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Classifying people living with hepatitis C virus using a population-level latent class analysis to understand association with treatment uptake and optimize integration of health services

University of British Columbia

Background Hepatitis C virus (HCV) infection affects diverse populations such as people who inject drugs (PWID), 'baby boomers' (BB’s), gay, bisexual, and other men who have sex with men (gbMSM), and immigrants from HCV endemic regions. Assessing patterns of shared characteristics, the burden of syndemics, and the likelihood of treatment uptake among subpopulations may facilitate targeted program planning. Methods The BC Hepatitis Testers Cohort includes all HCV cases identified in BC from 1990 to 2015 followed up to 2018 and linked with data on medical visits, emergency department visits, hospitalizations, cancers, prescription drugs, and deaths. Latent Class Analysis was used to group people diagnosed with HCV according to shared characteristics previously shown to be related to HCV acquisition, transmission, retention in care and/or treatment uptake. Models were fitted step-wise, with the best fitting model chosen based on fit statistics, epidemiological meaningfulness, and maximisation of posterior probability for class assignment. Latent class groups were named based on defining characteristics and analysed for their association with treatment uptake (based on first treatment course). Results The best fitting latent class model had six groups, with names and characteristics as follows: Younger PWID (n=11,563): people born >1974, mental illness, material deprivation, recent injection drug use (IDU). Older PWID (n=15,266): past IDU, HIV, HBV, TB coinfections, alcohol misuse. gbMSM (n=12,698): gbMSM, material privilege, no liver disease. People of Asian Backgrounds (n=4,718): East/South Asians, people born <1945, social privilege, no alcohol misuse/mental illness. Rural BB (n=20,401): rural dwellers, BBs, heterosexuals, no HIV. Urban socially deprived BB (n=12,698): urbanites, liver disease, social deprivation, no IDU. Compared to Younger PWID, groups with higher odds of treatment uptake were People of Asian Backgrounds and Rural BB. Compared to all other groups, gbMSM and Younger PWID had lower likelihoods of treatment uptake. Conclusion There are differences in HCV treatment uptake among the multivariable patient profiles, suggesting that the co-occurrence of multiple factors influences likelihood of receiving treatment. Further investigation of treatment uptake patterns related to multivariable patient profiles may help with program planning or addressing areas where services do not align with the particular patient populations.

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2020-05-04

Attribution-NonCommercial-NoDerivatives 4.0 International

http://hdl.handle.net/2429/74309

Population and Public Health

University of British Columbia

UBCV

http://creativecommons.org/licenses/by-nc-nd/4.0/