Statistical methods
REGRESSION, SECONDARY
Analyses will be performed using the intention-to-treat principle. Bivariate statistical tests will be used to compare variables, including results from the ACASI surveys between study groups. Given the randomized design, the primary comparison will include the absolute percentage difference and risk ratio with 95% CIs for initiation of HCV treatment (primary outcome) and will be tested using chi-square or Fisher’s exact test. Kaplan-Meier and Cox proportional hazard regression will be used to estimate associations between the interventions and outcomes when modeled using time-to-event as an outcome. One interim effectiveness analysis is planned and will be performed by the study’s biostatistician while maintaining blinding to study arm allocation. Using the approach by O’Brien-Fleming, the interim analysis will occur at the study’s halfway point, after 140 total patients (approximately 35 per arm) have been enrolled and outcomes data collected, and with an effectiveness threshold of Additional secondary analyses were planned a priori to evaluate disparities and the effects of social determinants of health (SDoH) on linkage, treatment initiation, and SVR12. Multivariable logistic regression analyses will be used to estimate the associations between gender and study outcomes while adjusting for confounders, including but not necessarily limited to age, race, ethnicity, housing status, HCV knowledge, and willingness to engage in care. Additionally, effect modifiers (e.g., race, ethnicity and gender, age and gender) will be evaluated. The statistical approach will be variable centered and will use hierarchical multivariable logistic regression to estimate associations between SDoH characteristics and linkage to care, treatment initiation, and SVR12. We will use a theoretical framework and prior studies to inform covariate selection to assess the relationships between SDoH and the outcomes.Although we do not anticipate significant missing data, multiple imputation will be used in instances where variables have > 5% missingness. No adjustments will be made for loss to follow-up as patients will be considered not linked to care after 18 months from the time of entry into the study.