Statistical analysis
RPE, CRF, diabetes
CARDIOVASCULAR DISEASE, CRF, HYPERTENSION, OSTEOPOROSIS, DIABETES
As this was a pragmatic trial, we aimed to recruit as many patients as possible. To calculate the achieved power, we used the primary endpoint of FACIT-F score at immediately post-RT, as we hypothesized that the effect of exercise on CRF would be the strongest at that time point. Achieved power was calculated using G*Power (Version 3.1.9.7, Universitat Kiel, Germany). At post-RT, the difference between groups had an effect size of A linear mixed-effects model was used with participant ID as the random-effects factor, while fixed-effects factors consisted of demographic and physical characteristics (age, baseline body fat percentage), physical symptoms and conditions (hypertension, high cholesterol, cardiovascular disease, diabetes, osteoporosis), and cancer-specific treatments before and during the intervention (chemotherapy, hormone therapy, surgery), as well as exercise dosage for the exercise group only (number of resistance and aerobic sessions, number of resistance exercises, duration of aerobic exercise, and RPE during resistance and aerobic exercise). The assumption of normality and homoscedasticity of the residuals was verified by visual quantile–quantile plot inspection of the plots and a Shapiro–Wilk test. In the case of a significant interaction effect, pairwise comparisons were performed between conditions and timepoints, with a Holm's 