Abstract
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.
Highlights
Cirrhosis is advanced fibrosis of the liver; resulting in severe architectural distortion and derangement of liver function which can progress to portal hypertension and decompensation
The purpose of this study was to, produce statistical survival models at the time a patient is first diagnosed with liver cirrhosis, utilising only clinical data commonly recorded in routine clinical practice independently of any inputs from liver-disease specialists required for the existing risk models—Model for End-stage Liver Disease (MELD) and Child-Pugh [9]
From Clinical Practice Research Datalink (CPRD) 26,385 patients eligible for the hospital episode statistics (HES) linkage scheme were identified with an incident diagnosis of cirrhosis
Summary
Cirrhosis is advanced fibrosis of the liver; resulting in severe architectural distortion and derangement of liver function which can progress to portal hypertension and decompensation. The main causes of liver cirrhosis are alcohol-related liver disease (ARLD), obesity, and hepatitis B and/or C infection [1]. Morbid damage to the liver increases over time, progressing to cirrhosis over many years. Cirrhosis and HCC contribute to 2.5% of deaths worldwide, with hepatitis B the most common cause in developing countries, and ARLD being the most common cause in developed countries [2]. Cirrhosis can affect people of any age-group or gender. Cirrhosis causes around 4,000 deaths every year in the UK [4]. It is unclear how many people are truly affected by cirrhosis, since symptoms may arise only when the condition is clinically advanced and, often, nearly fatal [4]
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