Sleep Disorders Prior to and During a Course of Radiotherapy for Breast Cancer

Summary

Participation Requirements

Description

The majority of breast cancer patients receive adjuvant radiotherapy, either following breast-conserving surgery or mastectomy. The situation that a patient needs to be irradiated may cause distress due to a sense of menace in view of the technology, fear of the exposure to radiation and fear of rad...

The majority of breast cancer patients receive adjuvant radiotherapy, either following breast-conserving surgery or mastectomy. The situation that a patient needs to be irradiated may cause distress due to a sense of menace in view of the technology, fear of the exposure to radiation and fear of radiation-related adverse effects. These fears and other factors may lead to sleep disorders. In a previous the study, cancer patients reported the most sleep disorders prior to and at the beginning of radiotherapy. The patients appeared to develop coping strategies during the treatment. In another study, an increase of insomnia was observed during the course of radiotherapy due to treatment-related side effects. In general, very little is known about the prevalence of sleep disorders prior and during a radiotherapy course. This study mainly aims to evaluate the course of sleep disorders during radiotherapy for breast cancer. To assess the rate of patients with decrease of sleep disorders during the course of radiotherapy compared to baseline, defined as Decrease of severity of sleep disorders by at least 2 points on a patient self-rating scale (0=no problems; 10=maximum problems) or Decrease of distress caused by sleep disorders by at least 2 points on a patient self-rating scale (0=no distress; 10=maximum distress) or Reduction of the dose of sleeping drugs by at least 25%. The required sample size of N=51 (including drop-outs) is set at the maximum that is deemed achievable in this study within the timeframe of the study given the size of the target population. However, with this sample size a one-sample binomial test with a one-sided significance level of 2.5% has a power of 80% to yield statistical significance if the rate of patients with decrease of sleep disorders during the course of radiotherapy compared to baseline is 25% (rate under the alternative hypothesis) and assuming that a decrease of only 10% or less has to be judged as a random, non-causal change in this uncontrolled study setting (null hypothesis). The latter rate was chosen after respective discussions with experts. The focus of the statistical analysis is descriptive and exploratory in nature. If statistical tests are applied beyond the prespecified statistical hypothesis testing for the primary study endpoint, they are to be interpreted on an exploratory perspective. All data recorded in the case report forms describing the study population (demographic and clinical characteristics, at baseline) will be analyzed descriptively. Categorical data will be presented in tables with frequencies and percentages. Continuous data will be summarized with at least the following: frequency (n), median, quartiles, mean, standard deviation (standard error), minimum and maximum. Number of patients with protocol deviations during the study and listings describing the deviations will be provided. Sleep disorders at baseline and during the course of radiotherapy will be rated using two patient self-reporting scales (sleep disorders and distress) and the intake of sleeping drugs. To evaluate the rate of patients with decrease of sleep disorders during the course of radiotherapy compared to baseline, the dichotomized composite endpoint is considered. The point estimate of the rate of decrease and the associated 95% confidence interval will be presented. To test whether the rate of decrease is significantly greater than 10%, the one-sided binomial test at a one-sided 2.5% significance level will be applied. To further assess the potential impact of other relevant factors on the primary study endpoint stratified analyses will be conducted. The associated factors of particular importance are sleeping disorders at baseline (? median score on sleep disorder self-rating scale vs.> median score) and the use of smartphones at bedtime (? median score vs. > median score). Furthermore, a logistic regression model including sleep disorder rating scale at baseline (? median score on sleep order self-rating scale vs.> median score), the use of smartphones / tablets at bedtime (? median score vs. > median score) and other factors, namely age, type of breast surgery, systemic anticancer treatment, body mass index, co-morbidity will be fitted to identify potentially relevant prognostic factors for the decrease of sleep disorders. Adjusted odds ratios and 95% confidence interval (Wald ?2) will be derived thereof. In addition, each component of the primary composite endpoint will be subjected to statistical analyses to evaluate the sleep disorders during the course of the study using descriptive statistical methods. These analyses allow for detailed assessment of the scales over time taking into account potential decrease as well potential increase in sleep orders. For graphical visualization Spaghetti-plots and Box-Whisker diagrams will be provided. Moreover, the change from baseline values will be considered and subjected to descriptive analyses. Friedman tests and Wilcoxon-Mann Whitney tests may be applied for comparison of study visits. Cumulative distribution plots of changes from baseline at each visit will be presented; these plots will display a continuous change from baseline on the x-axis and the cumulative percentage of patients experiencing that change on the y-axis. The above mentioned analyses will be further stratified by sleeping disorders at baseline (? median score on sleep disorder self-rating scale vs.> median score) and the use of smartphones at bedtime (? median score vs. > median score). For further exploratory analysis, the rates of patients experiencing any sleep disorders (yes/no) at each time will be estimated together with their associated confidence intervals; these analyses will also be stratified by sleeping disorders at baseline and the use of smartphones at bedtime. The recruitment of all 51 patients (48 patients plus 5% drop-outs) should be completed within 4.5 months. The radiotherapy period will be 3-6.5 weeks. This equals a total running time for the study of approximately 6 months.The recruitment of all 51 patients (48 patients plus 5% drop-outs) should be completed within 4.5 months. The radiotherapy period will be 3-6.5 weeks. This equals a total running time for the study of approximately 6 months.

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