Can routine blood tests be modelled to detect advanced liver disease in the community: model derivation and validation using UK primary and secondary care data.

Autor:	Hydes T; School of Primary Care and Population Sciences, University of Southampton, Southampton, Hampshire, UK., Moore M; School of Primary Care and Population Sciences, University of Southampton, Southampton, Hampshire, UK., Stuart B; School of Primary Care and Population Sciences, University of Southampton, Southampton, Hampshire, UK., Kim M; School of Primary Care and Population Sciences, University of Southampton, Southampton, Hampshire, UK., Su F; School of Primary Care and Population Sciences, University of Southampton, Southampton, Hampshire, UK., Newell C; Human Development and Health, University of Southampton Faculty of Medicine, Southampton, Southampton, UK.; Southampton Biomedical Research Centre, Southampton, UK., Cable D; Informatics, University Hospital Southampton NHS Foundation Trust, Southampton, Southampton, UK., Hales A; School of Primary Care and Population Sciences, University of Southampton, Southampton, Hampshire, UK.; AH IT Solutions, Southampton, Hampshire, UK., Sheron N; The Institute of Hepatology, Foundation for Liver Research, London, UK nicksheronwork@outlook.com.
Jazyk:	angličtina
Zdroj:	BMJ open [BMJ Open] 2021 Feb 11; Vol. 11 (2), pp. e044952. Date of Electronic Publication: 2021 Feb 11.
DOI:	10.1136/bmjopen-2020-044952
Abstrakt:	Objectives: Most patients are unaware they have liver cirrhosis until they present with a decompensating event. We therefore aimed to develop and validate an algorithm to predict advanced liver disease (AdvLD) using data widely available in primary care. Design, Setting and Participants: Logistic regression was performed on routinely collected blood result data from the University Hospital Southampton (UHS) information systems for 16 967 individuals who underwent an upper gastrointestinal endoscopy (2005-2016). Data were used to create a model aimed at detecting AdvLD: 'CIRRhosis Using Standard tests' (CIRRUS). Prediction of a first serious liver event (SLE) was then validated in two cohorts of 394 253 (UHS: primary and secondary care) and 183 045 individuals (Care and Health Information Exchange (CHIE): primary care). Primary Outcome Measures: Model creation dataset: cirrhosis or portal hypertension. Validation datasets: SLE (gastro-oesophageal varices, liver-related ascites or cirrhosis). Results: In the model creation dataset, 931 SLEs were recorded (5.5%). CIRRUS detected cirrhosis or portal hypertension with an area under the curve (AUC) of 0.90 (95% CI 0.88 to 0.92). Overall, 3044 (0.8%) and 1170 (0.6%) SLEs were recorded in the UHS and CHIE validation cohorts, respectively. In the UHS cohort, CIRRUS predicted a first SLE within 5 years with an AUC of 0.90 (0.89 to 0.91) continuous, 0.88 (0.87 to 0.89) categorised (crimson, red, amber, green grades); and AUC 0.84 (0.82 to 0.86) and 0.83 (0.81 to 0.85) for the CHIE cohort. In patients with a specified liver risk factor (alcohol, diabetes, viral hepatitis), a crimson/red cut-off predicted a first SLE with a sensitivity of 72%/59%, specificity 87%/93%, positive predictive value 26%/18% and negative predictive value 98%/99% for the UHS/CHIE validation cohorts, respectively. Conclusion: Identification of individuals at risk of AdvLD within primary care using routinely available data may provide an opportunity for earlier intervention and prevention of liver-related morbidity and mortality. Competing Interests: Competing interests: NS undertook paid consultancy work and received travelling expenses from pharmaceutical companies Norgine (2014) and Kyowa Kirin Limited (2014), as well as under taking medicolegal work in hepatitis C and alcohol-related liver disease. None of the remaining authors have any competing interests. (© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)
Databáze:	MEDLINE
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