Abstract
Background & Aims
The new nomenclature for metabolic dysfunction-associated steatohepatitis (MASH) requires presence of steatohepatitis in the context of at least one cardiometabolic risk. Having a health-related quality of life (HRQL) instrument validated specifically in patients with MASH is important for clinical research and clinical trials.
Methods
From our non-alcoholic fatty liver disease/non-alcoholic steatohepatitis (NAFLD/NASH) database, patients who met the definition of MASH according to the new criteria were selected. Subjects had completed the Chronic Liver Disease Questionnaire for NAFLD/NASH (CLDQ-NAFLD/NASH) and other HRQL instruments (Functional Assessment of Chronic Illness Therapy – Fatigue [FACIT-F], Short-Form 36 [SF-36]), and had available clinico-laboratory data including fibrosis non-invasive tests (NITs). The CLDQ-MASH was developed following a standard pipeline and subsequently validated in a non-overlapping sample.
Results
There were 4,213 MASH patients included: age 56 ± 11 years, 44% male, 65% type 2 diabetes, 69% advanced fibrosis (F3–F4). The patients with MASH were split 1:2 into a training set used for development of CLDQ-MASH and a testing set used for validation using standard pipeline. After item reduction and exploratory factor analysis with the training set (>90% variance), the CLDQ-MASH contained 35 items and seven domains. With the non-overlapping testing set, CLDQ-MASH demonstrated excellent face validity, internal consistency (all Cronbach’s alpha >0.78), and high correlations with relevant domains of SF-36, FACIT-F (p <0.01). Known-groups validity assessment confirmed that CLDQ-MASH can discriminate patients based on liver disease severity (histology- and NIT-based) and the presence of non-hepatic comorbidities (obesity, type 2 diabetes, depression, clinically overt fatigue, insomnia). In a subsample of subjects with 1-year follow-up, the instrument was responsive to changes in Enhanced Liver Fibrosis® scores and liver stiffness measurements (p <0.05 for four to six domains).
Conclusions
The CLDQ-MASH can be used as a valid disease-specific HRQL instrument for patients with MASH.
Impact and implications:
The new criteria for metabolic dysfunction-associated steatohepatitis (MASH) are different from those previously used for non-alcoholic steatohepatitis so the evidence collected for the previous criteria need to be revisited, including disease-specific instruments for assessment of health-related quality of life. In patients with MASH, Chronic Liver Disease Questionnaire-MASH (CLDQ-MASH; 35 items, seven domains) has excellent psychometric properties including its internal consistency and various aspects of validity, and is responsive to changes in liver disease severity indicators. The CLDQ-MASH can be used as a valid disease-specific health-related quality of life instrument for MASH in clinical research and clinical trials.
Keywords: Chronic liver disease, Metabolic liver disease, NASH, NAFLD, Quality of life, MASH, MASLD
Graphical abstract
Highlights:
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The new criteria for MASH are different from those previously used for NASH.
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A new quality of life instrument for MASH, the CLDQ-MASH, has 35 items, seven domains.
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The CLDQ-MASH has excellent psychometric properties (consistency, validity).
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The instrument is also responsive to changes in liver disease severity indicators.
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Therefore, the CLDQ-MASH can be used as a valid HRQL instrument for MASH.
Introduction
Metabolic dysfunction-associated steatohepatitis (MASH) is the most common cause of liver disease affecting 5–7% of the general population1 and is responsible for increasing clinical burden (cirrhosis, hepatocellular carcinoma, and liver mortality), as well as enormous economic and disability burden.[2], [3], [4]
Despite previous beliefs, MASH is not completely asymptomatic. Indeed, patients with MASH experience significant fatigue and other non-specific symptoms such as abdominal discomfort and pruritus.5 In this context, MASH has been shown to negatively impact patients’ health-related quality of life (HRQL) and other patient reported outcome (PRO) measures.[6], [7], [8] Studies using the generic Functional Assessment of Chronic Illness Therapy – Fatigue (FACIT-F) and disease-specific Chronic Liver Disease Questionnaire for non-alcoholic fatty liver disease/non-alcoholic steatohepatitis (CLDQ-NAFLD/NASH) have shown the impairment in HRQL and other PROs which worsen with disease severity and in the presence of other comorbidities.9 Although evidence is still limited, data from efficacy trials suggest that PROs in patients with NASH/MASH can improve if patients respond to treatment as indicated by improvement of fibrosis and/or resolution of steatohepatitis.[10], [11], [12]
Even with the growing burden of MASH, awareness of this disease remains relatively low.13 This was partly blamed on stigma associated with the previous name (NAFLD) and lack of connection with underlying pathogenesis which is related to metabolic abnormalities.14 In this context, it has been shown that stigma did exist in a small proportion of these patients15 and it negatively affected patients’ HRQL.16 These challenges led to development of a multisociety effort which concluded by changing the name from NAFLD to metabolic dysfunction-associated steatotic liver disease (MASLD) and from NASH to MASH.17 In this process of changing the terminology, the diagnostic definition of this liver disease also changed. In this context, the diagnosis of MASH requires not only the presence of steatohepatitis in the absence of excessive alcohol use, but also requires having at least one cardiometabolic risk.17
The change in the terminology led to reassessment of evidence generated under the previous definition of NASH with the new definition. Recent studies have shown that there is very high concordance of NAFLD and MASLD and, in particular, NASH and MASH.18 However, because the two definitions are not identical, the HRQL instruments developed for patients with NAFLD and NASH should also be re-assessed and validated for patients who fulfil the criteria for MASH. Therefore, our aim was to validate an etiology-specific instrument of CLDQ (CLDQ-MASH) that would be tailored to patients with MASH.
Patients and methods
Study sample
Individuals with MASH from our clinical NAFLD/MASLD database were included in this study.19 In the multicenter multinational database which was established in 2015, all individuals were required to have NAFLD (biopsy-proven or imaging-based), be at least 18 years of age, not to have other major chronic diseases which might substantially bias their HRQL, and were willing and able to give informed consent. Individuals with NAFLD were not eligible for inclusion in the database if they had any condition which, in the opinion of the principal investigator, would make them unsuitable for enrollment, or which could interfere with their participation (such as psychiatric or emotional problems, language or cognitive difficulties); had any other cause of chronic liver disease (including but not limited to: excessive alcohol use, viral hepatitis, autoimmune liver disease, etc.); had history of hepatic decompensation or liver transplantation; or were unwilling or unable to provide informed consent.
From this database, we selected only NAFLD patients who met the criteria for MASH; those individuals were required to have biopsy-proven NASH in the presence of at least one cardiometabolic risk factor such as overweight, excessive waist circumference, type 2 diabetes, hypertension, or hyperlipidemia.17 Demographic and clinical parameters (elements of medical history, histologic fibrosis stage, relevant laboratory and imaging data including fibrosis non-invasive tests [NITs]) were available. To be included in this study, participants were also required to have completed the CLDQ-NAFLD upon enrollment to the database.20
The sample was then randomly split 1:2 into training (initial development of CLDQ-MASH) and testing (validation of CLDQ-MASH) non-overlapping sets. Therefore, the CLDQ-MASH was developed using the training set and validated using the testing set following a standard pipeline.21
Step 1: Development of CLDQ-MASH
The CLDQ-NAFLD/NASH instrument was used as a basis for development of CLDQ-MASH, similar to other etiology-specific instruments of the CLDQ family (CLDQ-HCV, CLDQ-HBV, CLDQ-PSC, CLDQ-PBC[20], [21], [22], [23], [24], [25]). Originally, both CLDQ and CLDQ-NAFLD/NASH instruments were based on a large item reduction questionnaire each, with an extensive number of items that had been collected from patient interviews, focus groups, review of the literature, and expert input. Then, for each etiology-specific instrument, additional patient input had been obtained to supplement the initial questionnaires followed by further item reduction, factor analysis, and validation. Using this methodology, the CLDQ-NAFLD/NASH instrument had been developed with 36 items and six domains, and was previously published and validated in multiple languages.20 We used a similar approach to develop the CLDQ-MASH from the orginal CLDQ-NAFLD/NASH.
Item reduction
In this study, the aim of item reduction was to remove items which would be not relevant in the context of MASH. For this purpose, we calculated the proportion of individuals in the training set who indicated that a problem bothered them at least ’a little of the time’ (as opposed to ‘hardly any of the time’ or ‘none of the time’) over the recall period of 2 weeks for each item. Then, the items reported as never or hardly even bothering them by more than 70% of individuals would be removed as non-relevant.
Factor analysis
To group the items into interpretable domains, we conducted exploratory factor analysis using the training set and the items which remained after the item-reduction step. The number of factors was not pre-defined but rather determined from the proportion of total variance accounted for by the factors (90%–100%). Items were assessed based on their factor loadings after varimax rotation and for face validity; by default, the domain with the highest loading was presumed to be the most relevant for each item.
CLDQ-MASH
The items for CLDQ-MASH were distributed into domains according to the factor loadings and the content validity assessment in the training set so that each item would be assigned to one domain. In the final instrument, each domain includes at least two items, and the final domain names were chosen to reflect their main idea.
Similar to other instruments of the CLDQ family, CLDQ-MASH follows the pattern for each question: ‘How much of the time/How often during the past two weeks you <experienced a problem>/<were bothered by a problem>?’, and a 1–7 Likert scale was used for the responses (where the score of 1 would correspond to ‘All of the time’, and the score of 7 to ‘None of the time’). Again, similar to other CLDQ instruments, the scoring scheme for CLDQ-MASH requires each domain score to be calculated as an average of the domain’s items without additional Likert scores transformation. Finally, similar to other CLDQ instruments, greater scores for all CLDQ-MASH domains would reflect better health.
Step 2: Validation of CLDQ-MASH
For the second step, a standard HRQL instrument validation pipeline was applied to validate the CLDQ-MASH instrument in a separate group of participants (the testing set).
Internal consistency
Internal consistency of CLDQ-MASH was assessed by calculation of Cronbach’s alpha coefficients for the domains, and by calculation of item-to-own-domain correlations after adjustment for overlap for all items. The distributions of the domain scores were also qualitatively evaluated for skewness as well as discriminatory power and floor/ceiling effects.
Known-groups validity
Known-groups validity was assessed by evaluation of the association of CLDQ-MASH domain scores with potentially relevant demographic and clinical parameters. The validation parameters were age, sex, obesity (BMI >30), type 2 diabetes, history of depression, clinically overt fatigue, sleep disorders, and the severity of liver disease (by biopsy or NITs with commonly used cut-off values26). The Wilcoxon non-parametric test was used to compare the CLDQ-MASH domain scores between the respective groups of participants.
Other validity assessments
Discriminant validity assessment was run with the purpose to confirm that each item was the most correlated with its own domain. For the purpose of convergent validity assessment, correlations between related domains of CLDQ-MASH and of other validated HRQL instruments (Short-Form 36 [SF-36], FACIT-F27,28) were calculated.
Responsiveness to changes in liver disease severity
A subsample of patients with MASH who had sequential (baseline and 1-year follow-up) measurements of NITs (Enhanced Liver Fibrosis® [ELF] score, liver stiffness by transient elastography) was used to assess responsiveness of the instrument to changes in those NITs; previously published cut-offs for NIT changes were applied.29 The changes in CLDQ-MASH domain scores were calculated as mean ± SE and were compared to zero and between subgroups using sign rank and rank sum tests, respectively.
All analyses were run using SAS 9.4 (SAS Institute, Cary, NC, USA). All research was conducted in accordance with both the Declarations of Helsinki and Istanbul, the database and all research were approved by the IRB and all the data had been collected after informed consent.
Results
There were 4,213 individuals who had completed the CLDQ-NAFLD and fulfilled the criteria for MASH. Characteristics were, on average, 56 ± 11 years old (62% ≥55 years), 44% male, 51% employed, 70% obese, 65% with type 2 diabetes, 25% history of depression, 14% reported having clinically overt fatigue, 16% sleep disorders or insomnia, 69% advanced fibrosis (F3 or F4), 11% ELF score ≥11.3, and 56% liver stiffness measurement (LSM) by transient elastography ≥12 kPa (Table 1). The sample was randomly split into a training set (1,405 participants) and a testing set (2,808 participants) (Table 1).
Table 1.
Demographic and clinical parameters of subjects with MASH used for development (training set) and validation (testing set) of the CLDQ-MASH.
| Training set | Testing set | All MASH | |
|---|---|---|---|
| N | 1,405 | 2,808 | 4,213 |
| Age, years | 56.1 ± 10.7 | 56.1 ± 10.6 | 56.1 ± 10.6 |
| Age ≥55 years, n (%) | 864 (61.5) | 1,741 (62.0) | 2,605 (61.8) |
| Male sex, n (%) | 619 (44.1) | 1,224 (43.6) | 1,843 (43.7) |
| Employed, n (%) | 617 (49.7) | 1,266 (51.2) | 1,883 (50.7) |
| BMI, kg/m2 | 33.6 ± 6.2 | 33.7 ± 6.4 | 33.7 ± 6.3 |
| Obese (BMI >30), n (%) | 967 (69.1) | 1,965 (70.3) | 2,932 (69.9) |
| Type 2 diabetes, n (%) | 915 (65.1) | 1,816 (64.7) | 2,731 (64.8) |
| Depression or mood disorders, n (%) | 351 (25.3) | 695 (25.1) | 1,046 (25.2) |
| Clinically overt fatigue, n (%) | 212 (15.3) | 369 (13.3) | 581 (14.0) |
| Insomnia or sleep disorders, n (%) | 167 (14.2) | 399 (17.0) | 566 (16.0) |
| Histologic advanced fibrosis (F3 or F4), n (%) | 966 (69.6) | 1,917 (68.8) | 2,883 (69.1) |
| Histologic cirrhosis, n (%) | 321 (23.1) | 659 (23.7) | 980 (23.5) |
| ELF score | 10.0 ± 1.0 | 10.0 ± 1.0 | 10.0 ± 1.0 |
| ELF ≥11.3, n (%) | 145 (12.4) | 245 (10.5) | 390 (11.2) |
| FIB-4 score | 1.97 ± 1.77 | 1.93 ± 1.36 | 1.94 ± 1.51 |
| FIB-4 ≥2.67, n (%) | 279 (20.1) | 506 (18.4) | 785 (19.0) |
| LSM, kPa | 16.5 ± 10.9 | 16.1 ± 11.0 | 16.2 ± 11.0 |
| LSM ≥12 kPa, n (%) | 533 (60.2) | 969 (54.5) | 1,502 (56.4) |
CLDQ, Chronic Liver Disease Questionnaire; ELF score, Enhanced Liver Fibrosis score; FIB-4, Fibrosis-4; LSM, liver stiffness measurement; MASH, metabolic dysfunction-associated steatohepatitis.
Step 1. CLDQ-MASH
During the item reduction step with the training set, one original CLDQ-NAFLD/NASH item had been reported to be never or hardly even a problem by 72% of individuals, while 35 items were further fed to factor analysis (Table 2). For the remaining 35 items, 33–79% (average 50%) of individuals reported being bothered by the respective problem at least ‘a little of the time’ during the past 2 weeks. The one excluded item asked if the individuals were frequently concerned about availability of a liver transplant should they need it.
Table 2.
The CLDQ-MASH structure (all the parameters as assessed in the training set).
| CLDQ-MASH item description (‘For how long/How often during the past two weeks have you been <bothered by a problem>’) | Percentage of participants reporting never or hardly ever bothered by the problem | Mean ± SD (range 1–7) | Correlation with own domain |
|---|---|---|---|
| Domain: Worry about liver disease | |||
| Worried about the impact of liver disease on one’s family | 50.3 | 5.11 ± 1.86 | 0.75 |
| Worried about symptoms developing into major problems | 41.4 | 4.84 ± 1.82 | 0.84 |
| Worried about the condition getting worse | 43.4 | 4.94 ± 1.78 | 0.87 |
| Worried about never feeling any better | 58.4 | 5.48 ± 1.64 | 0.73 |
| Feeling like one may die earlier because of MASH | 61.7 | 5.59 ± 1.69 | 0.77 |
| Feeling distressed by having MASH | 55.0 | 5.33 ± 1.72 | 0.82 |
| Domain: Activity | |||
| Shortness of breath is a problem for daily activities | 62.9 | 5.63 ± 1.57 | 0.63 |
| Bothered by having decreased strength | 55.3 | 5.36 ± 1.65 | 0.69 |
| Having trouble lifting or carrying heavy objects | 53.8 | 5.12 ± 1.97 | 0.73 |
| Having trouble walking two blocks or climbing two flights of stairs | 61.0 | 5.45 ± 1.87 | 0.75 |
| Having trouble bending, lifting, or stooping | 51.7 | 5.09 ± 1.89 | 0.75 |
| Domain: Emotional well-being | |||
| Feeling anxious | 54.2 | 5.33 ± 1.67 | 0.73 |
| Feeling unhappy | 60.0 | 5.52 ± 1.52 | 0.79 |
| Being irritable | 46.1 | 5.17 ± 1.49 | 0.70 |
| Having mood swings | 56.1 | 5.43 ± 1.5 | 0.76 |
| Feeling depressed | 63.2 | 5.67 ± 1.52 | 0.81 |
| Having problems concentrating | 54.4 | 5.37 ± 1.55 | 0.68 |
| Not enjoying life | 62.3 | 5.54 ± 1.66 | 0.60 |
| Domain: Fatigue | |||
| Being tired or fatigued | 21.4 | 4.04 ± 1.76 | 0.76 |
| Feeling sleepy during the day | 28.6 | 4.48 ± 1.67 | 0.79 |
| Feeling a decreased level of energy | 37.1 | 4.72 ± 1.7 | 0.75 |
| Feeling drowsy | 39.0 | 4.87 ± 1.61 | 0.79 |
| Feeling the need to take naps during the day | 33.0 | 4.46 ± 1.86 | 0.67 |
| Domain: Digestive symptoms and diet | |||
| Feeling of abdominal bloating | 47.4 | 4.99 ± 1.87 | 0.66 |
| Abdominal pain | 62.1 | 5.63 ± 1.54 | 0.72 |
| Unable to eat as much as one would like | 63.2 | 5.57 ± 1.75 | 0.48 |
| Bothered by a limitation of one’s diet | 66.8 | 5.77 ± 1.47 | 0.47 |
| Feeling of abdominal discomfort | 58.3 | 5.48 ± 1.59 | 0.77 |
| Domain: Sleep disturbances | |||
| Having difficulty sleeping at night | 38.3 | 4.64 ± 1.89 | 0.80 |
| Unable to fall asleep at night | 50.2 | 5.06 ± 1.8 | 0.80 |
| Domain: Systemic symptoms | |||
| Bodily pain | 33.3 | 4.46 ± 1.83 | 0.62 |
| Muscle cramps | 54.7 | 5.37 ± 1.66 | 0.53 |
| Dry mouth | 42.6 | 4.78 ± 1.86 | 0.53 |
| Itching | 59.1 | 5.53 ± 1.64 | 0.45 |
| Joint pain | 35.5 | 4.42 ± 2.01 | 0.65 |
CLDQ, Chronic Liver Disease Questionnaire; MASH, metabolic dysfunction-associated steatohepatitis.
Exploratory factor analysis of the 35 items in the training set resulted in 60% of variance in those explained by one factor, 71% by two factors, 77% by three factors, 82% by four factors, 86% by five factors, 89% by six factors, and 91% by seven factors. Given that, we chose the resulting number of factors and, thus, domains in CLDQ-MASH to be seven. Varimax rotation was used to calculate the resulting factor loadings for all items.
After an additional assessment of content validity for the items and their highest factor loadings, four out of seven factors/domains in CLDQ-MASH were found to be structured similarly to the CLDQ-NAFLD/NASH domains of Worry, Emotional well-being, Fatigue, Systemic symptoms. However, one item which originally belonged to the CLDQ-NAFLD/NASH Fatigue domain (asking about having decreased strength) and one item from the original Systemic symptoms domain (asking about shortness of breath being a problem for daily activities) were both found to be primarily loading on a fifth factor for CLDQ-MASH, along with three original Activity/energy domain items (all asking about problems with physical activities); we named the resulting five-item CLDQ-MASH domain Activity. In addition, two items originally from the CLDQ-NAFLD/NASH Emotional well-being domain (asking about having difficulty sleeping and being unable to fall asleep) were found to be loading on the sixth factor for CLDQ-MASH; the domain was named Sleep disturbances. Finally, three items from the original CLDQ-NAFLD/NASH domain of Abdominal symptoms were all found to be loading on the same (seventh) factor for CLDQ-MASH, together with two diet-related items from the original Activity/energy domain (asking about being able to eat as much as one would like and being bothered by diet limitations), and this sustained in an additional round of factor analysis with forcing an eighth factor into the model; the domain was named Digestive symptoms and diet.
The final CLDQ-MASH instrument has 35 items grouped into seven HRQL domains: Activity, Digestive symptoms and diet, Emotional well-being, Fatigue, Sleep disturbances, Systemic Symptoms, and Worry (Table 2). The total CLDQ-MASH score can be calculated as an average of the seven domain scores.
Step 2. Validation of CLDQ-MASH
Internal consistency
The non-overlapping testing set was used for validation of the instrument (Table 1). A good to excellent internal consistency (all Cronbach alphas >0.78) was detected in all seven CLDQ-MASH domains (Table 3). Additionally, after sequential one-item exclusions, the resulting Cronbach’s alpha values did not change substantially (Table 3); this confirms that the items are neither too correlated with, nor too different from, other items belonging to the same domains. The greatest variability in Cronbach’s alpha values over the course of one-item exclusions was found in the Digestive symptoms and Systemic symptoms domains which may indeed include items measuring potentially distinct, even if highly correlated, constructs such as abdominal problems vs. diet restrictions or bodily pain vs. itching. Despite this, item-to-own-dimension correlations were above +0.50 for all but three items (Table 1), and all items were the highest correlated with their own CLDQ-MASH domain (discriminatory validity).
Table 3.
Internal consistency of CLDQ-MASH (testing set).
| CLDQ-MASH domain | Cronbach’s alpha | Item to own domain correlations | Cronbach α with one item removed |
|---|---|---|---|
| Activity | 0.88 | 0.63–0.75 | 0.84–0.87 |
| Digestive symptoms and diet | 0.82 | 0.47–0.77 | 0.74–0.83 |
| Emotional well-being | 0.91 | 0.60–0.81 | 0.88–0.91 |
| Fatigue | 0.90 | 0.67–0.79 | 0.87–0.90 |
| Sleep disturbances | 0.89 | 0.80 | NA |
| Systemic symptoms | 0.78 | 0.45–0.65 | 0.71–0.77 |
| Worry | 0.93 | 0.73–0.87 | 0.91–0.93 |
CLDQ, Chronic Liver Disease Questionnaire; MASH, metabolic dysfunction-associated steatohepatitis; NA, not applicable.
The distribution of the CLDQ-MASH domain scores suggested some skewness towards higher values for most items, with the Fatigue domain being the least skewed (Fig. 1). Indeed, the prevalence of values of less than 3.5 did not exceed 20% for six domain scores (25% for Fatigue). In contrast, the proportion of the highest possible values (≥6.5) ranged from 8% (Fatigue) to 29% (Activity and Sleep disturbances) (Fig. 1).
Fig. 1.
Histograms of the domain and total scores of CLDQ-MASH. CLD, chronic liver disease; MASH, metabolic dysfunction-associated steatohepatitis.
Validity
Known-groups validity assessment of CLDQ-MASH and its discriminant function in the testing set with reference to demographic and clinical parameters is summarized in Table 4. As expected, males had higher HRQL scores in all domains of CLDQ-MASH and so did individual without obesity, type 2 diabetes, and other comorbidities (depression, clinically overt fatigue, sleep disorders) (p <0.01) (Table 4). In fact, individuals with MASH and obesity had the greatest impairment in the Activity, Fatigue, and Systemic Symptoms domain scores in comparison to those with MASH who were non-obese (all p <0.0001) (Table 4). Individuals with type 2 diabetes also had the lowest scores in the Activity and Systemic symptoms domains (all p <0.0001) (Table 4). Furthermore, subjects with history of depression had lower scores in all CLDQ-MASH domain, with the greatest impairment observed in the Emotional well-being and Fatigue domains (all p <0.0001) (Table 4). Expectedly, the greatest HRQL impairment associated with clinically overt fatigue was observed in the CLDQ-MASH Fatigue domain (by 16% of the score range size, p <0.0001), and history of sleep disorders or insomnia was associated with the greatest impairment in the Sleep domain score (18% of the score range size, p <0.0001) (Table 4).
Table 4.
Known-groups validity of CLDQ-MASH (testing set).
| Item | Age ≥55 years | Age <55 years | p values |
|---|---|---|---|
| N | 1,741 | 1,067 | |
| Activity | 5.31 ± 1.48 | 5.44 ± 1.49 | 0.0035 |
| Digestive symptoms and diet | 5.60 ± 1.24 | 5.40 ± 1.30 | 0.0001 |
| Emotional well-being | 5.54 ± 1.20 | 5.31 ± 1.35 | 0.0001 |
| Fatigue | 4.61 ± 1.40 | 4.36 ± 1.56 | 0.0001 |
| Sleep disturbances | 4.94 ± 1.72 | 4.92 ± 1.79 | 0.96 |
| Systemic symptoms | 4.92 ± 1.30 | 5.03 ± 1.36 | 0.0118 |
| Worry | 5.29 ± 1.46 | 4.98 ± 1.62 | <0.0001 |
| Total CLDQ-MASH | 5.17 ± 1.12 | 5.06 ± 1.21 | 0.0499 |
| Item | Male | Female | p values |
| N | 1,224 | 1,584 | |
| Activity | 5.70 ± 1.35 | 5.09 ± 1.53 | <0.0001 |
| Digestive symptoms and diet | 5.85 ± 1.08 | 5.26 ± 1.33 | <0.0001 |
| Emotional well-being | 5.65 ± 1.19 | 5.30 ± 1.29 | <0.0001 |
| Fatigue | 4.78 ± 1.39 | 4.31 ± 1.50 | <0.0001 |
| Sleep disturbances | 5.26 ± 1.62 | 4.68 ± 1.80 | <0.0001 |
| Systemic symptoms | 5.28 ± 1.21 | 4.71 ± 1.36 | <0.0001 |
| Worry | 5.44 ± 1.43 | 4.97 ± 1.57 | <0.0001 |
| Total CLDQ-MASH | 5.42 ± 1.05 | 4.90 ± 1.18 | <0.0001 |
| Item | Obesity (BMI ≥30) | No obesity (BMI <30) | p values |
| N | 1,965 | 831 | |
| Activity | 5.23 ± 1.53 | 5.65 ± 1.32 | <0.0001 |
| Digestive symptoms and diet | 5.45 ± 1.28 | 5.67 ± 1.21 | <0.0001 |
| Emotional well-being | 5.39 ± 1.28 | 5.59 ± 1.20 | 0.0001 |
| Fatigue | 4.39 ± 1.48 | 4.82 ± 1.41 | <0.0001 |
| Sleep disturbances | 4.83 ± 1.77 | 5.14 ± 1.68 | <0.0001 |
| Systemic symptoms | 4.83 ± 1.33 | 5.24 ± 1.28 | <0.0001 |
| Worry | 5.11 ± 1.55 | 5.32 ± 1.48 | 0.0005 |
| Total CLDQ-MASH | 5.03 ± 1.17 | 5.35 ± 1.09 | <0.0001 |
| Item | Type 2 diabetes | No type 2 diabetes | p values |
| N | 1,816 | 992 | |
| Activity | 5.26 ± 1.52 | 5.52 ± 1.40 | <0.0001 |
| Digestive symptoms and diet | 5.47 ± 1.28 | 5.61 ± 1.23 | 0.0071 |
| Emotional well-being | 5.42 ± 1.27 | 5.50 ± 1.25 | 0.10 |
| Fatigue | 4.47 ± 1.47 | 4.60 ± 1.48 | 0.0341 |
| Sleep disturbances | 4.85 ± 1.76 | 5.07 ± 1.71 | 0.0011 |
| Systemic symptoms | 4.86 ± 1.32 | 5.13 ± 1.33 | <0.0001 |
| Worry | 5.15 ± 1.53 | 5.21 ± 1.53 | 0.31 |
| Total CLDQ-MASH | 5.07 ± 1.17 | 5.23 ± 1.12 | 0.0004 |
| Item | Depression | No depression | p values |
| N | 697 | 2,072 | |
| Activity | 4.67 ± 1.62 | 5.58 ± 1.36 | <0.0001 |
| Digestive symptoms and diet | 5.03 ± 1.38 | 5.68 ± 1.18 | <0.0001 |
| Emotional well-being | 4.72 ± 1.39 | 5.70 ± 1.11 | <0.0001 |
| Fatigue | 3.76 ± 1.48 | 4.77 ± 1.38 | <0.0001 |
| Sleep disturbances | 4.32 ± 1.80 | 5.13 ± 1.68 | <0.0001 |
| Systemic symptoms | 4.38 ± 1.35 | 5.15 ± 1.26 | <0.0001 |
| Worry | 4.57 ± 1.65 | 5.37 ± 1.44 | <0.0001 |
| Total CLDQ-MASH | 4.49 ± 1.20 | 5.34 ± 1.06 | <0.0001 |
| Clinically overt fatigue | No fatigue | p values | |
| N | 369 | 2,402 | |
| Activity | 4.66 ± 1.53 | 5.46 ± 1.45 | <0.0001 |
| Digestive symptoms and diet | 5.13 ± 1.30 | 5.57 ± 1.25 | <0.0001 |
| Emotional well-being | 4.94 ± 1.28 | 5.53 ± 1.24 | <0.0001 |
| Fatigue | 3.67 ± 1.41 | 4.64 ± 1.44 | <0.0001 |
| Sleep disturbances | 4.49 ± 1.73 | 5.00 ± 1.74 | <0.0001 |
| Systemic symptoms | 4.48 ± 1.32 | 5.03 ± 1.32 | <0.0001 |
| Worry | 4.71 ± 1.57 | 5.23 ± 1.52 | <0.0001 |
| Total CLDQ-MASH | 4.58 ± 1.10 | 5.21 ± 1.14 | <0.0001 |
| Insomnia or sleep disorders | No sleep disorders | p values | |
| N | 400 | 1951 | |
| Activity | 4.93 ± 1.57 | 5.46 ± 1.44 | <0.0001 |
| Digestive symptoms and diet | 5.10 ± 1.36 | 5.57 ± 1.25 | <0.0001 |
| Emotional well-being | 5.06 ± 1.35 | 5.56 ± 1.21 | <0.0001 |
| Fatigue | 4.10 ± 1.47 | 4.59 ± 1.46 | <0.0001 |
| Sleep disturbances | 4.04 ± 1.76 | 5.10 ± 1.68 | <0.0001 |
| Systemic symptoms | 4.43 ± 1.30 | 5.05 ± 1.30 | <0.0001 |
| Worry | 4.77 ± 1.67 | 5.22 ± 1.50 | <0.0001 |
| Total CLDQ-MASH | 4.63 ± 1.17 | 5.22 ± 1.13 | <0.0001 |
| Histologic F3–F4 | Histologic F0–F2 | p values | |
| N | 1,917 | 868 | |
| Activity | 5.33 ± 1.46 | 5.41 ± 1.55 | 0.0316 |
| Digestive symptoms and diet | 5.50 ± 1.27 | 5.56 ± 1.24 | 0.37 |
| Emotional well-being | 5.46 ± 1.23 | 5.44 ± 1.31 | 0.62 |
| Fatigue | 4.50 ± 1.46 | 4.55 ± 1.49 | 0.28 |
| Sleep disturbances | 4.91 ± 1.73 | 4.99 ± 1.77 | 0.16 |
| Systemic symptoms | 4.91 ± 1.33 | 5.05 ± 1.33 | 0.0091 |
| Worry | 5.11 ± 1.53 | 5.31 ± 1.52 | 0.0002 |
| Total CLDQ-MASH | 5.10 ± 1.14 | 5.19 ± 1.18 | 0.0281 |
| ELF ≥11.3 | ELF <11.3 | p values | |
| N | 245 | 2,078 | |
| Activity | 5.03 ± 1.50 | 5.41 ± 1.47 | <0.0001 |
| Digestive symptoms and diet | 5.26 ± 1.42 | 5.51 ± 1.26 | 0.0183 |
| Emotional well-being | 5.36 ± 1.23 | 5.49 ± 1.25 | 0.07 |
| Fatigue | 4.27 ± 1.46 | 4.54 ± 1.47 | 0.0053 |
| Sleep disturbances | 4.72 ± 1.82 | 4.93 ± 1.73 | 0.11 |
| Systemic symptoms | 4.67 ± 1.38 | 4.97 ± 1.31 | 0.0019 |
| Worry | 4.98 ± 1.58 | 5.16 ± 1.54 | 0.07 |
| Total CLDQ-MASH | 4.90 ± 1.19 | 5.14 ± 1.15 | 0.0021 |
| Liver stiffness by transient elastography ≥12 kPa | <12 kPa | p values | |
| N | 969 | 808 | |
| Activity | 5.24 ± 1.52 | 5.45 ± 1.48 | 0.0016 |
| Digestive symptoms and diet | 5.43 ± 1.30 | 5.58 ± 1.23 | 0.0204 |
| Emotional well-being | 5.43 ± 1.25 | 5.45 ± 1.27 | 0.54 |
| Fatigue | 4.43 ± 1.48 | 4.61 ± 1.45 | 0.0146 |
| Sleep disturbances | 4.86 ± 1.72 | 4.97 ± 1.75 | 0.10 |
| Systemic symptoms | 4.87 ± 1.34 | 5.03 ± 1.33 | 0.0076 |
| Worry | 5.10 ± 1.55 | 5.33 ± 1.51 | 0.0003 |
| Total CLDQ-MASH | 5.05 ± 1.17 | 5.20 ± 1.15 | 0.0059 |
P values for comparison across the patient groups are returned by the Mann-Whitney test. CLDQ, Chronic Liver Disease Questionnaire; MASH, metabolic dysfunction-associated steatohepatitis.
Notably, in the context of liver disease severity, the CLDQ-MASH was able to discriminate individuals with vs. without histologic advanced fibrosis (p <0.05 for three domains and the total score), as well as with high ELF score (ELF ≥11.3 vs. <11.3: p <0.05 for four of seven domains, p <0.10 for six of seven domains) and high LSM by transient elastography (≥12 kPa vs. <12 kPa: p <0.05 for five of seven domains and the total score) (Table 4).
Correlations of CLDQ-MASH domains with the domains of widely used and extensively validated SF-36 (available for n = 1,691 individuals from the testing set) and FACIT-F (n = 442) are summarized in Table 5. As expected, the highest correlated domain was Physical functioning for Activity (rho = +0.78), Mental Health for Emotional well-being (rho = +0.80), Vitality for Fatigue (rho = +0.76), and Bodily pain for Systemic symptoms (rho = +0.72); Fatigue domain of CLDQ-MASH was also highly correlated with Fatigue scale (rho = +0.75) while Worry of CLDQ-MASH was correlated with Emotional well-being of FACIT-F (rho = +0.67) (all p <0.0001) (Table 5). In contrast, there were no markedly highly correlated domains of SF-36 or FACIT-F for the CLDQ-MASH domains of Digestive symptoms and diet and Sleep (Table 5) which could be because of the disease-specific nature of these domains.
Table 5.
Convergent validity of CLDQ-MASH (testing set); Pearson’s correlation (p value).
| HRQL domain/CLDQ-MASH domain | Activity | Digestive symptoms and diet | Emotional well-being | Fatigue | Sleep disturbances | Systemic symptoms | Worry |
|---|---|---|---|---|---|---|---|
| SF-36 | |||||||
| Physical functioning | 0.78 (<0.0001) | 0.48 (<0.0001) | 0.48 (<0.0001) | 0.51 (<0.0001) | 0.41 (<0.0001) | 0.60 (<0.0001) | 0.36 (<0.0001) |
| Role physical | 0.74 (<0.0001) | 0.53 (<0.0001) | 0.56 (<0.0001) | 0.58 (<0.0001) | 0.44 (<0.0001) | 0.60 (<0.0001) | 0.45 (<0.0001) |
| Bodily pain | 0.70 (<0.0001) | 0.52 (<0.0001) | 0.50 (<0.0001) | 0.54 (<0.0001) | 0.44 (<0.0001) | 0.72 (<0.0001) | 0.41 (<0.0001) |
| General health | 0.60 (<0.0001) | 0.48 (<0.0001) | 0.57 (<0.0001) | 0.57 (<0.0001) | 0.47 (<0.0001) | 0.56 (<0.0001) | 0.52 (<0.0001) |
| Vitality | 0.65 (<0.0001) | 0.52 (<0.0001) | 0.67 (<0.0001) | 0.76 (<0.0001) | 0.50 (<0.0001) | 0.60 (<0.0001) | 0.47 (<0.0001) |
| Social functioning | 0.64 (<0.0001) | 0.53 (<0.0001) | 0.70 (<0.0001) | 0.57 (<0.0001) | 0.47 (<0.0001) | 0.55 (<0.0001) | 0.48 (<0.0001) |
| Role emotional | 0.58 (<0.0001) | 0.50 (<0.0001) | 0.70 (<0.0001) | 0.52 (<0.0001) | 0.45 (<0.0001) | 0.48 (<0.0001) | 0.47 (<0.0001) |
| Mental health | 0.51 (<0.0001) | 0.48 (<0.0001) | 0.80 (<0.0001) | 0.51 (<0.0001) | 0.46 (<0.0001) | 0.47 (<0.0001) | 0.51 (<0.0001) |
| FACIT-F | |||||||
| Physical well-being | 0.73 (<0.0001) | 0.58 (<0.0001) | 0.65 (<0.0001) | 0.66 (<0.0001) | 0.47 (<0.0001) | 0.67 (<0.0001) | 0.54 (<0.0001) |
| Emotional well-being | 0.51 (<0.0001) | 0.50 (<0.0001) | 0.69 (<0.0001) | 0.49 (<0.0001) | 0.42 (<0.0001) | 0.48 (<0.0001) | 0.67 (<0.0001) |
| Social well-being | 0.11 (0.03) | 0.11 (0.02) | 0.18 (0.0001) | 0.10 (0.03) | 0.16 (0.0007) | 0.14 (0.004) | 0.09 (0.07) |
| Functional well-being | 0.52 (<0.0001) | 0.39 (<0.0001) | 0.49 (<0.0001) | 0.41 (<0.0001) | 0.46 (<0.0001) | 0.41 (<0.0001) | 0.36 (<0.0001) |
| Fatigue scale | 0.75 (<0.0001) | 0.55 (<0.0001) | 0.72 (<0.0001) | 0.75 (<0.0001) | 0.52 (<0.0001) | 0.66 (<0.0001) | 0.56 (<0.0001) |
| Other parameters | |||||||
| Age, years | -0.04 (0.03) | 0.08 (<0.0001) | 0.12 (<0.0001) | 0.10 (<0.0001) | 0.03 (0.17) | -0.05 (0.01) | 0.12 (<0.0001) |
| BMI | -0.20 (<0.0001) | -0.09 (<0.0001) | -0.10 (<0.0001) | -0.18 (<0.0001) | -0.11 (<0.0001) | -0.19 (<0.0001) | -0.08 (<0.0001) |
| ELF score | -0.13 (<0.0001) | -0.06 (0.008) | -0.03 (0.19) | -0.06 (0.003) | -0.04 (0.04) | -0.12 (<0.0001) | -0.05 (0.01) |
| FIB-4 score | -0.02 (0.26) | 0.00 (0.84) | 0.05 (0.02) | 0.02 (0.30) | 0.02 (0.38) | -0.03 (0.12) | -0.02 (0.24) |
| Liver stiffness, kPa | -0.09 (<0.0001) | -0.10 (<0.0001) | -0.05 (0.04) | -0.09 (0.0003) | -0.04 (0.12) | -0.07 (0.002) | -0.08 (0.0008) |
CLDQ, Chronic Liver Disease Questionnaire; ELF, Enhanced Liver Fibrosis; FACIT-F, Functional Assessment of Chronic Illness Therapy – Fatigue; FIB-4, Fibrosis 4; HRQL, health-related quality of life; LSM, liver stiffness measurement; MASH, metabolic dysfunction-associated steatohepatitis; SF-36, Short-Form 36.
Negative correlations of all CLDQ-MASH domains scores with BMI ranged from -0.08 (Worry) to -0.20 (Activity) (all p <0.0001) (Table 5). In addition, two NITs (LSM by transient elastography and ELF score) were significantly negatively correlated with six of seven domains of CLDQ-MASH each (rho up to -0.13, p <0.05) (Table 5).
Responsiveness
For assessment of responsiveness to changes in liver disease severity indicators, we used a subsample of MASH individuals with both baseline and 1-year ELF or LSMs (available for 75% of included individuals with MASH). Using those and previously published cut-offs for the two NITs,29 we found that CLDQ-MASH was responsive to both improvement (-0.8) and worsening (+0.8) of ELF scores (p <0.05 for six of seven domains and the total score) as well as changes, particularly improvement (-4.6 kPa), in LSM by transient elastography (p <0.05 for five of seven domains and the total score) (Table 6).
Table 6.
Responsiveness of CLDQ-MASH domain scores to changes (Δ) in fibrosis NITs (ELF and LSM by transient elastography).
| CLDQ-MASH domain | ΔELF <-0.8 | -0.8 ≤ΔELF <+0.8 | ΔELF ≥+0.8 | p values |
|---|---|---|---|---|
| Activity | 0.24 ± 0.06 (0.0005) | -0.03 ± 0.02 (0.71) | -0.19 ± 0.06 (0.0029) | 0.0001 |
| Digestive symptoms and diet | 0.25 ± 0.06 (<0.0001) | 0.08 ± 0.02 (<0.0001) | -0.10 ± 0.06 (0.12) | 0.0002 |
| Emotional well-being | 0.13 ± 0.06 (0.0080) | 0.06 ± 0.02 (0.0032) | -0.07 ± 0.05 (0.12) | 0.0050 |
| Fatigue | 0.31 ± 0.07 (0.0001) | 0.06 ± 0.02 (0.0070) | -0.04 ± 0.06 (0.80) | 0.0010 |
| Sleep disturbances | 0.08 ± 0.09 (0.48) | 0.04 ± 0.03 (0.14) | 0.07 ± 0.08 (0.40) | 0.99 |
| Systemic symptoms | 0.14 ± 0.05 (0.0280) | 0.02 ± 0.02 (0.34) | -0.05 ± 0.05 (0.23) | 0.0450 |
| Worry | 0.60 ± 0.07 (<0.0001) | 0.42 ± 0.03 (<0.0001) | 0.17 ± 0.07 (0.0015) | 0.0002 |
| Total CLDQ-MASH | 0.25 ± 0.05 (<0.0001) | 0.09 ± 0.02 (<0.0001) | -0.03 ± 0.04 (0.70) | 0.0001 |
| CLDQ-MASH domain | ΔLSM <-4.6 kPa | -4.6 kPa ≤ΔLSM <+4.6 kPa | ΔLSM ≥+4.6 kPa | p values |
| Activity | -0.00 ± 0.05 (0.77) | -0.10 ± 0.03 (0.0265) | -0.09 ± 0.06 (0.09) | 0.15 |
| Digestive symptoms and diet | 0.16 ± 0.05 (0.0011) | -0.02 ± 0.03 (0.81) | -0.01 ± 0.06 (0.68) | 0.0199 |
| Emotional well-being | 0.08 ± 0.05 (0.14) | -0.00 ± 0.03 (0.78) | -0.09 ± 0.05 (0.0366) | 0.0280 |
| Fatigue | 0.06 ± 0.06 (0.29) | 0.03 ± 0.03 (0.59) | -0.02 ± 0.06 (0.87) | 0.73 |
| Sleep disturbances | 0.11 ± 0.07 (0.09) | -0.07 ± 0.05 (0.11) | 0.07 ± 0.08 (0.29) | 0.0202 |
| Systemic symptoms | 0.03 ± 0.05 (0.49) | -0.07 ± 0.03 (0.0024) | 0.03 ± 0.05 (0.27) | 0.0258 |
| Worry | 0.56 ± 0.06 (<0.0001) | 0.30 ± 0.04 (<0.0001) | 0.24 ± 0.07 (0.0003) | 0.0006 |
| Total CLDQ-MASH | 0.14 ± 0.04 (0.0002) | 0.01 ± 0.02 (0.55) | 0.02 ± 0.04 (0.95) | 0.0065 |
Each cell shows mean ± SE domain score change (p value for comparison to zero). P-value for comparison across the patient groups is returned by the Mann-Whitney test. CLDQ, Chronic Liver Disease Questionnaire; ELF, Enhanced Liver Fibrosis; LSM, liver stiffness measurement; MASH, metabolic dysfunction-associated steatohepatitis.
Discussion
This study describes the validation of a disease-specific HRQL instrument for patients with MASH (CLDQ-MASH). As a member of the CLDQ family that has been in use for 25 years, this instrument was validated based on the methodology that has stood the test of time for developing disease-specific HRQL instruments.[20], [21], [22], [23], [24], [25] As the diagnostic criteria for NASH was recently changed to MASH, there is a need to have a validated disease-specific instrument for assessment of HRQL in recently designated persons with MASH.
The new CLDQ-MASH has seven domains with good to excellent internal consistency as shown by Cronbach alpha of up to 0.93 and good item-to-domain correlations. Additionally, CLDQ-MASH has excellent known-groups validity based on demographic factors, the presence of comorbidities, various symptoms to include those expected to be the most relevant for specific domains of the instrument (e.g. clinically over fatigue for the domain of Fatigue, history of depression for Emotional well-being, history of sleep disorders for Sleep disturbances), and severity of liver disease by both biopsy and NITs. Furthermore, using two extensively validated generic HRQL instruments (SF-36 and FACIT-F) and a number of clinically relevant variables, CLDQ-MASH returned excellent convergent validity via high correlations with the pertinent domains. It is important to note that although we were unable to assess test-retest reliability of CLDQ-MASH in this study, all of the items included in the final version of CLDQ-MASH had undergone this step during development of CLDQ-NAFLD/NASH.20 Finally, we have shown that the instrument was sensitive to significant changes in markers of liver disease severity to include the ELF score and widely used LSM by transient elastography. These data support the use of CLDQ-MASH as a valid HRQL instrument for patients with MASH to be used in observational clinical studies or clinical trials.
While four out of seven domains of CLDQ-MASH were structured similarly to those of CLDQ-NAFLD/NASH, two domains were substantially reorganized (and, therefore, renamed) and one more domain was added in CLDQ-MASH. Among those, the newly designated domain of Digestive symptoms and diet highlights importance of the respective symptomatology among patients with MASH. The domain of Sleep, although not present in the original CLDQ-NAFLD/NASH, was found to be relevant in other etiology-specific instruments of the family (CLDQ-PBC, CLDQ-PSC, CLDQ-HBV). In this context, as CLDQ-MASH has similarly structured items from partially overlapping domains, it will allow not only to assess HRQL among patients with MASH, but also to compare it with HRQL of patients from other CLD designations which may be essential for epidemiologic and disease-burden studies.
Given that the set of items originally chosen for NAFLD/NASH underwent item reduction and factor analysis in patients with MASH exclusively, we believe that the newly designed instrument is better suited to this patient group. However, we would like to emphasize that for studies that are currently using CLDQ-NAFLD/NASH, the data can be analyzed both using the previously developed scoring scheme for CLDQ-NAFLD/NASH as well as the new scheme developed for CLDQ-MASH. Another strength of the study is the size of the study cohort and the fact that patients in the source database were enrolled from multiple countries.19 This approach provides additional support for validity of this instrument to be used in different regions.
The limitations of the study include the lack of certain clinical subgroups in the validation sample such as patients with major non-hepatic comorbidities, patients with metabolic dysfunction- and alcohol-related liver disease (MetALD), as well as patients with more advanced liver disease with hepatic decompensation. This is important because in patients with MASH-related decompensated cirrhosis, CLDQ-MASH may have more floor effects and one may not be able to discern their lower HRQL. Another limitation is the lack of significant correlation of some CLDQ-MASH domains with stage of disease by histology and by changes in NITs (i.e. Emotional well-being domain, Sleep disturbances domain). Additional studies are required to confirm generalizability of the instrument’s psychometric properties to other groups, better understanding the floor/ceiling effects in patients with advanced cirrhosis, and correlation of domains with NITs using larger studies are needed.
In summary, CLDQ-MASH is a disease-specific HRQL instrument specially tailored for patients with MASH. It has excellent psychometric properties to include internal consistency and various indicators of validity and, therefore, can be used in clinical research and clinical trials that enroll patients with MASH. In this context, CLDQ-MASH adds to the PRO tools available for assessment of patient experience with this important liver disease and its outcomes.30,31
Abbreviations
CLD, chronic liver disease; CLDQ, Chronic Liver Disease Questionnaire; ELF, Enhanced Liver Fibrosis; FACIT-F, Functional Assessment of Chronic Illness Therapy – Fatigue; FIB-4, Fibrosis 4; HRQL, health-related quality of life; LSM, liver stiffness measurement; MASH, metabolic dysfunction-associated steatohepatitis; MASLD, metabolic dysfunction-associated steatotic liver disease; MetALD, metabolic dysfunction- and alcohol-related liver disease; NAFLD, non-alcoholic fatty liver disease; NASH, non-alcoholic steatohepatitis; NIT, non-invasive test; PRO, patient reported outcome; SF-36, Short-Form 36.
Financial support
The Study was supported by the Center for Outcomes Research in Liver Disease, Washington DC.
Authors’ contributions
Conceptualization: ZMY. Data acquisition: IY, AR. Data analysis: MS. Manuscript writing: ZMY, MS, IY, AR. Critical review of final version: ZMY, IY, AR and MS.
Data availability statement
Data used in this study can be requested from the corresponding author for research purposes.
Conflicts of interest
ZMY has received research funding and/or served as consultant to Intercept, CymaBay, Boehringer Ingelheim, BMS, GSK, NovoNordisk, Ipsen, AstraZeneca, Siemens, Madridgal, Merck, Abbott. None of the other authors have conflicts to disclose.
Please refer to the accompanying ICMJE disclosure forms for further details.
Acknowledgements
CLDQ, CLDQ-NAFLD, and CLDQ-MASH were used in the study under permission granted by the copyright holder of these instruments LPRO LLC.
Footnotes
Supplementary data to this article can be found online at https://doi.org/10.1016/j.jhepr.2024.101276.
Supplementary data
The following are the Supplementary data to this article:
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
Data used in this study can be requested from the corresponding author for research purposes.