Symptom Measurement and Interrelationships During Chemotherapy for Ovarian Cancer

描述（由申请人提供）：研究强调了卵巢癌化疗期间疲劳和抑郁的流行和破坏性。现在需要有效的干预措施来减少疲劳和抑郁，但这种干预措施的发展受到目前理解的差距的阻碍：1）引起疲劳和抑郁的因素，以及2）评估这些症状的最佳方法。目前的建议扩展了先前的研究，表明卵巢癌患者的疲劳和抑郁可能与睡眠/活动昼夜节律模式的破坏有关（即，在24小时内睡眠和身体活动行为的节律性中断）。拟议的研究将模拟卵巢癌化疗前三个周期期间疲劳，抑郁和睡眠/活动昼夜节律模式之间的纵向变化和相互关系。此外，它将比较疲劳和抑郁的两种不同评估方法获得的结果：回顾性自我报告和实时评估。具体目标是：1）检查化疗开始前和前三次输注期间疲劳、抑郁和睡眠/活动昼夜节律模式的变化; 2）检查疲劳、抑郁和睡眠/活动昼夜节律模式之间关系的竞争模型; 3）检查疲劳和抑郁的回顾性自我报告的准确性。据推测，症状之间的变化率将是相关的，并将遵循周期性模式，在每次化疗输注后的几天内急剧增加，然后逐渐下降。此外，假设症状遵循级联模式，其中睡眠/活动昼夜节律模式的中断导致疲劳，这反过来又导致抑郁症。最后，据推测，回顾性自我报告的疲劳和抑郁症将不准确比实时评估，特别是当症状的变异性很高。这些假设将通过收集前三次化疗输注前后三、两周内的实时和回顾性疲劳和抑郁数据进行检查。在这些时间段内，将通过活动记录仪记录睡眠/活动昼夜节律模式，活动记录仪是一种佩戴在非优势手腕上测量运动的设备。这项拟议的研究将有助于更好地了解疲劳，抑郁和睡眠/活动昼夜节律模式之间的过程和相互关系，这将作为开发行为干预以减少卵巢癌患者症状的基础。此外，拟议的研究将检查回顾性自我报告的准确性，这是一种常见的症状测量方法。准确的测量对于评估新干预措施的有效性至关重要，以确保患者获得最高质量的护理。更好地了解化疗期间常见症状之间的关系可能有助于制定更有效的干预措施来预防或减少这些症状，从而改善公共卫生。此外，准确的测量对于评估新干预措施的有效性至关重要，以确保患者获得最高质量的护理。这项研究将模拟疲劳、抑郁和睡眠/活动昼夜节律模式之间随时间的变化和关系，并检查评估症状的常用方法的准确性。

DESCRIPTION (provided by applicant): Research has highlighted the prevalence and disruptiveness of fatigue and depression during chemotherapy for ovarian cancer. Effective interventions are now needed to reduce fatigue and depression, but development of such interventions is hampered by gaps in current understanding of: 1) the factors that give rise to fatigue and depression, and 2) the best methods of assessing these symptoms. The current proposal extends previous research suggesting that fatigue and depression in ovarian cancer patients may be associated with disruptions in sleep/activity circadian patterns (i.e., disruptions in the rhythmicity of sleep and physical activity behaviors over a 24 hour period). The proposed study will model longitudinal changes and inter-relationships between fatigue, depression, and sleep/activity circadian patterns during the first three cycles of chemotherapy for ovarian cancer. Additionally, it will compare results obtained by two different assessment methods of fatigue and depression: retrospective self-report and real-time assessment. The specific aims are: 1) to examine changes in fatigue, depression, and sleep/activity circadian patterns prior to initiation of chemotherapy and across the first three infusions; 2) to examine competing models of relationships between fatigue, depression, and sleep/activity circadian patterns; 3) to examine the accuracy of retrospective self-reports of fatigue and depression. It is hypothesized that rates of change between symptoms will be correlated and will follow a cyclical pattern, increasing dramatically in the days following each chemotherapy infusion, then declining gradually. Further, it is hypothesized that symptoms follow a cascade pattern, in which disruptions in sleep/activity circadian patterns contribute to fatigue, which in turn contributes to depression. Finally, it is hypothesized that retrospective self-reports of fatigue and depression will be less accurate than real-time assessment, particularly when symptom variability is high. These hypotheses will be examined by collecting real-time and retrospective fatigue and depression data during three, two week periods surrounding each of the first three chemotherapy infusions. Sleep/activity circadian patterns will be recorded during these periods through an actigraph, a device worn on the non-dominant wrist that measures motion. The proposed study will contribute to a better understanding of the course and inter-relationships between fatigue, depression, and sleep/activity circadian patterns, which will serve as the basis for developing a behavioral intervention to reduce symptoms in ovarian cancer patients. In addition, the proposed study will examine the accuracy of retrospective self-reports, a common measure of symptoms. Accurate measurement is essential to assess the efficacy of new interventions, ensuring that patients receive the highest quality care. A better understanding of the relationships between common symptoms during chemotherapy may be helpful in developing more effective interventions to prevent or reduce these symptoms, thereby improving public health. Additionally, accurate measurement is essential to assess the efficacy of new interventions, ensuring that patients receive the highest quality care. The proposed study will model change and relationships over time between fatigue, depression, and sleep/activity circadian patterns, as well as examine the accuracy of a common method of assessing symptoms.