Abstract
BACKGROUND
The albumin-bilirubin (ALBI) score is a marker of liver function and prognosis in hepatocellular carcinoma, with its utility being expanded to various liver conditions. However, its role in predicting long-term outcomes in patients with metabolic-associated steatotic liver disease (MASLD) remains unknown.
AIM
To determine the ability of the ALBI score in predicting the 8-year liver-related complications and all-cause mortality in MASLD.
METHODS
We conducted a retrospective longitudinal cohort study of 1163 patients with MASLD. MASLD was defined by a controlled attenuation parameter of > 254 dB/m on transient elastography, at least one cardiometabolic risk factor, and no excessive alcohol consumption. Odds ratio regression was employed to create based-prognostic scores with and without ALBI. The predictive accuracy of both scores, the ALBI score, and fibrosis-4 (FIB-4) were assessed using area under the receiving operating characteristic curve (AUROC) analysis and compared using the DeLong test.
RESULTS
Over 8 years, 100 (8.6%) participants of liver-related complications, and 86 (7.4%) died (30.2% of prior liver complications). ALBI had greater accuracy for predicting liver-related complications [AUROC = 0.72, 95% confidence interval (CI): 0.66-0.77] compared with the based-prognostic score (AUROC = 0.67, 95%CI: 0.62-0.73) and FIB-4 (AUROC = 0.64, 95%CI: 0.58-0.70). Additionally, ALBI was superior to the based-prognostic score and FIB-4 (AUROC = 0.81, 95%CI: 0.76-0.86 vs AUROC = 0.78, 95%CI: 0.72-0.83 and AUROC = 0.72, 95%CI: 0.65-0.78, respectively) for predicting all-cause mortality. Incorporating ALBI improved the prognostic score’s accuracy for both outcomes (liver complications: AUROC = 0.74, 95%CI: 0.68-0.79; all-cause mortality: AUROC = 0.83, 95%CI: 0.79-0.88).
CONCLUSION
The ALBI score is a robust and independent predictor of long-term liver-related complications and all-cause mortality in patients with MASLD. ALBI may have potential clinical applications for long-term risk stratification in MASLD management.
Keywords: Albumin-bilirubin, Metabolic-associated steatotic liver disease, Survival, Hepatic outcomes, Risk prediction
Core Tip: The albumin-bilirubin (ALBI) score, which was developed for hepatocellular carcinoma, showed a strong predictive value for long-term liver-related complications and all-cause mortality in patients with metabolic-associated steatotic liver disease (MASLD). In a cohort of 1163 patients with MASLD, ALBI outperformed fibrosis-4 and the existing prognostic models. Incorporating ALBI significantly improved the predictive accuracy for long-term complications and mortality, suggesting its potential role as a valuable and noninvasive tool for long-term risk stratification in MASLD.
INTRODUCTION
The albumin-bilirubin (ALBI) score was initially developed as a simple, objective, and noninvasive method to assess the prognosis of patients with hepatocellular carcinoma (HCC)[1]. Recently, the application of the ALBI score has been broadened to predict outcomes in patients with chronic liver diseases and cirrhosis[2-4]. Unlike traditional liver function scoring systems such as the Child-Pugh and the model for end-stage liver disease scores, the ALBI score is calculated based on serum albumin and bilirubin levels only, making it an objective and standardized tool for assessing hepatic function. Its utility has been validated across various liver diseases, including chronic viral hepatitis B (HBV)[3,5,6] and primary biliary cholangitis[7]. The ALBI score’s simplicity and precision have resulted in its acceptance as a predictive indicator for cirrhosis-related morbidity and mortality, enhancing risk stratification in clinical practice[8]. For HCC, the ALBI score is used to predict survival rates in patients undergoing various treatments[9], including liver resection[10,11], transarterial chemoembolization[12,13], and systemic therapies[14,15]. Studies have shown that the ALBI score has a higher predictive ability relative to traditional liver function models, especially in patients with cirrhosis[1,4,8]. Additionally, an increased ALBI score is a robust indicator of short- and long-term mortality in individuals with chronic HBV[16] and hepatitis B-related cirrhosis[5].
The ALBI score is also useful for predicting patient outcomes across other medical conditions, including heart failure[17-19], hypertrophic cardiomyopathy[20], and perioperative risk in cardiac surgery[21]. Research has correlated the ALBI score with sepsis-related mortality, indicating its capacity to evaluate systemic inflammation and multiorgan failure in critically ill patients[22].
However, the specific role of the ALBI score in forecasting mortality in individuals with metabolic-associated steatotic liver disease (MASLD) remains unknown. Therefore, we assessed the efficacy of the baseline ALBI score in predicting liver-related complications and all-cause morbidity in a large MASLD population.
MATERIALS AND METHODS
Study design and population
We conducted retrospective longitudinal study at Vajira Hospital from January 2017 to December 2023 and enrolled patients with MASLD. MASLD was defined as the presence of liver steatosis identified by a controlled attenuation parameter (CAP) value of > 254 dB/m along with at least one cardiometabolic risk factor, including overweight/obesity, prediabetes or type 2 diabetes mellitus, dyslipidemia, and/or hypertension, and in the absence of risky alcohol intake (average ≥ 20 g for women or ≥ 30 g for men per day)[23]. We excluded patients who were aged < 18 years or pregnant and who had prior liver-related complications.
Transient elastography
Transient elastography was performed using FibroScan® (Echosens, Paris, France). The measurements were considered to have acceptable reliability and accuracy when at least 10 valid readings were obtained, and the interquartile range (IQR)-to-median ratio did not exceed 30%.
Liver steatosis and fibrosis were assessed using the CAP, measured in decibels per meter (dB/m), and liver stiffness measurement (LSM), measured in kilopascals (kPa), respectively. Based on the CAP values, patients were classified into three groups: Mild steatosis (S1), moderate steatosis (S2), and severe steatosis (S3). The CAP cut-off values were stratified based on the type of FibroScan probe used as follows: (1) M probe S1: 254-283 dB/m, S2: 283-312 dB/m, and S3: > 312 dB/m; and (2) XL probe S1: 278-281 dB/m, S2: 281-327 dB/m, and S3: > 327 dB/m. Patients were classified into five stages based on the LSM values as follows: Normal (F0), non-advanced fibrosis (F1-F2), and advanced fibrosis (F3-F4). The LSM cut-off values were stratified by the type of FibroScan probe used as follows: (1) M probe F0: < 6.6 kPa, F1: 6.6-7.8 kPa, F2: 7.8-9.9 kPa, F3: 9.9-13.3 kPa and F4: > 13.3 kPa; and (2) XL probe F0: < 6.6 kPa, F1: 6.6-7.0 kPa, F2: 7.0-9.2 kPa, F3: 9.2-13.2 kPa and F4: > 13.2 kPa[24].
Data collection
Baseline demographics of cardiometabolic risk factors, including body mass index (BMI), concomitant liver disease, and liver function tests, and fibrosis-4 index (FIB-4) and LSM values were collected. The ALBI formula calculates two main components of liver function: Bilirubin (a measure of excretion function) and albumin (a measure of synthetic function). The ALBI score was calculated using the following formula: (Log10 bilirubin in μmol/L × 0.66) + [albumin in g/L × (-0.085)]. After calculating the score, patients are categorized into three different levels based on defined threshold values, similar to the classification used for HCC: Grade 1: ALBI score ≤ -2.60, which generally indicates better liver function; Grade 2: ALBI score > -2.60 to -1.39, indicating moderately impaired liver function; Grade 3: ALBI score > -1.39, indicating severely impaired liver function[25]. The advanced fibrosis group was defined by a FIB-4 score of ≥ 1.3 combined with LSM stage indicative of fibrosis (stages F3-F4). The time to the diagnosis of the first liver-related complication (ascites, hepatic encephalopathy, variceal bleeding, spontaneous bacterial peritonitis including systemic infection) or all-cause mortality was censored across the 8-year follow-up period. Data were extracted from the Electronic Public Hospital Information System of Vajira Hospital. All participant data were reviewed with stringent secrecy. This study was approved by the Human Research Ethics Committee of Navamindradhiraj University (No. COA 111/2567).
Statistical analysis
Statistical analyses were performed using Stata version 13.0 (Stata Corporation, College Station, TX, United States). Categorical data are presented using frequency (n) with percentage (%). Continuous variables are presented as mean with standard deviation or median with IQR, depending on their distribution. The normality of the continuous data was assessed using K-Squared test and the Shapiro-Wilk test. Pearson’s χ2 or Fisher’s exact tests were used to compare the categorical variables between patients with MASLD who developed liver-related complications and those who did not. Continuous variables were compared using the Student’s t-test or the Wilcoxon rank-sum test, as appropriate. A P value of < 0.05 was considered statistically significant.
Univariable and multivariable odds ratio (OR) regression (binary logistic regression) were conducted to develop a prognostic score to predict the 8-year liver-related complications and all-cause mortality. Baseline cardiometabolic risk factors and noninvasive fibrosis assessment, excluding the ALBI score, were used to construct the based-prognostic score. To evaluate the added prognostic value of the ALBI score, an extended prognostic score incorporating it was developed. Prognostic scores were calculated by summing the regression coefficient (β) of significant prognostic factors, expressed as the natural logarithm (ln) of the OR, as shown in formulas f1 and f2.
(f1): Prognostic score = ln (ORconstant) + [X1 × ln (ORx1)] + [X2 × ln (ORx2)] + [X3 × ln (ORx3)] + … + [Xn × ln (ORxn)].
(f2): Prognostic score plus ALBI = ln (ORconstant) + [X1 × ln (ORx1)] + [X2 × ln (ORx2)] + [X3 × ln (ORx3)] + … + [Xn × ln (ORxn)] + [ALBI × ln (ORALBI)].
The predictive accuracy of the based-prognostic score, the based-prognostic score plus ALBI, ALBI alone, and FIB-4 was evaluated using area under the receiving operating characteristic curve (AUROC) analysis. The AUROC and 95% confidence interval (CI), along with sensitivity, specificity, positive and negative predictive values, positive and negative likelihood ratios, and overall classification accuracy, were calculated for each score and liver marker in forecasting the 8-year liver-related complications and all-cause mortality. Optimal cut-off points were established utilizing the Euclidean distance criterion to maximize both sensitivity and specificity.
The Kaplan-Meier method with the log-rank test and Cox regression analysis were used to estimate and compare the risk of liver-related complications and all-cause mortality between the two groups of participants based on the optimal cut-off points of the ALBI score based on the AUROC analysis. The Kaplan-Meier plot, hazard ratio (HR), 95%CI, and P value were documented.
The DeLong test was employed to assess the additional prognostic value of the ALBI score by comparing the baseline prognostic score with baseline prognostic score plus the ALBI score. The performance of the ALBI score alone was compared with that of FIB-4. A subgroup study of fibrosis severity was also conducted to evaluate the predictive accuracy of the ALBI score relative to FIB-4.
RESULTS
Overall, data of 1163 patients with MASLD were analyzed to determine the 8-year incidence of liver-related complications and overall mortality. The descriptive demographic characteristics are presented in Table 1. The median age was 56.0 years (IQR: 46.0 to 63.0), with 587 patients (50.5%) being men. The median BMI was 26.4 kg/m2. Cardiometabolic risk factors were prevalent; 82.3% of patients were overweight, 57.8% had hypertension, 81.6% had prediabetes and type 2 diabetes mellitus, 29.9% had hypertriglyceridemia, and 30.3% had low high-density lipoprotein levels. Concomitant liver illness was noted in 37.8% of patients with viral hepatitis. The median values for CAP and LSM were 298.0 (IQR: 275.0 to 329.0) dB/m and 6.9 (IQR: 5.2 to 11.6) kPa, respectively. The median FIB-4 was 1.3 (IQR: 0.8 to 2.0) and the median ALBI score was -3.0 (IQR: -3.2 to -2.7). At baseline, 964 (82.9%), 178 (15.3%), and 21 (1.8%) patients were categorized as ALBI grades 1, 2, and 3, respectively. Advanced fibrosis was identified in 261 patients (22.4%).
Table 1.
Baseline characteristics of metabolic-associated steatotic liver disease participants, n (%)
| Characteristics | Total (n = 1163) |
8-year liver-related complications
|
8-year all-cause mortality
|
||||
|
Yes (n = 100)
|
No (n = 1063)
|
P value1
|
Yes (n = 86)
|
No (n = 1077)
|
P value1
|
||
| Age (years), median IQR | 56.0 (46.0 to 63.0) | 61.5 (52.0 to 68.0) | 55.0 (45.0 to 63.0) | < 0.001a | 62.0 (54.0 to 70.0) | 55.0 (45.0 to 63.0) | < 0.001a |
| Male | 587 (50.5) | 50 (50.0) | 537 (50.5) | 0.921 | 52 (60.5) | 535 (49.7) | 0.054 |
| BMI (kg/m2), median IQR | 26.4 (24.0 to 29.3) | 27.6 (24.8 to 31.2) | 26.3 (23.9 to 29.2) | 0.034a | 25.8 (23.1 to 27.7) | 26.4 (24.0 to 29.4) | 0.038a |
| Overweight/obesity | 957 (82.3) | 83 (83.0) | 874 (82.2) | 0.845 | 61 (70.9) | 896 (83.2) | 0.004a |
| Hypertension | 658 (57.8) | 66 (68.0) | 592 (56.9) | 0.033a | 50 (62.5) | 608 (57.5) | 0.379 |
| Prediabetes/diabetes | 809 (81.6) | 81 (88.0) | 728 (81.0) | 0.096 | 65 (86.7) | 744 (81.2) | 0.242 |
| Hypertriglyceridemia | 310 (29.9) | 33 (36.3) | 277 (29.3) | 0.165 | 21 (28.0) | 289 (30.0) | 0.710 |
| Low HDL | 312 (30.3) | 35 (38.0) | 277 (29.5) | 0.090 | 25 (34.3) | 287 (30.0) | 0.445 |
| AST, median IQR | 30.0 (23.0 to 40.0) | 35.0 (24.0 to 57.0) | 29.0 (23.0 to 39.0) | 0.003a | 43.0 (25.0 to 65.0) | 29.0 (23.0 to 39.0) | < 0.001a |
| ALT, median IQR | 33.0 (20.0 to 51.0) | 36.5 (21.5 to 54.0) | 33.0 (20.0 to 50.0) | 0.390 | 36.0 (22.0 to 55.0) | 33.0 (20.0 to 51.0) | 0.358 |
| Albumin (g/dL), median IQR | 4.2 (4.0 to 4.5) | 3.9 (3.6 to 4.2) | 4.3 (4.0 to 4.5) | < 0.001a | 3.6 (2.8 to 4.1) | 4.3 (4.0 to 4.5) | < 0.001a |
| CAP (dB/m), median IQR | 298.0 (275.0 to 329.0) | 299.0 (278.5 to 325.0) | 298.0 (275.0 to 330.0) | 0.866 | 290.0 (271.0 to 312.0) | 299.0 (275.0 to 331.0) | 0.012a |
| Steatosis grade | 0.418 | 0.030a | |||||
| S1 | 383 (32.9) | 28 (28.0) | 355 (33.4) | 36 (41.9) | 347 (32.2) | ||
| S2 | 359 (30.9) | 36 (36.0) | 323 (30.4) | 30 (34.9) | 329 (30.6) | ||
| S3 | 421 (36.2) | 36 (36.0) | 385 (36.2) | 20 (23.2) | 401 (37.2) | ||
| LSM (kPa), median IQR | 6.9 (5.2 to 11.6) | 8.5 (6.1 to 14.9) | 6.8 (5.1 to 11.0) | < 0.001a | 11.2 (7.6 to 32.5) | 6.8 (5.1 to 10.7) | < 0.001a |
| Fibrosis stage | 0.035a | < 0.001a | |||||
| F0 | 514 (44.2) | 30 (30.0) | 484 (45.5) | 18 (20.9) | 496 (46.0) | ||
| F1 | 127 (10.9) | 11 (11.0) | 116 (10.9) | 4 (4.7) | 123 (11.4) | ||
| F2 | 146 (12.5) | 15 (15.0) | 131 (12.3) | 13 (15.1) | 133 (12.4) | ||
| F3 | 138 (11.9) | 15 (15.0) | 123 (11.6) | 13 (15.1) | 125 (11.6) | ||
| F4 | 238 (20.5) | 29 (29.0) | 209 (19.7) | 38 (44.2) | 200 (18.6) | ||
| FIB-4, median IQR | 1.3 (0.8 to 2.0) | 1.7 (1.1 to 3.6) | 1.2 (0.8 to 1.9) | < 0.001a | 2.1 (1.3 to 4.9) | 1.2 (0.8 to 1.9) | < 0.001a |
| ALBI, median IQR | -3.0 (-3.2 to -2.7) | -2.7 (-2.9 to -2.3) | -3.0 (-3.2 to -2.7) | < 0.001a | -2.5 (-2.9 to -1.5) | -3.0 (-3.2 to -2.8) | < 0.001a |
| ALBI grade | < 0.001a | < 0.001a | |||||
| 1 | 964 (82.9) | 61 (61.0) | 903 (85.0) | 34 (39.5) | 930 (86.3) | ||
| 2 | 178 (15.3) | 28 (28.0) | 150 (14.1) | 33 (38.4) | 145 (13.5) | ||
| 3 | 21 (1.8) | 11 (11.0) | 10 (0.9) | 19 (22.1) | 2 (0.2) | ||
| Advanced fibrosis group | 261 (22.4) | 35 (35.0) | 226 (21.3) | 0.002a | 43 (50.0) | 218 (20.2) | < 0.001a |
| Hepatitis B/C | 358 (37.8) | 24 (25.5) | 334 (39.2) | 0.010a | 39 (53.4) | 319 (36.5) | 0.004a |
| Follow-up duration (years), median IQR | 4.8 (2.5 to 6.3) | 4.9 (2.5 to 6.5) | 4.8 (2.5 to 6.3) | 0.668 | 3.1 (1.8 to 5.0) | 4.9 (2.6 to 6.4) | < 0.001a |
P < 0.05.
P value by Pearson’s χ2 test or Mann-Whitney U test.
IQR: Interquartile range; BMI: Body mass index; HDL: High-density lipoprotein; AST: Aspartate aminotransferase; ALT: Alanine aminotransferase; CAP: Controlled attenuation parameter; LSM: Liver stiffness measurement; ALBI: Albumin-Bilirubin; FIB-4: Fibrosis-4.
Baseline parameters showed that participants who had liver-related complications were significantly older and had a higher BMI compared to those who did not [61.5 years (IQR: 52.0 to 68.0) vs 55.0 years (IQR: 45.0 to 63.0), P < 0.001]; 27.6 kg/m² (IQR: 24.8 to 31.2) vs 26.3 kg/m² (IQR: 23.9 to 29.2), P = 0.034, respectively]. Hypertension was more prevalent among patients with complications (68.0% vs 56.9%, P = 0.033). Patients who died were significantly older than those who survived [62.0 years (IQR: 54.0 to 70.0) vs 55.0 years (IQR: 45.0 to 63.0), P < 0.001].
Participants who developed liver-related complications exhibited a significantly elevated LSM [8.5 kPa (IQR: 6.1 to 14.9) vs 6.8 kPa (IQR: 5.1 to 11.0), P < 0.001], FIB-4 [1.7 (IQR: 1.1 to 3.6) vs 1.2 (IQR: 0.8 to 1.9), P < 0.001], and ALBI [-2.7 (IQR: -2.9 to -2.3) vs -3.0 (IQR: -3.2 to -2.7), P < 0.001]. Patients were more likely to belong to the advanced fibrosis group compared to those who did not experience liver-related complications (35.0% vs 21.3%; P = 0.002).
Patients who died exhibited significantly elevated LSM, FIB-4 and ALBI scores [11.2 kPa (IQR: 7.6 to 32.5) vs 6.8 kPa (IQR: 5.1 to 10.7), P < 0.001; 2.1 (IQR: 1.3 to 4.9) vs 1.2 (IQR: 0.8 to 1.9), P < 0.001; -2.5 (IQR: -2.9 to -1.5) vs -3.0 (IQR: -3.2 to -2.8), P < 0.001, respectively] and had a higher likelihood of being classified in the advanced fibrosis group compared to survivors (50.0% vs 20.2%; P < 0.001).
Over the 8-year follow-up period, 100 (8.6%) patients experienced liver-related complications as follows: Hepatic encephalopathy in 72 patients (72.0%), HCC in 22 patients (22.0%), sepsis in 6 patients (6.0%), and variceal hemorrhage in 2 patients (2.0%). Among the 86 (7.4%) patients who died, 26 (30.2%) had a history of liver-related complications (Table 1).
The based-prognostic score was established using a multivariable logistic regression model that included parameters such as age, hypertension, LSM, and FIB-4 for predicting the 8-year liver-related complications (Supplementary Table 1), and age, CAP, LSM, and FIB-4 for predicting the 8-year mortality (Supplementary Table 2). Results revealed that the based-prognostic score showed moderate accuracy in predicting outcomes, with AUROC values of 0.67 (95%CI: 0.62-0.73) and 0.78 (95%CI: 0.72-0.83) for liver-related complications and mortality, respectively. Notably, these data were subpar in comparison to the baseline ALBI score projections. The baseline ALBI score outperformed the based-prognostic score and FIB-4, showing an AUROC of 0.72 (95%CI: 0.66-0.77) for liver-related complications and 0.81 (95%CI: 0.76-0.86) for all-cause mortality (Table 2). Compared to the ALBI score alone, the ALBI plus based-prognostic score did not significantly enhance its predictive accuracy for liver-related complications (AUROC = 0.74; 95%CI: 0.68-0.79; P = 0.193) and all-cause mortality (AUROC = 0.83; 95%CI: 0.79-0.88; P = 0.152) (Figure 1 and Table 2). Throughout the follow-up period, an elevated ALBI score correlated with a 3.3-fold increase in the risk of liver-related complications (HR = 3.28; 95%CI: 2.17-4.97, P < 0.001) and a 4.4-fold increase in the risk of all-cause mortality (HR = 4.41; 95%CI: 2.74-7.10, P < 0.001) (Figure 2).
Table 2.
Prognostic performance of albumin-bilirubin and other non-invasive scores on 8-year liver-related complications and all-cause mortality
|
Scores (n = 1163)
|
8-year liver-related complications
|
8-year all-cause mortality
|
| Based-prognostic score | ||
| AUROC (95%CI) | 0.67 (0.62-0.73) | 0.78 (0.72-0.83) |
| Euclidian cut-off values | ≥ -2.39 | ≥ -2.60 |
| Sensitivity/specificity (%) | 62.89/64.75 | 72.09/72.98 |
| PPV/NPV (%) | 14.25/94.93 | 12.85/96.48 |
| Positive/negative LR | 1.78/0.57 | 2.67/0.38 |
| Correctly classified (%) | 64.59 | 72.91 |
| Based-prognostic score plus ALBI | ||
| AUROC (95%CI) | 0.74 (0.68-0.79) | 0.83 (0.79-0.88) |
| Euclidian cut-off values | ≥ -2.44 | ≥ -2.70 |
| Sensitivity/specificity (%) | 65.98/67.72 | 74.42/75.95 |
| PPV/NPV (%) | 16.00/95.53 | 14.50/97.02 |
| Positive/negative LR | 2.04/0.50 | 3.09/0.34 |
| Correctly classified (%) | 67.57 | 75.84 |
| ALBI | ||
| AUROC (95%CI) | 0.72 (0.66-0.77) | 0.81 (0.76-0.86) |
| Euclidian cut-off values | ≥ -2.82 | ≥ -2.77 |
| Sensitivity/specificity (%) | 66.00/66.60 | 72.09/72.52 |
| PPV/NPV (%) | 15.68/95.42 | 17.32/97.02 |
| Positive/negative LR | 1.98/0.51 | 2.62/0.38 |
| Correctly classified (%) | 66.55 | 72.48 |
| FIB-4 | ||
| AUROC (95%CI) | 0.64 (0.58-0.70) | 0.72 (0.65-0.78) |
| Euclidian cut-off values | ≥ 1.51 | ≥ 1.76 |
| Sensitivity/specificity (%) | 62.00/62.84 | 68.60/71.68 |
| PPV/NPV (%) | 13.57/94.62 | 16.21/96.62 |
| Positive/negative LR | 1.67/0.60 | 2.42/0.44 |
| Correctly classified (%) | 62.77 | 71.45 |
| Comparison of AUROC1 | ||
| Based-prognostic scores vs based-prognostic scores plus ALBI | 0.003a | 0.002a |
| Based-prognostic scores plus ALBI vs ALBI | 0.193 | 0.152 |
| ALBI vs FIB-4 | 0.033a | 0.004a |
P < 0.05.
P value by DeLong test.
AUROC: Area under the receiver operating characteristic curve; ALBI: Albumin-bilirubin; LR: Likelihood ratio; NPV: Negative predictive value; PPV: Positive predictive value; FIB-4: Fibrosis-4; CI: Confidence interval.
Figure 1.
Area under the receiver operating characteristic curve of albumin-bilirubin, fibrosis-4 and prognostic scores from multivariable logistic regression including determinants. A: 8-year liver-related complications; B: 8-year all-cause mortality. AUROC: Area under the receiver operating characteristic curve; ALBI: Albumin-bilirubin; FIB-4: Fibrosis-4.
Figure 2.
Kaplan-Meier plot of estimated. A: 8-year liver-related complications; B: 8-year all-cause mortality according to the optimum cut point of albumin-bilirubin. Short-dashed line with shaded areas indicates a 95% confidence interval. ALBI: Albumin-bilirubin.
In the advanced fibrosis cohort, the ALBI score predicted all-cause mortality more accurately than FIB-4 (AUROC = 0.86; 95%CI: 0.79-0.93 vs AUROC = 0.72; 95%CI: 0.63-0.80; P < 0.001). The ALBI score had superior predictive capability for liver-related complications compared to FIB-4, but the difference was not significant (AUROC = 0.76; 95%CI: 0.67-0.85 vs AUROC = 0.67; 95%CI: 0.56-0.79; P = 0.087) (Figure 3 and Supplementary Table 3).
Figure 3.
Area under the receiver operating characteristic curve of albumin-bilirubin, fibrosis-4 determinants. A: 8-year liver-related complications in advance fibrosis group; B: 8-year all- cause mortality in advance fibrosis group; C: 8-year liver-related complications in non-advance fibrosis group; D: 8-year all caused mortality in non-advance fibrosis group. AUROC: Area under the receiver operating characteristic curve; ALBI: Albumin-bilirubin; FIB-4: Fibrosis-4.
DISCUSSION
Our results revealed that the ALBI score is a robust independent predictor of long-term liver-related complications and overall mortality in adults with MASLD.
Over an 8-year follow-up period, the baseline ALBI score consistently outperformed the baseline FIB-4 and significantly enhanced the predictive accuracy of both outcomes in patients with MASLD with pre-existing cardiometabolic risk. This finding indicates that the ALBI score may offer enhanced long-term risk stratification relative to traditional cardiometabolic risk factors in this population.
Albumin’s diverse qualities render it a significant biomarker in multiple clinical contexts especially in the treatment of liver disease and critical care. In MASLD, increased levels of several inflammatory cytokines is correlated with an increased risk of liver-related and cardiovascular events[26-28]. Albumin, which is a protein synthesized by the liver, exhibits anti-inflammatory and immunomodulatory properties. Thus, albumin may represent not only hepatic synthetic function but also overall systemic health, serving as a marker for the general clinical status and liver-related outcomes.
The baseline FIB-4 index is an effective surrogate screening tool in MASLD for identifying individuals who may require referral to a hepatologist for further assessment, including liver elastography. Triage from hepatology care is acceptable for individuals with low FIB-4 Levels, with dynamic review advised every 2-3 years. Simple noninvasive scoring systems, such as FIB-4, can assist in identifying patients with MASLD who are at risk for developing liver-related complications and increased mortality[29]. In our cohort, most of the patients had low baseline FIB-4 scores, potentially accounting for its restricted prognostic utility regarding long-term outcomes. Age and transaminase levels may be significant factors affecting the dynamic alterations in FIB-4, necessitating additional examinations in subsequent research.
The ALBI score has also been studied in the context of HBV infection. Higher ALBI scores correlate with an increased risk of all-cause mortality in patients with HBV, showing its efficacy in accurately predicting short- and long-term outcomes[16]. Our study introduced a novel approach to evaluate the utility of the ALBI score specifically in patients with MASLD and revealed that it is superior to cardiometabolic risk variables and FIB-4 in predicting liver-related decompensation episodes and all-cause mortality. These findings suggest the utilization of the ALBI score as an effective prognostic tool in the management of MASLD.
Previous studies have reported the efficacy of the ALBI score in forecasting the occurrence of decompensated episodes within 3 years in individuals with compensated cirrhosis[4]. During our qualifying periods, almost 25% of patients with MASLD presented with advanced fibrosis, consistent with the distribution of MASLD severity. Despite the comparatively fewer liver-related incidents in the advanced fibrosis group, the prediction accuracy of the ALBI score remains superior. Furthermore, the ALBI score consistently exhibited a robust prediction capability for the 8-year all-cause mortality irrespective of the liver fibrosis stage. These results highlight the benefits of the ALBI score not only for individuals with significant or advanced fibrosis but also as an important prognostic tool for the wider MASLD demographic.
Current evidence confirms the efficacy of the ALBI score in nonmalignant liver disease[30,31]. The robustness of our data suggests that integrating the ALBI score into standard risk stratification may enhance long-term risk prediction in MASLD, contributing to individualized monitoring strategies or early intervention. In real-world clinical practice, most patients screened for MASLD have ALBI grade 1, hence reinforcing the generalizability of our findings. Notably, the ALBI score alone already enhanced predictive discrimination, underscoring its complementary role in comprehensive risk assessment. Nonetheless, certain diseases, including hemolytic anemia, severe malnutrition, and inflammation, might alter albumin and bilirubin levels, hence affecting the predictive accuracy of the ALBI score.
This study has some limitations. The ALBI score was evaluated only at baseline, restricting our capacity to determine the prognostic significance of temporal variations. Histological confirmation of advanced fibrosis was not performed in the advanced fibrosis subgroup, potentially compromising the accuracy of fibrosis staging. Ultimately, due to the characteristics of this data-driven prospective study, most liver-related complications were documented as hepatic encephalopathy; additional complications, including ascites and esophageal varices, may have been inadequately diagnosed or reported.
Considering the increasing global prevalence of MASLD, our results advocate for the incorporation of the ALBI score into clinical practice as a streamlined, economical, and easily accessible tool for long-term prognostication. Moreover, in the context of a multidisciplinary approach to MASLD, the uniformity of our extensive cohort of over 1000 individuals offers pragmatic assistance for general practitioners, endocrinologists, and hepatologists in evaluating disease prognosis at the initial point of care.
CONCLUSION
The ALBI score was superior to cardiometabolic risk variables and FIB-4 in forecasting long-term liver-related mortality and all-cause mortality in patients with MASLD. The ALBI score also consistently retained its prognostic accuracy irrespective of the liver fibrosis stage. The ALBI score may be an effective tool for prognostic assessment in individuals with MASLD.
Footnotes
Institutional review board statement: The study protocol was approved by the Vajira Institutional Review Board Institutional Review Board, Faculty of Medicine Vajira Hospital (No. COA 111/2567).
Informed consent statement: The informed consent was waived due to our study being retrospective study.
Conflict-of-interest statement: The authors declare that they have no conflict of interest.
STROBE statement: The authors have read the STROBE Statement—a checklist of items, and the manuscript was prepared and revised according to the STROBE Statement-a checklist of items.
Provenance and peer review: Unsolicited article; Externally peer reviewed.
Peer-review model: Single blind
Specialty type: Gastroenterology and hepatology
Country of origin: Thailand
Peer-review report’s classification
Scientific Quality: Grade A, Grade B
Novelty: Grade A, Grade C
Creativity or Innovation: Grade A, Grade C
Scientific Significance: Grade A, Grade C
P-Reviewer: Suresh A, PhD, Assistant Professor, India; Wang CB, PhD, China S-Editor: Fan M L-Editor: A P-Editor: Wang CH
Contributor Information
Supatsri Sethasine, Division of Gastroenterology and Hepatology, Department of Medicine, Faculty of Medicine Vajira Hospital, Navamindradhiraj University, Bangkok 10300, Thailand.
Padoemwut Teerawongsakul, Division of Cardiology, Department of Medicine, Faculty of Medicine Vajira Hospital, Navamindradhiraj University, Bangkok 10300, Thailand.
Witchakorn Ruamtawee, Clinical Research Center, Research Facilitation Division, Faculty of Medicine Vajira Hospital, Navamindradhiraj University, Bangkok 10300, Thailand.
Nutachat Treerasoradaj, Faculty of Medicine Vajira Hospital, Navamindradhiraj University, Bangkok 10300, Thailand.
Huttakan Navadurong, Division of Gastroenterology and Hepatology, Department of Medicine, Faculty of Medicine Vajira Hospital, Navamindradhiraj University, Bangkok 10300, Thailand. huttakan.nav@nmu.ac.th.
Data sharing statement
No additional data are available.
References
- 1.Hsu WF, Chang KC, Chen TH, Lin CH, Lin YC, Tsai MH, Chen PY, Wang HW, Chu CS, Peng CY. Comparison of 10 noninvasive models for predicting overall survival in patients with intermediate-stage hepatocellular carcinoma. Medicine (Baltimore) 2021;100:e27000. doi: 10.1097/MD.0000000000027000. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Oikonomou T, Goulis L, Doumtsis P, Tzoumari T, Akriviadis E, Cholongitas E. ALBI and PALBI Grades Are Associated with the Outcome of Patients with Stable Decompensated Cirrhosis. Ann Hepatol. 2019;18:126–136. doi: 10.5604/01.3001.0012.7904. [DOI] [PubMed] [Google Scholar]
- 3.Wang J, Zhang Z, Yan X, Li M, Xia J, Liu Y, Chen Y, Jia B, Zhu L, Zhu C, Huang R, Wu C. Albumin-Bilirubin (ALBI) as an accurate and simple prognostic score for chronic hepatitis B-related liver cirrhosis. Dig Liver Dis. 2019;51:1172–1178. doi: 10.1016/j.dld.2019.01.011. [DOI] [PubMed] [Google Scholar]
- 4.Navadurong H, Thanapirom K, Wejnaruemarn S, Prasoppokakorn T, Chaiteerakij R, Komolmit P, Treeprasertsuk S. Validation of the albumin-bilirubin score for identifying decompensation risk in patients with compensated cirrhosis. World J Gastroenterol. 2023;29:4873–4882. doi: 10.3748/wjg.v29.i32.4873. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Chen RC, Cai YJ, Wu JM, Wang XD, Song M, Wang YQ, Zheng MH, Chen YP, Lin Z, Shi KQ. Usefulness of albumin-bilirubin grade for evaluation of long-term prognosis for hepatitis B-related cirrhosis. J Viral Hepat. 2017;24:238–245. doi: 10.1111/jvh.12638. [DOI] [PubMed] [Google Scholar]
- 6.Fujita K, Oura K, Yoneyama H, Shi T, Takuma K, Nakahara M, Tadokoro T, Nomura T, Morishita A, Tsutsui K, Himoto T, Masaki T. Albumin-bilirubin score indicates liver fibrosis staging and prognosis in patients with chronic hepatitis C. Hepatol Res. 2019;49:731–742. doi: 10.1111/hepr.13333. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Ito T, Ishigami M, Morooka H, Yamamoto K, Imai N, Ishizu Y, Honda T, Nishimura D, Tada T, Yasuda S, Toyoda H, Kumada T, Fujishiro M. The albumin-bilirubin score as a predictor of outcomes in Japanese patients with PBC: an analysis using time-dependent ROC. Sci Rep. 2020;10:17812. doi: 10.1038/s41598-020-74732-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Sakamaki A, Takamura M, Sakai N, Watanabe Y, Arao Y, Kimura N, Setsu T, Abe H, Yokoo T, Kamimura H, Tsubata S, Waguri N, Ishikawa T, Kawai H, Sugitani S, Sato T, Funakoshi K, Watanabe M, Igarashi K, Kamimura K, Tsuchiya A, Aoyagi Y, Terai S. Longitudinal increase in albumin-bilirubin score is associated with non-malignancy-related mortality and quality of life in patients with liver cirrhosis. PLoS One. 2022;17:e0263464. doi: 10.1371/journal.pone.0263464. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Deng M, Ng SWY, Cheung ST, Chong CCN. Clinical application of Albumin-Bilirubin (ALBI) score: The current status. Surgeon. 2020;18:178–186. doi: 10.1016/j.surge.2019.09.002. [DOI] [PubMed] [Google Scholar]
- 10.Zhang J, Luo Y, Li C, Liu J, Xiang H, Wen T. The combination of the preoperative albumin-bilirubin grade and the fibrosis-4 index predicts the prognosis of patients with hepatocellular carcinoma after liver resection. Biosci Trends. 2019;13:351–357. doi: 10.5582/bst.2019.01212. [DOI] [PubMed] [Google Scholar]
- 11.Endo Y, Tsilimigras DI, Munir MM, Woldesenbet S, Guglielmi A, Ratti F, Marques HP, Cauchy F, Lam V, Poultsides GA, Kitago M, Alexandrescu S, Popescu I, Martel G, Gleisner A, Hugh T, Aldrighetti L, Shen F, Endo I, Pawlik TM. Machine learning models including preoperative and postoperative albumin-bilirubin score: short-term outcomes among patients with hepatocellular carcinoma. HPB (Oxford) 2024;26:1369–1378. doi: 10.1016/j.hpb.2024.07.415. [DOI] [PubMed] [Google Scholar]
- 12.Koonsiripaiboon P, Ruamtawee W, Simasingha N, Tanasoontrarat W, Claimon T, Sethasine S. Efficacy of N-acetylcysteine vs dexamethasone in preventing postembolization syndrome post-transarterial chemoembolization in hepatocellular carcinoma: A randomized controlled trial. World J Gastroenterol. 2025;31:109630. doi: 10.3748/wjg.v31.i31.109630. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Lin PT, Teng W, Jeng WJ, Chen WT, Hsieh YC, Huang CH, Lui KW, Hung CF, Wang CT, Chai PM, Lin CC, Lin CY, Lin SM, Sheen IS. Dynamic Change of Albumin-Bilirubin Score Is Good Predictive Parameter for Prognosis in Chronic Hepatitis C-hepatocellular Carcinoma Patients Receiving Transarterial Chemoembolization. Diagnostics (Basel) 2022;12:665. doi: 10.3390/diagnostics12030665. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Tada T, Kumada T, Toyoda H, Tsuji K, Hiraoka A, Michitaka K, Deguchi A, Ishikawa T, Imai M, Ochi H, Joko K, Shimada N, Tajiri K, Hirooka M, Koizumi Y, Hiasa Y, Tanaka J. Impact of albumin-bilirubin grade on survival in patients with hepatocellular carcinoma who received sorafenib: An analysis using time-dependent receiver operating characteristic. J Gastroenterol Hepatol. 2019;34:1066–1073. doi: 10.1111/jgh.14564. [DOI] [PubMed] [Google Scholar]
- 15.Yukimoto A, Hirooka M, Hiraoka A, Michitaka K, Ochi H, Joko K, Imai Y, Watanabe T, Koizumi Y, Yoshida O, Abe M, Hiasa Y. Using ALBI score at the start of sorafenib treatment to predict regorafenib treatment candidates in patients with hepatocellular carcinoma. Jpn J Clin Oncol. 2019;49:42–47. doi: 10.1093/jjco/hyy153. [DOI] [PubMed] [Google Scholar]
- 16.Du L, Xu H, Fang L, Qiao L, Xie Y, Yang C, Ji L, Zhao L, Wang C, Zhang W, Feng X, Chen T, Yuan Q. Albumin-bilirubin score as a predictor of all-cause mortality in patients with hepatitis B virus infection: An analysis of National Health and Nutrition Examination Survey (NHANES) 1999-2018. Prev Med Rep. 2024;39:102639. doi: 10.1016/j.pmedr.2024.102639. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Han S, Wang C, Tong F, Li Y, Li Z, Sun Z, Sun Z. Prognostic impact of albumin-bilirubin score on the prediction of in-hospital mortality in patients with heart failure: a retrospective cohort study. BMJ Open. 2022;12:e049325. doi: 10.1136/bmjopen-2021-049325. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Kawata T, Ikeda A, Masuda H, Komatsu S. Association Between Albumin-Bilirubin Score at Admission and In-Hospital Mortality in Patients with Acute Heart Failure. Int Heart J. 2021;62:829–836. doi: 10.1536/ihj.21-080. [DOI] [PubMed] [Google Scholar]
- 19.Matsue Y, Kagiyama N, Yamaguchi T, Kuroda S, Okumura T, Kida K, Mizuno A, Oishi S, Inuzuka Y, Akiyama E, Matsukawa R, Kato K, Suzuki S, Naruke T, Yoshioka K, Miyoshi T, Baba Y, Yamamoto M, Mizutani K, Yoshida K, Kitai T. Clinical and Prognostic Values of ALBI Score in Patients With Acute Heart Failure. Heart Lung Circ. 2020;29:1328–1337. doi: 10.1016/j.hlc.2019.12.003. [DOI] [PubMed] [Google Scholar]
- 20.Qiao P, Li L, Ruan H, Zhang M, Wang Z, Li X, Shi R, Wei X, Duan L, Zheng Y, He S. Application of the ALBI Scoring System for Mortality Outcome Prediction in Patients with Hypertrophic Cardiomyopathy. Glob Heart. 2022;17:73. doi: 10.5334/gh.1163. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Duman ZM, Timur B. Albumin-Bilirubin Score: A Novel Mortality Predictor in Valvular Surgery. Braz J Cardiovasc Surg. 2023;38:271–277. doi: 10.21470/1678-9741-2022-0008. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Gou E, Yang Q, Chen J, Kong T, Tang Z, Wen Q, Huang W, Yang G, Li W, Wen D, Zhang Z. Association between albumin-bilirubin score and in-hospital mortality in patients with sepsis: Evidence from two large databases. Heliyon. 2024;10:e34697. doi: 10.1016/j.heliyon.2024.e34697. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.European Association for the Study of the Liver (EASL); European Association for the Study of Diabetes (EASD); European Association for the Study of Obesity (EASO) EASL-EASD-EASO Clinical Practice Guidelines on the management of metabolic dysfunction-associated steatotic liver disease (MASLD) J Hepatol. 2024;81:492–542. doi: 10.1016/j.jhep.2024.04.031. [DOI] [PubMed] [Google Scholar]
- 24.Cao YT, Xiang LL, Qi F, Zhang YJ, Chen Y, Zhou XQ. Accuracy of controlled attenuation parameter (CAP) and liver stiffness measurement (LSM) for assessing steatosis and fibrosis in non-alcoholic fatty liver disease: A systematic review and meta-analysis. EClinicalMedicine. 2022;51:101547. doi: 10.1016/j.eclinm.2022.101547. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Johnson PJ, Berhane S, Kagebayashi C, Satomura S, Teng M, Reeves HL, O'Beirne J, Fox R, Skowronska A, Palmer D, Yeo W, Mo F, Lai P, Iñarrairaegui M, Chan SL, Sangro B, Miksad R, Tada T, Kumada T, Toyoda H. Assessment of liver function in patients with hepatocellular carcinoma: a new evidence-based approach-the ALBI grade. J Clin Oncol. 2015;33:550–558. doi: 10.1200/JCO.2014.57.9151. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Wang JJ, Zheng Z, Zhang Y. Association of Hematological Biomarkers of Inflammation with 10-Year Major Adverse Cardiovascular Events and All-Cause Mortality in Patients with Metabolic Dysfunction-Associated Steatotic Liver Disease: The ARIC Study. J Inflamm Res. 2024;17:4247–4256. doi: 10.2147/JIR.S466469. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Ionescu VA, Gheorghe G, Bacalbasa N, Diaconu CC. Metabolic Dysfunction-Associated Steatotic Liver Disease: Pathogenetic Links to Cardiovascular Risk. Biomolecules. 2025;15:163. doi: 10.3390/biom15020163. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Cano-Contreras AD, Francisco MDR, Vargas-Basurto JL, González-Gómez KD, Vivanco-Cid H, Hernández-Flores KG, Grube-Pagola P, Roesch-Dietlen FB, Remes-Troche JM. Hepatokine and Proinflammatory Cytokine Profile in Patients with Carotid Atherosclerosis and Metabolic Dysfunction-Associated Steatotic Liver Disease. Biomedicines. 2025;13:978. doi: 10.3390/biomedicines13040978. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Angulo P, Bugianesi E, Bjornsson ES, Charatcharoenwitthaya P, Mills PR, Barrera F, Haflidadottir S, Day CP, George J. Simple noninvasive systems predict long-term outcomes of patients with nonalcoholic fatty liver disease. Gastroenterology. 2013;145:782–9.e4. doi: 10.1053/j.gastro.2013.06.057. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.Zhang LF, Chen LX, Yang WJ, Hu B. Albumin-bilirubin score in non-malignant liver and other diseases. World J Gastroenterol. 2024;30:4481–4483. doi: 10.3748/wjg.v30.i41.4481. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31.Xu SX, Yang F, Ge N, Guo JT, Sun SY. Role of albumin-bilirubin score in non-malignant liver disease. World J Gastroenterol. 2024;30:999–1004. doi: 10.3748/wjg.v30.i9.999. [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
No additional data are available.