Development and validation of a prediction model to estimate the risk of liver cirrhosis in primary care patients with abnormal liver blood test results: protocol for an electronic health record study in Clinical Practice Research Datalink

• Published in: Diagnostic and prognostic research Vol. 3; no. 1; p. 10
• Main Authors: Härmälä, Suvi, O'Brien, Alastair, Parisinos, Constantinos A, Direk, Kenan, Shallcross, Laura, Hayward, Andrew
• Format: Journal Article
• Language: English
• Published: England BioMed Central 23.05.2019; BMC
• Subjects: Blood tests; Cirrhosis; Clinical medicine; Datasets; Decision making; Electronic health records; Hepatitis; Liver cirrhosis; Liver disease; Liver diseases; Patients; Practice research; Prediction model; Primary care; Prognosis; Protocol; United Kingdom > UK; England; Scotland; Prevention; Cirrhosis; Prognosis; Liver disease; Prediction model; Electronic health records; Primary care; Public health
• ISSN: 2397-7523; 2397-7523
• DOI: 10.1186/s41512-019-0056-7

Driven by alcohol consumption and obesity, the prevalence of non-viral liver disease in the UK is increasing. Due to its silent and slow nature, the progression of liver disease is currently unpredictable and challenging to monitor. The latest National Institute for Health Care Excellence cirrhosis guidelines call for a validated risk tool that would allow general practitioners to identify patients that are at high risk of developing cirrhosis. Using linked electronic health records from the Clinical Practice Research Datalink (a database of > 10 million patients in England), we aim to develop and validate a prediction model to estimate 2-, 5- and 10-year risk of cirrhosis. The model will provide individualised cirrhosis risk predictions for adult primary care patients, free from underlying liver disease or viral hepatitis infection, whose liver blood test results come back abnormal. We will externally validate the model in patients from 30 further Clinical Practice Research Datalink general practices in England. The prediction model will provide estimates of cirrhosis risk in primary care patients with abnormal liver blood test results to guide referral to secondary care, to identify patients who are in serious need of preventative health interventions and to help reassure patients at low risk of cirrhosis in the long term.