creat) + 0.6 X (bil) – 13 X (Na) + 70
• score was validated retrospectively on a cohort of 1,000
patients
Neuberger J, et al; Liver Advisory Group; UK Blood and Transplant.
Selection of patients for liver transplantation and allocation of donated
livers in the UK. Gut 2008

23. D-MELD
• In 2009, D-MELD score designed to simplify donor/recipient
matching by using recipient’s MELD and donor’s age to stratify
post tx survival.
• range : 40 to 3400.
• Using cutoff D-MELD score of 1600: define a subgroup of
donor–recipient matches with significantly poor post tx
outcomes (by survival and LOS)
Halldorson JB, et al. DMELD, a simple predictor of post liver transplant mortality
for optimization of donor/recipient matching. Am J Transplant 2009

24. D-MELD (donor/recipient matching)
4-year survival: 71.3% vs 63.8% if D-MELD
>1600 (p < 0.0001)
4-year survival: 68.3% vs 56.7% if D-MELD
>1600 (p < 0.0001)
Halldorson JB, et al.. Am J Transplant 2009

25. D-MELD (Etiology)
(p < 0.0001) for all Etiologies
Halldorson JB, et al. DMELD, a simple predictor of post liver transplant mortality for
optimization of donor/recipient matching. Am J Transplant 2009

26.  In this study, D-MELD did not accurately predict postoperative mortality.
• In 2016, study to predict post tx morbidity and survival in low
(<30) and high (>30) MELDs by different prediction models:
1. D-MELD
2. Delta MELD
3. DRI (donor risk index)
4. (SOFT) Survival Outcomes Following Liver Transplant
5. (BAR) Balance-of-risk
6. (UCLA-FRS)University of California Los Angeles–Futility Risk
Score
Schlegel A, et al. Risk assessment in high- and low-MELD liver transplantation. Am J
Transplant 2017

27. In conclusion, the BAR
score was most useful for
risk classification in LT,
based on expected posttx
mortality and morbidity.
Schlegel A, et al. Risk assessment in high- and low-MELD liver
transplantation. Am J Transplant 2017

30. Sharma P, et al. Endstage liver disease candidates at the highest model for end-stage
liver disease scores have higher wait-list mortality than status-1A candidates.
Hepatology 2012
• compared wait-list mortality between each MELD category and
Status1A (ref.) using time-dependent Cox regression
• ESLD with MELD >40 twice wait-list mortality risk with HR 1.96
(P<0.004) and no difference for MELD 36-40, whereas MELD < 36
significantly lower mortality risk compared to Status-1A.
• MELD > 40 similar posttx survival, so should be assigned higher
priority and MELD 36-40 should be assigned similar rather than
sequential priority for allocation.
71%
70%
52%

31. Share 35
• Share 35 policy: implemented in 2013 in US, which means
that regional patients with MELD > 35 had priority over other
local patients with MELD < 35.
• New listings with MELD >35 increased (9.2% to 9.7%, p=0.3),
but proportion of DDLTs allocated to recipients with MELD >35
increased 23.1% to 30.1% (p<0.001).
• The proportion of regional shares increased from 18.9% to
30.4% (p<0.001).
Massie AB, et al. Early changes in liver distribution following implementation of
Share 35. Am J Transplant 2015

32. Share 35
• Waitlist mortality decreased by 30% among patients with
MELD >35 (p<0.001)
• CIT (p=0.8), Posttx LOS (p=0.2) and posttx mortality (p=0.9)
remained unchanged.
Waitlist mortality – pre and post share 35
Massie AB, et al. Early changes in liver
distribution following implementation of
Share 35. Am J Transplant 2015

33. In post–Share 35 era, MELD >35 benefit from access to higher-quality donor
organs, l/t improved posttx survival and MELD <35 received higher-risk organs,
but without compromising posttx outcomes.
Improved 83.9% to 88.4% (P < 0.01)
(P = 0.69) (P = 0.32)
Kwong AJ, et al. Improved posttransplant mortality after share 35 for liver transplantation.
Hepatology 2018

34. MELD – uncapping?
• Nadim et al: compared MELD =40 patients to MELD > 40 and
divided them into three groups (with risk of death within 30
days of registration):
1. MELD 41 to 44 (1.4%)
2. MELD 45 to 49 (2.6%)
3. MELD 50 (5.0%)
• Patients with MELD>40 have significantly greater waitlist
mortality but comparable posttx outcomes (1 and 3 year
survival) to MELD=40 and, should be given priority for LT.
Nadim MK, et al. Inequity in organ allocation for patients awaiting liver transplantation:
rationale for uncapping the model for end-stage liver disease. J Hepatol 2017

35. MELD – uncapping?
• Uncapping MELD will allow more equitable organ distribution
aligned with the principle of prioritizing patients most in
need.
Nadim MK, et al. Inequity in organ allocation for patients awaiting liver transplantation:
rationale for uncapping the model for end-stage liver disease. J Hepatol 2017

36. MELD-Na + Frailty Index
• Frailty concept : allows assessment of patient’s physical
status by scales [Fried frailty, short physical performance
battery, activities of daily living]
• Cirrhosis : muscle wasting, malnutrition and functional decline
causes greater mortality & not quantified by MELDNa score
• In 2017, Lai et al developed frailty index in cirrhotic patients
to predict mortality.
MELD Na + Fraility index
• Frailty index consist of: grip strength, chair stands & balance
Lai JC, et al. Development of a novel frailty index to predictmortality in patientswith
end-stage liver disease. Hepatology 2017

37. MELD-Na + Frailty Index
• Compared with MELD-Na alone, MELD-Na + Frailty Index
correctly reclassified 16% of deaths/delistings (p = 0.005).
• 3-month waitlist mortality risk (i.e. C- statistic) for:
MELD Na – 0.80
fraility index – 0.76
MELD Na + fraility index - 0.82
• improves risk prediction of waitlist mortality over MELDNa
alone.
Lai JC, et al. Development of a novel frailty index to predictmortality in patientswith end-
stage liver disease. Hepatology 2017

39. MELD exceptions
• Exception points: in order to increase waitlist priority to those
whose severity of illness or risk of complications are not
captured by the MELD score.
• Two types of MELD exceptions:
1. Standardized: conditions with sufficient data such as
HCC,HPS or amyloid neuropathy.
2. Nonstandardized: conditions a/w poor quality of life when all
medical treatments have failed, such as recurrent or chronic
encephalopathy or refractory pruritus.
Freeman RB Jr, et al. MELD exception guidelines. Liver Transpl 2006

40. MELD exceptions

41. MELD exceptions - challenges
• Several challenges have emerged:
1. lack of standardization in criteria to approve such exceptions
2. geographic variability
3. approval of such exceptions
4. limited evidence base to support certain exceptions.
Goldberg DS, Standardizing MELD exceptions: current challenges and future
directions. Curr Transplant Rep 2014

42. HCC
• Most common indication for MELD exception points is HCC
(patients within Milan criteria).
• Initially, MELD exception policies over-prioritized by awarding
29 points (Feb 2002–Apr 2003),
• Decreased to 24 points (Apr 2003–Jan 2005), with subsequent
upgrades every 3 months. Revised mortality risk curve
demonstrated that 22 points should be given
• Again changed in Mar 2005: exceptions only for T2 lesions
• Several recent publications: even current policy over-
prioritizes HCC with significantly higher Tx rates compared to
non-exception waitlist population.
•Massie AB, et al. Am J Transplant. 2011.
•Washburn K, et al. Am J Transplant. 2010

43. Schuetz C, et al. HCC patients suffer less
from geographic differences in organ
availability. Am J Transplant 2013
• Overall risk of death decreases by 1% per MELD point (p =
0.65) for HCC, but increases by 7% for non-HCC (p < 0.0001).
• Post tx risk of death decreases by 2% per MELD point (p =
0.28) for HCC, but increases by 3% for non-HCC (p = 0.027)
p < 0.0001
p < 0.005

44. HCC
• The UNOS Committee - two proposed modifications to the
HCC MELD exception policy:
(i) delaying assigning exception points to HCC patients within
Milan criteria for 6 months after approval
(ii) capping the number of HCC MELD exception points at 34
OPTN/UNOS Policy and Bylaw Proposals Distributed for Public Comment.
http://optn.transplant.hrsa.gov/policiesAndBylaws/ publicComment/proposals.asp.
Accessed March 14, 2014

45. New eMELD - HCC
• In US, an update of allocation policy (Oct 2015): putting HCC
patients on hold for 6 months before they obtain their
exceptional points.
• The risk of this policy is progression of HCC during these 6
months
• A delay of 6-9 months would eliminate the geographic
variability in discrepancy between HCC and non-HCC
transplant rates and may allow more equal access to tx.
Heimbach JK, et al. Delayed hepatocellular carcinoma MELD exception score improves
disparity in access to liver transplant in the United States. Hepatology 2015

46. Ishaque T, et al. Liver transplantation and
waitlist mortality for HCC and non-HCC
candidates following the 2015 HCC exception
policy change. Am J Transplant 2019
• compared DDLT rates and waitlist mortality/dropout for HCC
vs non‐HCC before (Oct 2013 to Oct 2015, prepolicy) and after
(Oct 2015 to Oct 2017, postpolicy) using Cox and competing
risks regression.
• Tx rate for HCC remained 2.2 times higher than non-HCC but
decreased compared to prepolicy period (3.69 times).
• The risk of delisting /waitlist mortality was comparable after
the implementation of new policy

47. North Italy : HCC-MELD
• In Bologna, a modified MELD score: included MELD score,
waiting time and tumor stage
• In 2014, a modified MELD score, named HCC-MELD, included
AFP and MELD, was developed by Vitale et al:
HCC-MELD = 1.27 X MELD – 0.51 X logAFP + 4.59
• Many organ sharing organizations in European countries
follows same score.
Ravaioli M, et al. Am J Transplant 2006
Vitale A, et al. J Hepatol 2014

50. At last
• MELD score, although imperfect, is the best graft allocation
system found till date.
• Universal ethical challenge: imbalance between number of
grafts and waitlist for LT.
• lack of uniformity in allocation policies demonstrates inequity
• no perfect prioritization policy
• real-time assessment of waiting list and better models with
more data should be developed in the coming years.