The association of circadian parameters and the clustering of fatigue, depression, and sleep problems in breast cancer survivors: a latent class analysis

昼夜节律参数与乳腺癌幸存者疲劳、抑郁和睡眠问题聚集的关联:潜在类别分析

阅读:1

Abstract

PURPOSE: Circadian rhythms control a wide range of physiological processes and may be associated with fatigue, depression, and sleep problems. We aimed to identify subgroups of breast cancer survivors based on symptoms of fatigue, insomnia, and depression; and assess whether circadian parameters (i.e., chronotype, amplitude, and stability) were associated with these subgroups over time. METHODS: Among breast cancer survivors, usual circadian parameters were assessed at 3-4 months after diagnosis (T0), and symptoms of fatigue, depression, and insomnia were assessed after 2-3 years (T1, N = 265) and 6-8 years (T2, N = 169). We applied latent class analysis to classify survivors in unobserved groups ("classes") based on symptoms at T1. The impact of each of the circadian parameters on class allocation was assessed using multinomial logistic regression analysis, and changes in class allocation from T1 to T2 using latent transition models. RESULTS: We identified 3 latent classes of symptom burden: low (38%), moderate (41%), and high (21%). Survivors with a late chronotype ("evening types") or low circadian amplitude ("languid types") were more likely to have moderate or high symptom burden compared to "morning types" and "vigorous types," respectively. The majority of survivors with moderate (59%) or high (64%) symptom burden at T1 had persistent symptom burden at T2. IMPLICATIONS FOR CANCER SURVIVORS: A late chronotype and lower circadian amplitude after breast cancer diagnosis were associated with greater symptoms of fatigue, depression, and insomnia at follow-up. These circadian parameters may potentially be novel targets in interventions aimed at alleviating symptom burden among breast cancer survivors.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。