Sarcopenia and gender disparities in liver transplant waiting lists: evaluating predictive scores and delisting risks

Introduction

Prioritizing patients on the liver transplant (LT) waiting list according to the progression of their disease is one of the biggest challenges in the current context of organ shortage. This shortage of grafts significantly lengthens the time to transplantation, resulting in an estimated mortality on the waiting list of around 15% (1). Currently, the most widely used scores for prioritizing patients on the LT list are the model for end-stage liver disease (MELD) score and the model for end-stage liver disease-sodium (MELD-Na). Since its introduction, the MELD score has shown remarkable results in significantly reducing waiting list mortality (2). However, this score has exhibited certain limitations due to the increasing complexity of patient profiles and the evolution of indications. One of those limitations is the excess mortality of women on waiting list, attributed to a lower overall MELD score than men (3), notably because of lower serum creatinine levels (4,5). It should also be noted that MELD does not account for the sarcopenic status of patients on the waiting list, which is relatively common in the cirrhosis patient population (6) and is also recognized as an independent risk factor for mortality on the waiting list (7,8).

In this context, several scores have been developed in an attempt to address these disparities as effectively as possible, with the hope of reducing mortality on the list. There were two possible approaches: on one hand we could be focusing on sarcopenic status and incorporating it into the MELD score, resulting in the MELD-sarcopenia (9). On the other hand, the emphasis could be placed on estimating renal function, as renal dysfunction is the main source of mortality for patients on the waiting list (10). This has led to the emergence of various scores: the MELD with glomerular filtration rate assessment in liver disease (MELD-GRAIL) and the MELD with glomerular filtration rate assessment in liver disease-sodium (MELD-GRAIL-Na) (11), and more recently the gender equity model for liver allocation (GEMA) and the gender equity model for liver allocation-sodium (GEMA-Na) (12).

The main objective of this study is to compare these various scores to confirm the superiority of the GEMA model in predicting 90-day de-listing, considering the heightened mortality risk in women. Additionally, the study aims to evaluate the impact of sarcopenia in patients who have been de-listed. We present this article in accordance with the STROBE reporting checklist (available at https://hbsn.amegroups.com/article/view/10.21037/hbsn-24-531/rc).

Methods

Population and data collection

This study was conducted retrospectively utilizing data from a prospectively maintained database. To identify patients registered on the LT waiting list, we contacted the regional unit of the French Biomedicine Agency, which is also responsible for prospectively recording registrations on this list. All patients registered between January 1, 2012 and December 31, 2022, at Rennes University Hospital were included in the study. Patients under 18 years of age, or those registered for super-emergency, re-transplantation, or multi-visceral transplantation, were excluded. All data were recorded prospectively by the French Biomedicine Agency, except for computed tomography (CT) scan data and pre-transplant complications of liver disease (ascites, hemorrhage from ruptured esophageal varices, etc.), which were recorded retrospectively. After 2013, patients with hepatocellular carcinoma (HCC) were transplanted according to the model that includes alpha-fetoprotein (AFP) (13).

The patients’ MELD scores and ages were calculated at the time of registration on the waiting list. The study protocol complied with the ethical guidelines of the Declaration of Helsinki and its subsequent amendments and was approved by the Rennes University Hospital Ethics Committee (No. 23.109). All patients provided their consent.

Calculation of MELD-Na

The MELD-Na was calculated using the formula (14):

MELD-Na=MELD−Na−[0.025×MELD×(140−Na)]+140[1]

where the serum sodium concentration (Na) is constrained between 125 and 140 mmol per liter.

Calculation of MELD-GRAIL-Na

To more accurately assess glomerular filtration rate (GFR), a new model has been described by Asrani et al. based on GRAIL. To calculate GRAIL, we used the website developed by the authors: www.bswh.md/grail (15). For the calculation of MELD-GRAIL, we used the following equation:

MELD-GRAIL=28.848+11.183×log(INR)+3.150×log(bilirubin)−5.078×log(GRAIL)[2]

For MELD-GRAIL-Na, we used the following equation:

MELD-GRAIL-Na=29.751+10.836×log(INR)+3.039×log(bilirubin)−5.054×log(GRAIL)−0.372×log(Na)[3]

With bilirubin values, in mg/dL, ranging from 1 to infinity, an INR ranging from 1 to 3, a serum sodium concentration, in mEq/mL, between 125 and 140 mmol/L, and a GRAIL, in mL/min/1.73 m², between 15 and 90 (noting that GRAIL is rated at 15 in the presence of dialysis) (16).

Four-variable nomogram

The article by van Vugt et al. demonstrated that the model including the MELD score, hepatic encephalopathy, age, and sarcopenia had a higher discriminatory capacity compared to the MELD score alone (17). This model will be used for analyzing the comparability of the different scores.

Assessment of body composition

As CT scans are considered the gold standard for assessing muscle area in cirrhotic patients, the assessment of sarcopenia was based on the calculation of the skeletal muscle mass index (SMI). The SMI is the ratio of musculoskeletal area to height squared (18). This assessment was based on the preoperative CT scan performed within 3 months of the listing date. Body composition was assessed using the MuViSS tool, whose methodology was published in Wasielewski et al. (19).

To accurately assess the impact of sarcopenia, all patients without a pre-transplant CT scan, or with a CT scan older than 3 months, were excluded from the analysis. We also assessed the adipose surface on the same scan section. This analysis was based on a section passing through the third lumbar vertebra. Tissues were distinguished using Hounsfield units (HU), with values ranging from −29 to +150 HU for muscle (20) and −190 to −30 HU for fat (21). The skeletal muscle area, adjusted for the square of the patient’s height, was used to calculate SMI. The threshold values for the SMI, used to define sarcopenia, were <38.5 cm²/m² for women and <52.4 cm²/m² for men (22). In this study, the threshold defining visceral obesity, measured by the visceral fat area (VFA), was set at >100 cm² for both sexes (23). Subcutaneous fat was quantified by the subcutaneous fat area (SFA), expressed in cm². In the absence of a defined threshold, raw data were analyzed.

Calculation of the MELD-sarcopenia score

To calculate the MELD-sarcopenia score, we used the formula described by Montano-Loza et al. (9). The MELD-sarcopenia score was calculated as follows:

MELD-sarcopenia=MELD+(10.35×sarcopenia)[4]

Calculation of the gender-equity model for liver allocation (GEMA—GEMA-Na)

To calculate the GEMA score, we computed the RFH-GFR proposed by Kalafateli et al. (24), as follows:

RFH-GFR=45.9×creatinine−0.836×urea−0.229×INR−0.113×age−0.129×sodium0.972×1.236(ifmale)×0.92(ifmoderate/severeascites)[5]

For the calculation of the GEMA and GEMA-Na scores, we used the formula described by Rodriguez-Peralvarez et al. (12), as follows:

GEMA=3.777×ln(Bilirubin)+7.883×ln(INR)−8.306×ln(RFH-GFR)+31.932[6]

GEMA-Na=GEMA−Na−[0.025×GEMA×(140−Na)]+140[7]

Statistical analysis

For data description, quantitative results are expressed as medians and interquartile ranges, and qualitative results as headcounts (%). For group comparisons, the Mann-Whitney-Wilcoxon test was used for quantitative variables, and the Chi-squared test or Fisher’s exact test, if necessary, was used for qualitative variables. For time-to-event variables, Kaplan-Meier estimates were used, and the groups were compared using a log-rank test. To assess the discriminative ability of each score, the C-index was employed. To assess model calibration, the Brier score was used as a performance measure. To study the effect of the interaction between gender and sarcopenic status on 3-month delisting, a Cox model was employed. All statistical tests had a significance level set at 0.05. Statistical analyses were performed using SAS software, v.9.4^® (SAS Institute, Cary, NC, USA) and R software [R Core Team (2024), Vienna, Austria; https://www.R-project.org/].

The primary endpoint of this study was removal from the waiting list (including death or disease progression). For all patients, time on the waiting list was counted from the date of listing. Patients who were removed from the waiting list due to clinical deterioration related to liver pathology, death, or progression of HCC beyond the specified criteria were still considered as wait-listed.

Results

Patients

A total of 1,488 patients were registered on the waiting list from January 1, 2012 to December 31, 2022. Data regarding the inclusion of patients in the analysis are available in the flow chart in supplementary data (Figure S1). Of these, 900 cirrhotic patients were included in the analysis. The majority of listed patients were male (n=746, 82.9%), with a median age of 61 years, and a median body mass index (BMI) of 27.5 kg/m² (Table 1). The primary indication for transplantation was HCC, and the median MELD score was 16. In this study, 6.6% of patients were delisted, and delisting predominantly occurred among women (P<0.001). Regardless of the score used (MELD, MELD-Na, MELD-sarcopenia, MELD-GRAIL, MELD-GRAIL-Na, GEMA, GEMA-Na), it was systematically higher in women than in men (P<0.001), except for the MELD-sarcopenia score (P=0.11). Finally, the median time to complete the assessment scan was 14 days, with a median follow-up time of 42.9 months.

Regarding body composition, sarcopenia was present in 36% of patients (n=326) and was predominantly found in men (P<0.001). Obesity was present in 11% of patients and was also predominantly found in men. All body composition data are described in the supplementary data (Table S1).

Score performance

Table 2 displays the performance of each score along with the corresponding C-index. The study suggests that GEMA-Na has the best discriminative performance for predicting 3-month delisting (C=0.7205). Surprisingly, however, the Nomogram (C=0.7037), MELD-GRAIL-Na (C=0.7023), and MELD-GRAIL (C=0.7023) exhibit a higher C-index than GEMA (C=0.7011).

Survival according to sarcopenic status

The 3-month list-exit analysis (for either death or worsening) did not differ significantly according to sarcopenic status (log-rank: P=0.18), but did differ statistically according to gender (log-rank: P<0.001) (Figure 1). On the other hand, the overall list exit analysis showed a statistically significant difference according to sarcopenic status (log-rank: P=0.009) (Figure 2).

Figure 1 The 3-month survival curve for patients on the waiting list. (A) 3-month survival curve for patients on the waiting list according to sarcopenic status; (B) 3-month survival curve for patients on the waiting list according to gender. F, female; M, male.

Figure 2 Overall survival curve of patients on the waiting list according to sarcopenic status.

Disparity according to sarcopenic status

Previous results indicate that the GEMA-Na score provides better prediction of 3-month discharge. Although it helps reduce gender-related disparities, this score does not consider patients’ sarcopenic status. The interaction between gender and sarcopenic status was tested by Cox model and found to be significant (P=0.03), indicating that the effects of delisting due to sarcopenic status differ significantly by gender. When comparing delisted patients by gender, sarcopenia is one of the three factors that differ significantly between men and women (Table S2). The subgroup analysis of the 40 patients removed from the transplant list based on their sarcopenic status demonstrates that there is no statistically significant difference between the MELD scores or the GEMA-Na scores for sarcopenic versus non-sarcopenic men (Table S3). This suggests that the pathophysiological changes associated with sarcopenia may independently influence prognosis prior to transplantation. However, a larger-scale study is needed to confirm this hypothesis.

Impact of body composition by gender

Gender-specific characteristics are shown in Table 3. It should be noted that body composition has a significantly different impact on list exit according to gender. In fact, in women, there was no statistical difference between sarcopenic status and off-list status. Additionally, BMI, SMI, SFA, and VFA are not statistically different between women who have or have not come off the list. In men, on the other hand, 60% (n=24) of the patients removed from the list were sarcopenic (P<0.001), and body composition was significantly different in men removed from the list.

Discussion

Prioritizing access to liver transplantation in the current context of organ shortage is one of the major challenges. The goal is to reduce mortality or worsening conditions on the waiting list as much as possible. The objectives of this study were: (I) to compare the different scores currently in use or recently described, in order to determine the one with the greatest discriminatory power; and (II) to highlight the importance of assessing patients’ sarcopenic status to avoid creating further disparities based on the existing scores.

The main limitation of the MELD score is that women are significantly more likely to be removed from the list than men (3,25). This disparity was confirmed in our study, with 12% of women exiting the list between 2012 and 2022, compared to 5.4% of men (P=0.001). In this context, the GEMA and GEMA-Na scores were recently developed to limit this disparity. Marrone et al. (26) recently confirmed the superiority of the GEMA-Na score. However, it should be noted that their comparisons did not include scores incorporating GRAIL, another estimator of renal function in cirrhotic patients. Our study aligns with the observations reported in the literature. Our study is in line with observations reported in the literature. Indeed, while the C-indexes of the MELD-GRAIL-Na (0.7033) and the nomogram (0.7037) are relatively close to that of the GEMA-Na, the latter still demonstrates superiority. It is important to highlight that one of the strengths of our study lies not only in the inclusion of highly predictive scores, such as MELD-GRAIL and MELD-GRAIL-Na, but also in the substantial number of patients included. However, these results need to be validated in a larger cohort to confirm their robustness.

Epidemiology of liver diseases, and by extension, profiles of candidates awaiting liver transplantation, is constantly evolving. Indeed, number of transplants for hepatitis C viral cirrhosis is sharply declining, while, conversely, indications for liver transplantation due to nonalcoholic steatohepatitis (NASH) are continuously increasing (1). As a result, the evaluation and prioritization of patients on the waiting list must also evolve. In our view, this evolution should include the assessment and incorporation of sarcopenic status in the prioritization score.

Sarcopenia, the term used to describe a loss of muscle mass, is recognized as a risk factor for mortality in cirrhotic patients (7,8). Furthermore, it has been shown that accelerating access to liver transplantation for these patients could reduce on-list mortality (7,22), shorten hospitalization time (27), and decrease post-transplant mortality (28). With this in mind, Montano-Loza et al. described the MELD-sarcopenia score to include sarcopenic status in the prioritization of listed patients (9); sarcopenic status increases the MELD score by 10 points. However, this score did not demonstrate real superiority (17). This lack of improvement was also observed in our study, with a C-index of 0.67 for MELD-sarcopenia. This lack of improvement is challenging to elucidate, as sarcopenia represents a marker of fragility and systemic imbalance driven by numerous interconnected mechanisms, including malnutrition, chronic inflammation, metabolic dysfunctions associated with liver disease, ammonia toxicity, and hormonal dysregulation. The multifactorial nature of these mechanisms complicates the isolated evaluation of sarcopenia’s impact within current predictive scoring systems.

Despite these results, van Vugt et al. developed a nomogram that incorporates sarcopenia, history of hepatic encephalopathy prior to liver transplantation, and age, in addition to MELD, to predict mortality on the waiting list (17). In this study, we replicated this model with these four variables and found significant discriminatory performance. After GEMA-Na, this model had the best C-index (C=0.7037). The model’s ability to predict list exit is hardly surprising, given the study by Cullaro et al. (25). In fact, this model included 3 of the 6 clinical and biological variables identified as risk factors for leaving the list in their multivariate analysis. These results, therefore, seem to confirm that considering sarcopenic status in the evaluation and prioritization of patients on the waiting list remains essential. This is especially true given that, after 3 months, the survival of sarcopenic patients on the waiting list was significantly reduced (9). This study further confirms the reduction in survival after 3 months for sarcopenic patients.

One of the criticisms of sarcopenia assessment is its inter-operator variability (29). In this study, we used artificial intelligence to assess sarcopenia in a reliable, simple, rapid, and reproducible way, thereby minimizing inter-operator variability (19).

Finally, the issue of addressing gender disparity in access to transplantation is twofold. First, the GEMA score was designed to mathematically increase the scores of women in order to limit this disparity. In doing so, we must consider the impact this balancing might have on men, particularly those with sarcopenia. It is important to note that, in our study, 60% of the men removed from the list were sarcopenic, so this new score could exacerbate disparities related to body composition. Second, there are non-objective reasons for delisting women. According to Cullaro et al. (25), women are 10% more likely to be removed from the list. There are numerous factors contributing to the higher likelihood of women being removed from transplant waiting lists. Beyond the inadequacy of the MELD score, which underestimates the severity of disease in women (30,31), there is also the issue of graft-recipient size mismatch (31,32). Additionally, women are often subject to a potentially erroneous or exaggerated perception of fragility [as reflected in assessments like the Karnofsky Performance Status (KPS)] (25), unconscious biases among healthcare professionals (such as being perceived as less capable of tolerating major surgery) (31), and socio-economic or structural challenges, including family responsibilities, unequal access to follow-up care, and financial constraints (33,34). In the absence of objective criteria, functional assessment tools should be standardized to include measures such as the Liver Frailty Index (LFI), grip strength tests, and walking speed, which are significantly less susceptible to practitioner subjectivity. Additionally, medical teams could benefit from training designed to raise awareness of implicit biases, such as the exaggerated perception of women’s fragility. Moreover, implementing a multidisciplinary evaluation for each patient—encompassing input from hepatologists, surgeons, nutritionists, and physiotherapists—would further help mitigate the influence of individual biases on clinical decision-making.

There are several limitations to this study that should be considered when interpreting our results. First, the design of the study—a retrospective observational study. Additionally, the study was conducted over a long period of 10 years, so the reliability of the results depends on the accuracy of the data collection methodology. To minimize errors and ensure the robustness of our results, we collaborated with the French Biomedicine Agency for data collection. This organization is responsible for, collecting data from patients newly registered on the LT waiting list, and therefore, the data were collected prospectively. However, despite our efforts to account for a large number of variables, other factors potentially involved in patients leaving the list within 3 months may not have been included in our analysis. Another limitation of the study is the differences in etiologies between men and women regarding liver transplantation indications, which may impact decision-making practices, particularly in relation to delisting.

Finally, the evaluation of sarcopenia remains a significant challenge. This complexity arises not only from the diagnostic methods employed but also from the variability in the cut-off values applied. While numerous studies address sarcopenia, comparing their findings proves difficult due to differences in diagnostic approaches, such as bioelectrical impedance analysis, CT imaging with assessments of the psoas muscle index (PMI), or the SMI, among others. Even when the diagnostic methods align, as seen in SMI evaluations, the thresholds for categorizing patients as sarcopenic or non-sarcopenic vary. For instance, many studies rely on the criteria established by Prado et al. (35), which are based on cancer patients and may not reflect the characteristics of individuals with cirrhosis. To address this, our article adopts the criteria of Carey et al. (22), which were specifically developed for a population with end-stage liver disease. Moreover, research has shown that the average muscle mass in Asian populations is approximately 15% lower than in Western populations (36,37). This disparity could introduce biases in sarcopenia evaluations and contribute to the lack of comparability across studies.

Conclusions

In our study, the GEMA-Na score appeared to be the most predictive of delisting, although it does not take sarcopenia status in account. We observed a gender disparity associated with sarcopenia, particularly in delisted patients. The impact of sarcopenia on these patients appears to be significant; however, these results need to be validated on a larger scale. Therefore, we believe it is essential to develop a new score that incorporates sarcopenia status to reduce the increased risk of delisting in sarcopenic men at 3 months.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the STROBE reporting checklist. Available at https://hbsn.amegroups.com/article/view/10.21037/hbsn-24-531/rc

Data Sharing Statement: Available at https://hbsn.amegroups.com/article/view/10.21037/hbsn-24-531/dss

Peer Review File: Available at https://hbsn.amegroups.com/article/view/10.21037/hbsn-24-531/prf

Funding: None.

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://hbsn.amegroups.com/article/view/10.21037/hbsn-24-531/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study protocol complied with the ethical guidelines of the Declaration of Helsinki and its subsequent amendments and was approved by the Rennes University Hospital Ethics Committee (No. 23.109). All patients provided their consent.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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