Statistical analysis
death
EVENTS
Median number of sick leave days was compared with the Kruskal Wallis test. We estimated time until sustainable RTW (one month without receiving any medical benefits) using Kaplan Meier curves and log rank test. Hazard ratios (HR) were estimated using Cox proportional model with Efron method for ties. Time was calculated as number of days and participants were censored when they achieved sustainable RTW, death, or at the end of follow-up. Analyses were performed unadjusted and adjusted for age (continuous), gender, education, main diagnosis for sick leave and length and type (full/partial) of sick leave at inclusion. Probability of not receiving any medical benefits each month during follow-up was analyzed as repeating events with logistic General Estimating Equations (GEE). We used an exchangeable correlation structure and without robust standard errors. The analyses were performed unadjusted and adjusted (with the beforementioned variables). All analyses were performed in line with the intention-to-treat principle. In, addition we calculated an estimated per-protocol effect for MI compared to usual case management, adjusting for possible confounding factors of compliance (age, gender, education, and diagnosis).Precision was assessed using 95% confidence intervals (CI). The statistical analysis plan (SAP) was published at ClinicalTrials.gov (no. NCT03212118) prior to the completion of inclusion (ie, before analyses were started). All analyses were done using STATA 17.0 (StataCorp LLC, Stata Statistical Software: release 17. College Station, TX, USA).