The Model of Mortality with Incident Cirrhosis (MoMIC) and the model of Long-term Outlook of Mortality in Cirrhosis (LOMiC)

Autoři: Ellen R Berni aff001;  Bethan I Jones aff001;  Thomas R Berni aff001;  James Whitehouse aff002;  Mark Hudson aff003;  James Orr aff003;  Pete Conway aff001;  Bharat Amlani aff002;  Craig J. Currie aff001
Působiště autorů: Global Epidemiology, Pharmatelligence, Cardiff, United Kingdom aff001;  Norgine Pharmaceuticals Limited, Harefield, Uxbridge, United Kingdom aff002;  Liver Unit, Freeman Hospital, Newcastle upon Tyne, United Kingdom aff003;  Institute of Cellular Medicine, Newcastle University, Newcastle upon Tyne, United Kingdom aff004;  Division of Population Medicine, School of Medicine, Cardiff University, United Kingdom aff005
Vyšlo v časopise: PLoS ONE 14(10)
Kategorie: Research Article
doi: 10.1371/journal.pone.0223253


The purpose of this study was to produce two statistical survival models in those with cirrhosis utilising only routine parameters, including non-liver-related clinical factors that influence survival. The first model identified and utilised factors impacting short-term survival to 90-days post incident diagnosis, and a further model characterised factors that impacted survival following this acute phase. Data were from the Clinical Practice Research Datalink linked with Hospital Episode Statistics. Incident cases in patients ≥18 years were identified between 1998 and 2014. Patients that had prior history of cancer or had received liver transplants prior were excluded. Model-1 used a logistic regression model to predict mortality. Model-2 used data from those patients who survived 90 days, and used an extension of the Cox regression model, adjusting for time-dependent covariables. At 90 days, 23% of patients had died. Overall median survival was 3.7 years. Model-1: numerous predictors, prior comorbidities and decompensating events were incorporated. All comorbidities contributed to increased odds of death, with renal disease having the largest adjusted odds ratio (OR = 3.35, 95%CI 2.97–3.77). Model-2: covariables included cumulative admissions for liver disease-related events and admissions for infections. Significant covariates were renal disease (adjusted hazard ratio (HR = 2.89, 2.47–3.38)), elevated bilirubin levels (aHR = 1.38, 1.26–1.51) and low sodium levels (aHR = 2.26, 1.84–2.78). An internal validation demonstrated reliability of both models. In conclusion: two survival models that included parameters commonly recorded in routine clinical practice were generated that reliably forecast the risk of death in patients with cirrhosis: in the acute, post diagnosis phase, and following this critical, 90 day phase. This has implications for practice and helps better forecast the risk of mortality from cirrhosis using routinely recorded parameters without inputs from specialists.

Klíčová slova:

Alcohol consumption – Ascites – bilirubin – Cancer detection and diagnosis – Cirrhosis – Diagnostic medicine – Liver diseases


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Článek vyšel v časopise


2019 Číslo 10