Statistical Analysis
lung cancer, primary cancer
LUNG CANCER, PRIMARY CANCER
Based on the results of our pilot study (unpublished), a 14% responder rate in the SA group was assumed in this trial. With a dropout rate of approximately 15%, a sample size of 100 patients was estimated to provide 90% power to detect a between-group difference of 31.4 percentage points at a 2-sided The primary outcome was assessed by fitting a generalized linear model with a binomial distribution and identity link. The same approach was used for other categorical variables, such as the proportion of patients with 3 or more mean weekly SBMs and CSBMs and those with an increase of 1 or more mean weekly SBMs and CSBMs from baseline, proportions of patients using rescue medicine, and other interventions. Similar models were used for subgroup analyses based on baseline daily opioid dose (preplanned: 30-100 mg vs >100 mg oral morphine equivalent) and type of primary cancer (post hoc: lung cancer vs nonlung cancer).Changes from baseline in mean SBMs and CSBMs during weeks 1 to 8 and weeks 13 to 16 were analyzed by fitting linear mixed-effects models using treatment, visit, and treatment-by-visit interaction as fixed effects. The same approach was used for other continuous variables, such as the PAC-SYM score and the PAC-QOL score. Patients’ global response assessment, blinding, adherence, and AE data were provided for descriptive purposes only.The intention-to-treat population included all participants who were randomized according to randomized treatment assignment. Missing data on the primary outcome were imputed using the multiple imputation method under the missing at random assumption.All statistical analyses were performed according to the intention-to-treat principle using SAS, version 9.4 (SAS Institute Inc), with a 2-sided 