Statistical analysis
viral suppression
REGRESSION, SECONDARY
According to routine cohort data from the study districts [The analysis followed an intention-to-treat approach, including all enrolled participants as randomized. Health facilities (clusters) were the unit of randomization, whereas individuals were the unit of analysis, with viral suppression as a binary outcome. All participants missing their blood draw or having invalid VL results were classified as not meeting the viral suppression endpoints. For the analysis of the primary endpoint, we used a multilevel logistic regression model including cluster (health facility) as a random effect, and arm allocation and the randomization stratification factor (district) as a fixed effect. According to the procedure outlined in our statistical analysis plan, we first assessed all baseline tables for clinically important random imbalanced factors. We noted a substantial random imbalance in sex and thus decided to adjust for it in all analyses.For the secondary endpoints, we used the complete case set. The secondary endpoints of alternative viral suppression threshold, engagement in care, transfer out, LTFU, and mortality were analysed using a logistic regression model with the same explanatory variables as the primary analysis model. To compare perfect adherence between the 2 arms, we used the same model, but additionally adjusted for self-reported perfect adherence at enrolment and the treatment taken at the time point under consideration (dolutegravir (DTG) versus non-dolutegravir). Differences of QoL between the 2 arms were assessed using multilevel mixed effect linear regression models, adjusted for sex and additionally the respective QoL scores at enrolment. Similarly, satisfaction with care was assessed using a multilevel mixed effect logistic regression model with outcome “very satisfied with care” at 12 months, adjusted for sex and additionally the respective satisfaction at baseline. From the logistic regression models, results are presented as odds ratios (ORs) with 95% confidence interval (CI) and from the linear regression model as beta coefficients with 95% CI. We performed prespecified sensitivity analyses for the primary endpoint: adjustment for baseline VL, using a wider primary endpoint visit window (9 to 18 months), and restricting to the individual per protocol set (participants who attended both the 6-month and 12-month study visit). For the primary outcome, we also assessed effect modification by prespecified variables (age groups, sex, marital status, occupational status, time of ART exposure, DTG at time of endpoint). All analyses were done using R, version 4.0.3 (2020-10-10).