A model based on two-dimensional shear wave elastography for acute-on-chronic liver failure development in patients with acutely decompensated hepatitis B cirrhosis

Introduction

Chronic hepatitis B viral (HBV) infection is a global health problem, especially in Asia, where HBV is a significant cause of cirrhosis and liver-related death (1,2). Acute decompensation (AD) of liver cirrhosis is the acute development of infection, ascites, gastrointestinal hemorrhage, hepatic encephalopathy, or any combination thereof (3,4). A subset of patients with AD may be at risk of acute-on-chronic liver failure (ACLF), which is characterized by the presence of organ failure and severe systemic inflammation, and the 28-day mortality rate in patients with ACLF in the 2013 CANONIC study was as high as 34% (5,6).

The 2020 PREDICT study by the European Association for the Study of the Liver-Chronic Liver Failure Consortium (CLIF-C) showed that pre-ACLF patients, developed ACLF within 90 days of enrollment, are significantly related to severe systemic inflammation, ACLF development and 90-day mortality (7). While identifying patients who will develop ACLF is of utmost clinical importance, the predictive performance of the Child-Pugh, model for end-stage liver disease (MELD), MELD-Na, CLIF-C AD, and ACLF-D scores are unsatisfactory (7). Moreover, the latter two models were developed using data from the European population, where alcohol and hepatitis C virus are predominant causes of liver cirrhosis.

Liver stiffness measurement (LSM) using shear wave elastography (SWE) is correlated with fibrosis, inflammation and necrosis. LSM has recently gained increased attention as a prognostic predictor for cirrhosis patients (8-11). Two-dimensional (2D) SWE is increasingly used due to its higher success rate of measurement and comparable accuracy compared to transient elastography (TE) (11). 2D SWE can be applied to patients with ascites, and performed with B-mode image guidance. Previous studies (9,10,12,13) determined that 2D SWE values were significantly associated with liver fibrosis, liver-related events and prognosis. Few prior studies used 2D SWE to predict ACLF development among patients with acutely decompensated hepatitis B cirrhosis (AD-HBV).

Our purposes were: (I) to evaluate the accuracy of 2D SWE and (II) to develop and validate a model in predicting 90-day ACLF development for patients with AD-HBV. We present the following article in accordance with the TRIPOD reporting checklist (available at https://qims.amegroups.com/article/view/10.21037/qims-21-871/rc).

Methods

Study population

The local medical ethics committee approved the prospective cohort study of the hospital (No. 2019024). The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013). Written informed consent was obtained from each patient.

Patients with AD-HBV hospitalized at the Department of Infectious Diseases of the First Affiliated Hospital of Nanchang University from September 2019 to January 2021 were enrolled. Patients were excluded if they had alcohol-, autoimmunity-, toxicity-, or drug-induced liver damage, hepatocellular carcinoma, severe chronic extrahepatic diseases, HIV infection, immunosuppressive therapy, or unqualified 2D SWE images. Patients were randomly allocated to the derivation and validation cohorts at a ratio of 7:3. Diagnostic criteria for AD were based on the development of ascites, hepatic encephalopathy, gastrointestinal hemorrhage, infection, or any combination of these. ACLF was diagnosed according to the CANONIC study criteria (5).

The start date of the follow-up period was the date of AD diagnosis. Each enrolled patient was given standard medical treatments. All patients were monitored for at least 90 days. The outcome (ACLF developed) of each patient was recorded.

Baseline data and prognostic scores calculation

The baseline clinical data, including infection (spontaneous peritonitis, chest infection, lung infection, and sepsis diagnosed within the 48-hour period that preceded the onset of AD) (14), ascites, splenomegaly, upper gastrointestinal bleeding, hepatic encephalopathy, and laboratory data were recorded. Two serum parameters of liver fibrosis [aspartate aminotransferase-to-platelet ratio index (APRI) and fibrosis-4 index] were calculated (15,16). Prognostic scores including Child-Pugh, MELD and MELD-Na scores were calculated as well. The formulae see Appendix 1.

Conventional ultrasonographic examination

Spleen longitudinal diameter and portal vein diameter were recorded. The peak velocity of portal vein (PVv), hepatic arterial velocity and hepatic arterial resistive index were measured using a doppler angle of less than or equal to 60° for angle correction (17).

2D SWE examination

The 2D SWE procedure was performed by two radiologists with more than 5 years of ultrasonic experience using an Aixplorer US system (SuperSonic Imagine, Aix-en-Provence, France) equipped with an SC6-1 convex probe. Two operators were unaware of clinical information and strictly followed the guidelines of the Society of Radiologists in Ultrasound (Figure 1) (18). Patients fasted for more than 4 hours before the imaging procedure. The 2D SWE value was defined as the median value of five measurements. Reliability of the measurement was assessed by the interquartile range/median ratio (IQR/M): “very reliable” (IQR/M ≤0.10), “reliable” (0.10< IQR/M ≤0.30), and “poorly reliable” (IQR/M>0.30) referring to TE assessment (8). A measurement was considered acceptable if the IQR/M≤0.30 and more than two-thirds of the signal obtained in the elasticity box.

Figure 1 Image shows liver stiffness measured with 2D SWE in patients with acutely decompensated hepatitis B cirrhosis. The rectangular elasticity box (4 cm × 3 cm) was placed 1–2 cm under the liver capsule in the parenchyma area free of large vessels. Regions of interest ranged from 10 to 20 mm in diameter and were positioned in the elasticity box. 2D, two-dimensional; SWE, shear wave elastography.

Statistical analysis

Statistical tests were performed by using SPSS Statistics software (version 23; IBM, New York, NY, USA) and R software (version 4.0.1, https://www.r-project.org/; packages used are provided in Table S1). The Shapiro-Wilk test was used to evaluate the normal distribution. Continuous data were expressed as means ± standard deviation or M (IQR) and compared using Student’s t-test or Mann-Whitney U test. Categorical data were expressed as the n (%) and compared using a chi-square test or Fisher’s exact test.

For the derivation group, baseline factors significantly associated with 90-day ACLF development (P<0.05) in the Fine-Gray test were entered in the multivariable analysis by using the proportional-hazards competing risk (PH-CR) model, considering death and liver transplantation as competing risks. Parameters significantly associated with the outcome (P<0.05) and with a limited internal co-linearity (variance inflation factor ≤10) were used to fit the new model. The performance of the 2D SWE and new model were compared with serum parameters of liver fibrosis and prognostic scores in the validation and entire cohorts, respectively. Calibration performance was evaluated using a calibration curve and the Hosmer-Lemeshow test; discrimination performance was evaluated using Harrell’s concordance index (C-index). Integrated Discriminating Improvement (IDI) statistic was used to compare C-index (19). A confirmatory analysis was carried out to assess the discrimination ability of the new model by the area under the receiver operating characteristic curve (AUC) for 90-day ACLF development. Comparisons of AUCs were assessed by using the DeLong test.

The thresholds for 2D SWE values and the new model scores were defined as the value that produced the largest χ² value in the Mantel-Cox test (20). Survival probability (Kaplan-Meier) curves were constructed for different groups and compared using a log-rank test. A nomogram was drawn up based on the parameters used as categorical variables. The discrimination and calibration were assessed. The statistical significance level was set at P<0.05.

Results

Patient characteristics

A total of 263 AD-HBV patients met the inclusion criteria, and 221 were eventually enrolled (154 in the derivation cohort and 67 in the validation cohort) (Figure 2). Baseline characteristics are shown in Table 1. Among the derivation cohort, 33 patients developed ACLF, 4 deceased without ACLF development, and 2 received liver transplantation; 17 developed ACLF, 2 deceased without ACLF development, and 1 received transplantation among the validation cohort. There was a significant difference in frequency of hepatic encephalopathy, levels of age, g-glutamyl transferase and hepatic arterial velocity among the two cohorts (all P<0.05). According to the outcome, the distribution of clinical and laboratory characteristics are shown in Table S2. Patients with 90-day ACLF development had significantly lower serum sodium and prothrombin activity (PTA) levels and significantly higher prothrombin times, international normalized ratio, MELD, MELD-Na, and Child-Pugh levels than patients without ACLF development (all P<0.05).

Figure 2 Flowchart shows patient enrollment in the study. AD, acute decompensation; 2D, two-dimensional; SWE, shear wave elastography.

Predictive power of 2D SWE

The success rate of 2D SWE in patients was 95.3% (11/232). 26.3% (61/232) of the 2D SWE results were evaluated as “very reliable”, and 69.0% (160/232) were considered as “reliable”. 2D SWE failed in 11 patients due to liver atrophy (n=3), intestinal gas or obesity (n=6), or inability to hold their breath (n=2). 2D SWE values were significantly higher in patients with ACLF development (derivation cohort: 44.8 vs. 26.2 kPa, P<0.001; validation cohort: 42.8 vs. 24.2 kPa, P=0.001). Furthermore, 2D SWE was a risk factor for 90-day ACLF development (HR =1.050; 95% CI: 1.037–1.063; P<0.001). The C-index in the derivation (0.777; 95% CI: 0.706–0.848) and validation (0.754, 95% CI: 0.638–0.870) cohorts were significantly better than those corresponding to the APRI and fibrosis-4 index (Table 2). The AUC of 2D SWE in the entire cohort (0.794; 95% CI: 0.724–0.865) was significantly higher than the other (Figure 3A).

Figure 3 Receiver operating characteristic curves shows that predictive performance of 2D SWE values (A) and SWE model scores (B) are compared with serum biomarkers of liver fibrosis and prognostic models for 90-day ACLF development. 2D, two-dimensional; SWE, shear wave elastography; ACLF, acute-on-chronic liver failure; APRI, aspartate aminotransferase-to-platelet ratio index; FIB4, fibrosis-4 index; MELD, model for end-stage liver disease; AUC, area under the receiver operating characteristic curve.

Development of SWE model in the derivation cohort

Baseline factors significantly associated with ACLF developed for derivation cohort were age, white-cell count, serum sodium, bilirubin, alkaline phosphatase (ALP), prothrombin times, international normalized ratio, PTA, PVv and 2D SWE values in univariate analysis. After fitting an initial CR-PH model with all these factors, serum sodium, ALP, PTA, PVv and 2D SWE values were selected as the best predictors (Table 3). The most significant effect size was observed at 2D SWE values (1.141), followed by PTA (0.964) (Figure S1). The formula of the SWE model according to the CR-PH model was presented as follow:

SWEmodelscore=0.03×2DSWE(kPa)−0.062×sodium(mmol/L)+0.003×ALP(IU/L)−0.043×PTA(%)−0.099×PVv(cm/s)+10[1]

In our series, the extreme SWE model scores were from −3.652 to 2.746. Patients with 90-day ACLF development had significantly higher SWE model scores than patients without ACLF development in the derivation (0.37 vs. −1.16; P<0.001) and validation (0.55 vs. −1.12; P<0.001) cohorts. The Hosmer-Lemeshow test statistic (χ²=3.676; P=0.885) and calibration curve showed good calibration in the derivation cohort (Figure S2). The C-Index of the SWE model (0.855; 95% CI: 0.810–0.900) was significantly better than that of MELD, MELD-Na, and Child-Pugh scores (Table 4).

Validation of the SWE model

For the validation cohort, the C-index of the SWE model (0.840; 95% CI: 0.746–0.934) was significantly better than that of Child-Pugh, MELD and MELD-Na scores (Table 4). The AUC (0.885; 95% CI: 0.836–0.935) confirmed the superiority (Figure 3B). Moreover, the percentage improvement obtained with the SWE model in prediction error rate for the prognostic scores [100 × (C-index SWE model − C-index REF)/(1 − C-index REF)] were from 33.9% to 53.3% (Figure S3).

Development of the SWE nomogram

Cutoff values were 29.2 for 2D SWE values, 138.4 mmol/L for serum sodium, 106 IU/L for ALP, 40.2% for PTA and 12.8 cm/s for PVv. The cutoff values for the 2D SWE and SWE model were used to separate patients into low-risk and high-risk groups. Patients in high-risk groups had a significantly higher risk for ACLF development in the validation and entire cohorts (Figure 4). A nomogram incorporating the five predictors mentioned above, used as categorical variables, was constructed (Figure 5A). The calibration curve and Hosmer-Lemeshow test statistic (P=0.405 and 0.600 respectively) showed satisfactory calibration in the derivation and validation cohorts (Figure 5B,5C). The C-index of 0.817 (95% CI: 0.764–0.870) in the derivation cohort and 0.836 (95% CI: 0.740–0.932) in the validation cohort demonstrated good discrimination.

Figure 4 Kaplan-Meier 90-day ACLF development analyses based on the 2D SWE value and SWE model for patients with acutely decompensated hepatitis B cirrhosis in the validation and entire cohorts. 90-day ACLF development probability was significantly higher in patients with high 2D SWE values (>29.2 kPa) than in patients with low 2D SWE values (≤29.2 kPa) in the validation (A) and entire cohorts (B); 90-day ACLF development probability was significantly higher in patients with high SWE model score (>−0.8) than in patients with low SWE model score (≤−0.8) in the validation (C) and entire cohorts (D). ACLF, acute-on-chronic liver failure; 2D, two-dimensional; SWE, shear wave elastography.

Figure 5 Generation and evaluation of the nomogram. (A) Nomogram to predict 90-day ACLF development; (B,C) the calibration curve estimates 90-day ACLF development predicted by nomogram in the derivation and validation cohorts. ACLF, acute-on-chronic liver failure; ALP, alkaline phosphatase; PTA, prothrombin activity, PVv, peak velocity of portal vein; SWE, shear wave elastography.

Discussion

Our results showed that 2D SWE was correlated with 90-day ACLF development in patients with AD-HBV, whose predictive ability was better than APRI and fibrosis-4 index. The SWE model, composed of serum sodium, ALP, PTA, PVv and 2D SWE values, showed good calibration and discrimination. The novel model improved the prediction of Child-Pugh, MELD and MELD-Na scores and could aid the management of AD-HBV patients.

The PREDICT study found that the pre-ACLF is a specific course related to worse prognosis in patients with AD, indicating that rapid progression of systemic inflammation and ACLF development and short-term mortality, of which 90-day mortality rate was 53.7% (7). The different pathophysiological mechanisms and their corresponding effects on the liver make LSM possible to predict ACLF development (7). The most effective treatment of ACLF is liver transplantation, while it is not an available treatment for most patients. Therefore, antiviral therapy (interferon, nucleoside analogs) and artificial liver support systems (ALSSs) are the main alternatives to liver transplants; hence the mortality of patients with ACLF remains high (21,22). Serum prognostic scores for evaluating the prognosis of liver cirrhosis have limitations and were not the target for patients with AD-HBV.

LSM can be affected by inflammation, necrosis, and liver function (8,23,24). Qiu et al. (25) suggested that LSM was significantly related to liver function reserve. LSM is also associated with portal hypertension, supporting that it can reflect the clinical course of AD. A meta-analysis (26) showed that LSM was significantly related to liver-related events, including decompensation, hepatocellular carcinoma, and death. The prediction for the liver failure of LSM was comparable with that of MELD (27-30).

LSM tools, including TE, point SWE and 2D SWE, are now widely used. TE was recommended as a first-line examination for liver fibrosis and cirrhosis (31). Previous studies found that 2D SWE had comparable diagnostic accuracy to TE (8,11,12). Moreover, it is inappropriate for hospitalized patients with liver cirrhosis to perform TE because of ascites and liver atrophy. 2D SWE has a success rate of 86%-100% in patients with ascites (10). Our study confirmed excellent success rates of 2D SWE in patients with AD-HBV, whose images were successfully captured in 95.3% (221/232) of patients. Furthermore, when measuring 2D SWE values, we can simultaneously measure PVv and monitor ascites and liver tumors. Wu et al. (12) demonstrated that 2D SWE could predict liver-related events in patients with compensated liver cirrhosis. Jin et al. (10) found that 2D SWE improved the predictive performance of MELD in ACLF patients. Patients with higher 2D SWE values are more likely to have worse outcomes (27-30). In our study, 90-day ACLF development was correlated with higher 2D SWE values. The predictive performance of 2D SWE was better than that of APRI and fibrosis-4 index. Meanwhile, 2D SWE had the largest effect size in our SWE model. Given the above, 2D SWE could be a noninvasive and accurate predictor in patients with different stages of chronic liver disease.

The SWE model developed in our study contained parameters that can represent LSM, liver blood flow, electrolytes, coagulation and liver function. These parameters are usually involved in the systematic and prognostic evaluation. Our model was better than the Child-Pugh, MELD and MELD-Na scores to provide prognostic information and accurately stratify patients into high and low-risk groups. A nomogram composed of these parameters used as categorical variables is based on a multivariate Cox proportional hazards model and displays the probable value of individual ACLF development concisely and intuitively. Our nomogram also showed favorably predictive performance; hence it may effectively assist individualized treatment.

Our study had several limitations. First, this study was performed in a single center with small sample size; hence, further studies with multiple centers and larger samples are needed. Second, further research is necessary to evaluate the influence of the etiology, antiviral therapy and pathological inflammation grade for prediction. Third, we did not analyze the dynamic changes in 2D SWE values and SWE model scores of patients for the possible better presence of the correlation between parameters and prognosis.

Conclusions

2D SWE is a noninvasive and promising predictor for 90-day ACLF development in patients with AD-HBV. The prognostic model based on 2D SWE values, developed by our study, could be an individualized tool and provide a more accurate prognosis prediction than serum prognostic scores. Patients with higher 2D SWE values and SWE model scores may benefit from intensive medical treatment.

Acknowledgments

Funding: This study was supported by Natural Science Foundation of Jiangxi Province of China (No. 20212ACB206010).

Footnote

Reporting Checklist: The authors have completed the TRIPOD reporting checklist. Available at https://qims.amegroups.com/article/view/10.21037/qims-21-871/rc

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://qims.amegroups.com/article/view/10.21037/qims-21-871/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 was conducted in accordance with the Declaration of Helsinki (as revised in 2013). The study was approved by local medical ethics committee of the First Affiliated Hospital of Nanchang University (No. 2019024) and informed consent was taken from all individual participants.

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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