Here is the design of a clinical trial:

Official Title: Eurythmy Therapy (ERYT) as a Treatment Option for Fatigue in Metastatic Breast Cancer Patients

Included conditions:
- Fatigue
- Breast Cancer

Study Armgroups:
- {'label': 'Eurythmy therapy (ERYT)', 'type': 'EXPERIMENTAL', 'description': 'Eurythmy therapy (ERYT) is a standardized movement therapy and for each medical condition standardized ERYT exercise (series) exist. In such, in the present study, the cancer series "O-E-M-L-I-B-D" that is specific and standardized for breast cancer patients will be applied. Patients can perform and maintain the postures without stress and tension. Patients are instructed by ERYT therapists in sessions with 1 to 4 patients.', 'interventionNames': ['Other: Eurythmy therapy']}
- {'label': 'CoordiFit', 'type': 'ACTIVE_COMPARATOR', 'description': 'The CoordiFit program consists of standardized exercises that address physical coordination, stability, balance and dexterity. These exercises serve as a control intervention and are non-specific with respect of cancer-related fatigue and breast cancer. They mimic those of ERYT but have no mindfulness features. Patients are instructed by physical therapists in session with 1 to 4 patients.', 'interventionNames': ['Other: CoordiFit']}

Interventions:
- {'type': 'OTHER', 'name': 'Eurythmy therapy', 'description': 'Mind-body therapy', 'armGroupLabels': ['Eurythmy therapy (ERYT)']}
- {'type': 'OTHER', 'name': 'CoordiFit', 'description': 'Fitness training', 'armGroupLabels': ['CoordiFit']}

Primary Outcomes:
- {'measure': 'Change from baseline in fatigue over the whole intervention', 'description': 'Fatigue is measured using the Functional Assessment of Chronic Illness Therapy-Fatigue (FACIT-F). FACIT-F consists of the Functional Assessment of Cancer Therapy - General (FACT-G) plus the fatigue subscale comprising 13 fatigue-related items, with a total of 41 items. The fatigue subscale score is ranging from 8 to 44. A score \\< 34 is considered as cut-off for a diagnosis of relevant fatigue.', 'timeFrame': 'End of the intervention (week 20)'}

Please estimate the sample size based on the assumption: 
The mean FACIT-F subscale score at baseline for the two groups is assumed to be 30 points with a standard deviation of 10 points. The study aims for a power of ≥ 80% to reject the null hypothesis at the α = 0.05 level. The standard deviation of the FACIT-F subscale score should be ≤ 12 points, and the within-patient variation between two measurements should be ≤ 8 points. A dropout rate of 20% is accounted for.
Sample size calculation and statistical analysis
        
          Sample size
          Eurythmy therapy is expected to have a greater effect on CRF than the control intervention. A validated Minimal Clinically Important Difference (MCID) for FACIT-F subscale is defined as a change in score of 3â4 points [62]. We assume a non-parallel course over time of the FACIT-F subscale score between the ERYT group and the control group and a difference â¥â4 in the FACIT-F subscale score between the two groups at the end of the intervention (week 20).
          The mean FACIT-F subscale score at baseline for the two groups was assumed to be 30 points with a standard deviation of 10 points [60]. Simulations confirmed that the sample size of Nâ=â156 patients (excluding drop-outs) will provide enough power (â¥â80%) to reject the null-hypothesis of no interaction between the group and time at the Î±â=â0.05 level, if the effect of the ERYT intervention on the FACIT-F subscale score at the end of therapy is 4 points, if the standard deviation of the FACIT-F subscale score is â¤â12 points, and if the within-patient variation between two measurements is â¤â8 points. The simulations also confirmed that the power of 80% is reached in case of slight deviations from the assumptions if the difference between groups â¥â4 points at the end of the intervention. To account for a dropout rate of 20%, the total sample size will be Nâ=â196 patients (98 per group).
          In order to ensure the study population can comply with the intervention as excepted, we will check feasibility issues, i.e., the number of sessions completed and compliance with home training, after the inclusion of 50 patients.
        
        
          Statistical analysis
          A nonparametric ANOVA model for longitudinal data, the F1-LD-F1 model of Brunner, Domhof, and Langer, will be applied to model the course of the FACIT-F subscale scores from baseline over the whole intervention [77]. The first F1 means that there is one group factor, the second that there is one-time or repeated measures factor. The main hypotheses are the following:
          H0: there is no interaction of the treatment arm with the time;
          H1: there is an interaction of the treatment arm with the time (favoring ERYT).
          Least-square means of the original data (original scales) and 95% confidence intervals will be calculated and displayed in figures over time.
          Differences from baseline to end of intervention will be analyzed by stratified Wilcoxon rank-sum tests (via ordinal logistic regression, i.e., proportional odds model with baseline measurements as co-variable, treatment arm as binary predictor and differences as outcome variable). Least-squares means of the original differences and 95% confidence intervals will be calculated.
          Exploratory endpoints will be analyzed descriptively using mean and standard deviation or median and interquartile, as appropriate.
          Statistical analysis will be conducted applying an intention-to-treat approach, and therefore including all randomized patients. In case of protocol non-adherence, a per-protocol analysis will be conducted to estimate the robustness of the primary estimates. All tests will be two-sided with a significance level of 0.05. Statistical analysis will be performed using R [78].