Improving the accuracy of long‐term prognostic estimates in hepatitis C virus infection

Abstract

Obtaining unbiased estimates of HCV prognosis is difficult because of potential biases associated with study design and calculation methods. We propose a new method for estimating fibrosis progression rates. A Markov model with fibrosis health states (F0-F4) was created. The maximum likelihood method was used to estimate stage-specific progression rates. We compared the standard method to the new method using two well-known cohort studies. The known stage distribution at the end of follow-up was compared with stage predicted by the Markov model using both methods of calculating transition rates. We also compared rates obtained using both methods to known fibrosis rates in a series of Monte Carlo simulations. For Kenny-Walsh's study (1999), transition rates between F0-F1, F1-F2, F2-F3, and F3-F4 were 0.042, 0.045, 0.097 and 0.070 fibrosis units/year (new method) and 0.045 units/year (standard method). The new method predicted fibrosis stage and known transition rates in Monte Carlo simulations more accurately. The standard method underestimates 30-year cirrhosis rates by up to 40%. The new (Markov maximum likelihood or MML) method allows accurate estimation of stage-specific transition probabilities from the many studies in which only a single biopsy is available. Application of the method supports the hypothesis that rates of fibrosis vary between stages.

The natural history of hepatitis C infection acquired through injection drug use: Meta-analysis and meta-regression

“…We did not have enough data to estimate stage specific progression rates. Previous studies indicate that fibrosis progression rates increase with advanced fibrosis stage [30,34]. However, a more recent study of coinfected patients found no evidence of increasing progression rates, suggesting that assuming constant progression rates may not result in biased estimates [31].…”

Estimated progression rates in three United Kingdom hepatitis C cohorts differed according to method of recruitment

“…Multistage Markov models have not been widely used in hepatitis C disease progression, despite the categorical nature of biopsy assessment. Deuffic-Burban et al [15] illustrated the potential of using a Markov model to estimate hepatitis C progression rates, and Yi et al [16] showed the advantages of such an approach over routinely used methods. The model presented here allows only forward transitions, and includes adjustment for age at biopsy, gender, and PNALT status to provide estimates of cirrhosis development in a variety of subgroups.…”

“…Recently, representation of HCV progression as a series of disease stages through a multistage model formulation has been suggested as an alternative [15,16], when transition between specific disease stages is of interest and when, crucially, only information on stage occupation (rather than stage entrance) is available. Multistage modeling is particularly appropriate to the study of fibrosis in HCV where the only information available is the stage of disease identified at biopsy.…”

Hepatitis C virus (HCV) disease progression in people who inject drugs (PWID): A systematic review and meta-analysis

“…The FPR was approximated using one of three methods depending on the amount of data included in the report. In general, a modified version of the indirect or direct method for estimating a stage-constant FPR, appropriate for single-biopsy or serial-biopsy data (Yi, Wang, & Krahn, 2004; Thein et al 2008), respectively, was applied when the report provided the distribution of fibrosis stages.…”