Highlights
- •Seven percent of people treated for HCV in Australia were retreated.
- •Machine learning was used to classify retreatments based on national administrative data.
- •Overall, 52% of retreatment was for reinfection and 48% was for treatment failure.
- •Retreatment for reinfection increased over time, reflecting increasing numbers of people at-risk for reinfection following cure.
- •Retreatment for treatment failure increased when salvage DAAs became available.
Background & Aims
Population-level uptake of direct-acting antiviral (DAA) treatment for hepatitis C
virus (HCV) infection, including retreatment, can be estimated through administrative
pharmaceutical dispensation data. However, the reasons for retreatment are not captured
in these data. We developed a machine learning model to classify retreatments as reinfection
or treatment failure at a national level.
Methods
Retreatment data from the REACH-C cohort (n = 10,843 treated with DAAs; n = 320 retreatments
with known reason), were used to train a random forest model. Nested cross validation
was undertaken to assess model performance and to optimise hyperparameters. The model
was applied to data on DAA retreatment dispensed during 2016-2021 in Australia, to
identify the reason for retreatment (treatment failure or reinfection).
Results
Average predictive accuracy, precision, sensitivity, specificity and F1-score for the model were 96.3%, 96.5%, 96.3%, 96.3% and 96.3%, respectively. Nationally,
95,272 individuals initiated DAAs, with treatment uptake declining from 32,454 in
2016 to 6,566 in 2021. Of those treated, 6,980 (7%) were retreated. Our model classified
51.8% (95% CI 46.7–53.6%; n = 3,614) of cases as reinfection and 48.2% (95% CI 46.4–53.3%;
n = 3,366) as treatment failure. Retreatment for reinfection increased steadily over
the study period from 14 in 2016 to 1,092 in 2020, stabilising in 2021. Retreatment
for treatment failure increased from 73 in 2016 to 1,077 in 2019, then declined to
515 in 2021. Among individuals retreated for treatment failure, 50% had discontinued
initial treatment.
Conclusions
We used a novel methodology with high classification accuracy to evaluate DAA retreatment
patterns at a national level. Increases in retreatment uptake for treatment failure
corresponded to the availability of pangenotypic and salvage regimens. Increasing
retreatment uptake for reinfection likely reflects increasing reinfection incidence.
Impact and implications
This study used machine learning methodologies to analyse national administrative
data and characterise trends in HCV retreatment due to reinfection and treatment failure.
Retreatment for reinfection increased over time, reflecting increasing numbers of
people at risk for reinfection following HCV cure. Increased retreatment for treatment
failure corresponded to the availability of pangenotypic and salvage DAA regimens.
The findings of this study can be used by public health agencies and policy makers
to guide and assess HCV elimination strategies, while the novel methodology for monitoring
trends in HCV retreatment has the potential to be used in other settings, and health
conditions.
Graphical abstract
Graphical Abstract
Keywords
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Article info
Publication history
Published online: September 21, 2022
Accepted:
September 5,
2022
Received in revised form:
August 19,
2022
Received:
June 17,
2022
Identification
Copyright
© 2022 European Association for the Study of the Liver. Published by Elsevier B.V. All rights reserved.
