The role of the model for end-stage liver disease-sodium score and joint models for 90-day mortality prediction in patients with acute-on-chronic liver failure

Prognostic value of decline in model for end-stage liver disease score and hepatic encephalopathy in hepatitis B-related acute-on-chronic liver failure patients treated with plasma exchange

OBJECTIVE

To investigate the prognostic value of Model for End-Stage Liver Disease (MELD) score and Hepatic Encephalopathy (HE) for short-term prognosis of Hepatitis B virus-related Acute-on-Chronic Liver Failure (HBV-ACLF) patients treated with plasma exchange (PE).

METHODS

A total of 108 patients with HBV-ACLF treated with PE were retrospectively enrolled between January 2014 to December 2020. Based on survival at 28 days, patients were divided into survival (N = 87) and death groups (N = 21). Clinical data and laboratory indicators were analyzed.

RESULTS

Compared with the survival group, the death group was associated with higher ACLF grade and incidence of HE. The levels of total bilirubin, prothrombin time, creatinine, blood urea nitrogen, MELD score, and Chinese Group on the Study of Severe Hepatitis B-ACLF II (COSSH II) score were significantly higher in the death group than in the survival group (p < .05). Grade 1 ACLF and the MELD score after PE treatment at one week were independent risk factors for 28-day liver transplantation-free mortality (OR = 0.062, 95%CI: 0.005-0.768; OR = 1.328, 95%CI: 1.153-1.531). A MELD score at one week of at least 25.5 was associated with a poor short-term prognosis. Of note, HE was a strong independent risk factor for a decline in MELD score at one week. (OR = 11.815, 95%CI: 3.187-43.796, p < 0.001).

CONCLUSION

We found patients with HE at admission and MELD score of at least 25.5 at one week after PE treatment had a poor short-term prognosis and should prompt preparation for liver transplantation. Trial Registration: The trial is registered at ClinicalTrials.gov (CT.gov identifier: NCT04231565). Registered 13 May 2020.

Development and validation of a dynamic survival prediction model for patients with acute-on-chronic liver failure

Background & Aims

Acute-on-chronic liver failure (ACLF) is usually associated with a precipitating event and results in the failure of other organ systems and high short-term mortality. Current prediction models fail to adequately estimate prognosis and need for liver transplantation (LT) in ACLF. This study develops and validates a dynamic prediction model for patients with ACLF that uses both longitudinal and survival data.

Methods

Adult patients on the UNOS waitlist for LT between 11.01.2016-31.12.2019 were included. Repeated model for end-stage liver disease-sodium (MELD-Na) measurements were jointly modelled with Cox survival analysis to develop the ACLF joint model (ACLF-JM). Model validation was carried out using separate testing data with area under curve (AUC) and prediction errors. An online ACLF-JM tool was created for clinical application.

Results

In total, 30,533 patients were included. ACLF grade 1 to 3 was present in 16.4%, 10.4% and 6.2% of patients, respectively. The ACLF-JM predicted survival significantly (p <0.001) better than the MELD-Na score, both at baseline and during follow-up. For 28- and 90-day predictions, ACLF-JM AUCs ranged between 0.840-0.871 and 0.833-875, respectively. Compared to MELD-Na, AUCs and prediction errors were improved by 23.1%-62.0% and 5%-37.6% respectively. Also, the ACLF-JM could have prioritized patients with relatively low MELD-Na scores but with a 4-fold higher rate of waiting list mortality.

Conclusions

The ACLF-JM dynamically predicts outcome based on current and past disease severity. Prediction performance is excellent over time, even in patients with ACLF-3. Therefore, the ACLF-JM could be used as a clinical tool in the evaluation of prognosis and treatment in patients with ACLF.

Lay summary

Acute-on-chronic liver failure (ACLF) progresses rapidly and often leads to death. Liver transplantation is used as a treatment and the sickest patients are treated first. In this study, we develop a model that predicts survival in ACLF and we show that the newly developed model performs better than the currently used model for ranking patients on the liver transplant waiting list.

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ACLF is a dynamic disease that can rapidly change over time, which greatly influences patient survival without LT.

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Currently, the MELD-Na score is used to prioritize patients for LT, but MELD-Na underestimates ACLF disease severity.

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The ACLF joint model (ACLF-JM) was developed to dynamically predict survival.

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The ACLF-JM significantly outperformed the MELD-Na score for the prediction of mortality on the LT waiting list.

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The ACLF-JM can be used online to predict survival in individual patients.

Joint modeling of liver transplant candidates outperforms the model for end-stage liver disease: The effect of disease development over time on patient outcome

Liver function is measured regularly in liver transplantation (LT) candidates. Currently, these previous disease development data are not used for survival prediction. By constructing and validating joint models (JMs), we aimed to predict the outcome based on all available data, using both disease severity and its rate of change over time. Adult LT candidates listed in Eurotransplant between 2007 and 2018 (n = 16 283) and UNOS between 2016 and 2019 (n = 30 533) were included. Patients with acute liver failure, exception points, or priority status were excluded. Longitudinal MELD(-Na) data were modeled using spline-based mixed effects. Waiting list survival was modeled with Cox proportional hazards models. The JMs combined the longitudinal and survival analysis. JM 90-day mortality prediction performance was compared to MELD(-Na) in the validation cohorts. MELD(-Na) score and its rate of change over time significantly influenced patient survival. The JMs significantly outperformed the MELD(-Na) score at baseline and during follow-up. At baseline, MELD-JM AUC and MELD AUC were 0.94 (0.92-0.95) and 0.87 (0.85-0.89), respectively. MELDNa-JM AUC was 0.91 (0.89-0.93) and MELD-Na AUC was 0.84 (0.81-0.87). The JMs were significantly (p < .001) more accurate than MELD(-Na). After 90 days, we ranked patients for LT based on their MELD-Na and MELDNa-JM survival rates, showing that MELDNa-JM-prioritized patients had three times higher waiting list mortality.