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Statistical Methods in Medical Research
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0962280208094688v1
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*Hepatitis C
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What's this?

Re-weighted inference about hepatitis C virus-infected communities when analysing diagnosed patients referred to liver clinics

Bo Fu

MRC Biostatistics Unit, Cambridge, UK and Biostatistics Group, School of Medicine, University of Manchester, UK, Bo.Fu{at}manchester.ac.uk

Brian DM Tom

MRC Biostatistics Unit, Cambridge, UK

Sheila M Bird

MRC Biostatistics Unit, Cambridge, UK

To project national hepatitis C virus (HCV) burden, unbiased estimation of HCV progression to liver cirrhosis is required for the whole community of HCV-infected individuals. However, widely varying estimates of progression rates to cirrhosis have been produced. This disparity is partly associated with the statistical methods applied, but is mainly due to the differing types of study cohort. We use an inverse probability weighted estimation method to recover the true parameters for the (Weibull regression) model that determines the incubation period from infection to cirrhosis for the community of HCV-infected individuals, when there is cirrhosis-related recruitment bias to the studied cohort. We apply the method to simulated data for a liver clinic which attracts patients from a community of 1000 HCV-infected individuals under different event-biased referral patterns. We investigate how well the method performs in recovering the true community parameters, and then apply it to Edinburgh Royal Infirmary's liver clinic series. The results obtained are compared to those from a Weibull survival analysis which ignores the selection bias.

This version was published on June 1, 2009

Statistical Methods in Medical Research, Vol. 18, No. 3, 303-320 (2009)
DOI: 10.1177/0962280208094688


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