High Prevalence of Insomnia in Breast Cancer Patients: Exploring Feasibility and Potential Benefits of a Digital Sleep Diary – A Two-Stage Observational Study (Preprint)

Author:

Pilecka IzabelaORCID,Richardson LeanneORCID,Noori NihalORCID,Taylor MikeORCID,Berger LouiseORCID,Godec ThomasORCID,Goldsmith PaulORCID,Siddle JamesORCID,Brammer ZoeORCID,Galasso EmmaORCID,Armstrong AnneORCID

Abstract

BACKGROUND

Insomnia affects a significant proportion of the general population, including breast cancer patients. However, the reported prevalence of insomnia in breast cancer patients shows considerable heterogeneity across research findings. There is a need to better understand the prevalence and impact of insomnia in breast cancer patients and to explore digital interventions as potential solutions to improve their sleep quality and overall well-being.

OBJECTIVE

Our study aimed to determine insomnia prevalence in breast cancer patients, using the validated patient-reported Insomnia Severity Index (ISI). Over a three-week period, we evaluated insomnia severity, sleep efficiency (via the Closed Loop Medicine (CLM) digital sleep diary), and quality of life (using EQ-5D-5L and FACT-ES). Feasibility and experience of patients inputting sleep data into the CLM digital sleep diary were examined as well as safety of using the app.

METHODS

This prospective decentralized remote observational study was conducted in the community in two stages. In the first stage, eligible patients completed the ISI to determine insomnia prevalence. Patients with an ISI score of ≥8 were assessed for eligibility to continue to the second stage. In Stage 2, eligible patients downloaded the CLM digital sleep diary on their smartphones, completing daily entries over a three-week observation period. At completion, patients filled out questionnaires and underwent additional procedures.

RESULTS

A total of 220 patients completed Stage 1, of which 105 patients were available for analysis in Stage 2. Mean age was 54 years (SD 10), 99% identified as female, 92% were of White ethnicity, 74% were married or living with their partner, 46% had attended university-level education, 51% were employed, and 56% were postmenopausal. A high proportion (77%) experienced some level of insomnia: 41% subthreshold, 32% moderate, and 4% severe. 23% of Stage 1 patients were ineligible for Stage 2. Insomnia severity levels remained relatively stable during the three-week period. In Stage 1, patients without insomnia symptoms reported better quality of life. In Stage 2, EQ-5D-5L revealed consistent issues with pain/discomfort, anxiety, depression, and limited activities during the three-week period. FACT-ES data indicated reduced quality of life throughout the three-week period. 97 out of 105 patients (92%) provided sleep diary data. Mean sleep efficiency was 79% (SD 10.7%), with a range of 40% to 95%, remaining stable over the three-week period. Mean diary compliance was 80% (SD 24%). Most UEQ items achieved a positive mean score >0.8 (19 out of 26 items, 73%). No adverse events were associated with the CLM digital sleep diary.

CONCLUSIONS

Insomnia symptoms were highly prevalent among breast cancer patients and most patients experienced reduced sleep efficiency and quality of life. Our study demonstrates the feasibility, acceptability, and safety of patients self-inputting sleep-related data into a dedicated smartphone application. Based on the evidence gathered, future interventions using the CLM digital sleep diary can be explored for breast cancer patients with insomnia. A large-scale RCT combining the CLM digital sleep diary with insomnia medication (drug + digital) could be considered for precision management of insomnia.

Publisher

JMIR Publications Inc.

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3