Statistical analysis
REGRESSION
Overlap weighting was used to address the imbalance in baseline characteristics between treatment groups (Changes in study outcomes from baseline values, between-group differences and corresponding 95% confidence intervals (CI) were estimated using weighted mixed-effects regression models. The weights were obtained from the procedure described above. These models were also used to plot the estimated means at different time points for both groups. A linear mixed-effects quantile regression model was used to estimate the conditional median of the TBR due to the high degree of asymmetry in the distribution of this outcome (The statistical significance of the between-group differences was evaluated using the likelihood ratio test, testing the significance of the treatment by time interaction.To adjust for multiple testing, the Benjamini and Hochberg’s False Discovery Rate procedure was used (The analysis was performed using R version 4.3.0 (2023-04-21 ucrt). The “lmer” function from the “lme4” package and the “lqmm” function from the “lqmm” package were used to fit the linear mixed-effects regression models and the quantile mixed-effects regression models, respectively. 