Impact of Hepatitis C Virus Cure on Depressive Symptoms in the Human Immunodeficiency Virus-Hepatitis C Virus Coinfected Population in Canada.

BACKGROUND: Depression is common in people with human immunodeficiency virus (HIV) and hepatitis C virus (HCV), with biological and psychosocial mechanisms at play. Direct acting antivirals (DAA) result in high rates of sustained virologic response (SVR), with minimal side-effects. We assessed the impact of SVR on presence of depressive symptoms in the HIV-HCV coinfected population in Canada during the second-generation DAA era (2013-2020). METHODS: We used data from the Canadian CoInfection Cohort (CCC), a multicenter prospective cohort of people with a HIV and HCV coinfection, and its associated sub-study on food security. Because depression screening was performed only in the sub-study, we predicted Center for Epidemiologic Studies Depression Scale-10 classes in the CCC using a random forest classifier and corrected for misclassification. We included participants who achieved SVR and fit a segmented modified Poisson model using an interrupted time series design, adjusting for time-varying confounders. RESULTS: We included 470 participants; 58% had predicted depressive symptoms at baseline. The median follow-up was 2.4 years (interquartile range [IQR]: 1.0-4.5.) pre-SVR and 1.4 years (IQR: 0.6-2.5) post-SVR. The pre-SVR trend suggested depressive symptoms changed little over time, with no immediate level change at SVR. However, post-SVR trends showed a reduction of 5% per year (risk ratio: 0.95 (95% confidence interval [CI]: .94-.96)) in the prevalence of depressive symptoms. CONCLUSIONS: In the DAA era, predicted depressive symptoms declined over time following SVR. These improvements reflect possible changes in biological pathways and/or better general health. If such improvements in depression symptoms are durable, this provides an additional reason for treatment and early cure of HCV.

Predicting the presence of depressive symptoms in the HIV-HCV co-infected population in Canada using supervised machine learning.

BACKGROUND: Depression is common in the human immunodeficiency virus (HIV)-hepatitis C virus (HCV) co-infected population. Demographic, behavioural, and clinical data collected in research settings may be of help in identifying those at risk for clinical depression. We aimed to predict the presence of depressive symptoms indicative of a risk of depression and identify important classification predictors using supervised machine learning. METHODS: We used data from the Canadian Co-infection Cohort, a multicentre prospective cohort, and its associated sub-study on Food Security (FS). The Center for Epidemiologic Studies Depression Scale-10 (CES-D-10) was administered in the FS sub-study; participants were classified as being at risk for clinical depression if scores ≥ 10. We developed two random forest algorithms using the training data (80%) and tenfold cross validation to predict the CES-D-10 classes-1. Full algorithm with all candidate predictors (137 predictors) and 2. Reduced algorithm using a subset of predictors based on expert opinion (46 predictors). We evaluated the algorithm performances in the testing data using area under the receiver operating characteristic curves (AUC) and generated predictor importance plots. RESULTS: We included 1,934 FS sub-study visits from 717 participants who were predominantly male (73%), white (76%), unemployed (73%), and high school educated (52%). At the first visit, median age was 49 years (IQR:43-54) and 53% reported presence of depressive symptoms with CES-D-10 scores ≥ 10. The full algorithm had an AUC of 0.82 (95% CI:0.78-0.86) and the reduced algorithm of 0.76 (95% CI:0.71-0.81). Employment, HIV clinical stage, revenue source, body mass index, and education were the five most important predictors. CONCLUSION: We developed a prediction algorithm that could be instrumental in identifying individuals at risk for depression in the HIV-HCV co-infected population in research settings. Development of such machine learning algorithms using research data with rich predictor information can be useful for retrospective analyses of unanswered questions regarding impact of depressive symptoms on clinical and patient-centred outcomes among vulnerable populations.

Gaps in hepatitis C virus prevention and care for HIV-hepatitis C virus co-infected people who inject drugs in Canada.

BACKGROUND: People who inject drugs (PWID) living with HIV are a priority population for eliminating hepatitis C virus (HCV) as a public health threat. Maximizing access to HCV prevention and treatment strategies are key steps towards elimination. We aimed to evaluate engagement in harm reduction programs and HCV treatment, and to describe injection practices among HIV-HCV co-infected PWID in Canada from 2003 to 2019. METHODS: We included Canadian Coinfection Cohort study participants who reported injecting drugs between 2003 and 2019 in Quebec, Ontario, Saskatchewan, and British Columbia, Canada. We investigated temporal trends in HCV treatment uptake, efficacy, and effectiveness; injection practices; and engagement in harm reduction programs in three time periods based on HCV treatment availability: 1) interferon/ribavirin (2003-2010); 2) first-generation direct acting antivirals (DAAs) (2011-2013); 3) second-generation DAAs (2014-2019). Harm reduction services assessed included needle and syringe programs (NSP), opioid agonist therapy (OAT), and supervised injection sites (SIS). RESULTS: Median age of participants (N = 1,077) at cohort entry was 44 years; 69% were males. Province-specific HCV treatment rates increased among HCV RNA-positive PWID, reaching 16 to 31 per 100 person-years in 2014-2019. Treatment efficacy improved from a 50 to 70% range in 2003-2010 to >90% across provinces in 2014-2019. Drug injecting patterns among active PWID varied by province, with an overall decrease in cocaine injection frequency and increasing opioid injections. In the most recent time period (2014-2019), needle/syringe sharing was reported at 8-22% of visits. Gaps remained in engagement in harm reduction programs: NSP use decreased (58-70% of visits), OAT engagement among opioid users was low (8-26% of visits), and participants rarely used SIS (1-15% of visits). CONCLUSION: HCV treatment uptake and outcomes have improved among HIV-HCV coinfected PWID. Yet, this population remains exposed to drug-related harms, highlighting the need to tie HCV elimination strategies with enhanced harm reduction programs to improve overall health for this population.

Impact of a personalised, digital, HIV self-testing app-based program on linkages and new infections in the township populations of South Africa.

INTRODUCTION: Implementation data for digital unsupervised HIV self-testing (HIVST) are sparse. We evaluated the impact of an app-based, personalised, oral HIVST program offered by healthcare workers in Western Cape, South Africa. METHODS: In a quasirandomised study (n=3095), we recruited consenting adults with undiagnosed HIV infection from township clinics. To the HIVST arm participants (n=1535), we offered a choice of an offsite (home, office or kiosk based), unsupervised digital HIVST program (n=962), or an onsite, clinic-based, supervised digital HIVST program (n=573) with 24/7 linkages services.With propensity score analyses, we compared outcomes (ie, linkages, new HIV infections and test referrals) with conventional HIV testing (ConvHT) arm participants (n=1560), recruited randomly from geographically separated clinics. RESULTS: In both arms, participants were young (HIVST vs ConvHT) (mean age: 28.2 years vs 29.2 years), female (65.0% vs 76.0%) and had monthly income <3000 rand (80.8% vs 75%).Participants chose unsupervised HIVST (62.7%) versus supervised HIVST and reported multiple sex partners (10.88% vs 8.7%), exposure to sex workers (1.4% vs 0.2%) and fewer comorbidities (0.9% vs 1.9%). Almost all HIVST participants were linked (unsupervised HIVST (99.7%), supervised HIVST (99.8%) vs ConvHT (98.5%)) (adj RR 1.012; 95% CI 1.005 to 1.018) with new HIV infections: overall HIVST (9%); supervised HIVST (10.9%) and unsupervised HIVST (7.6%) versus ConvHT (6.79%) (adj RR 1.305; 95% CI 1.023 to 1.665); test referrals: 16.7% HIVST versus 3.1% ConvHT (adj RR 5.435; 95% CI 4.024 to 7.340). CONCLUSIONS: Our flexible, personalised, app-based HIVST program, offered by healthcare workers, successfully linked almost all HIV self-testers, detected new infections and increased referrals to self-test. Data are relevant for digital HIVST initiatives worldwide.