Center for Research Innovation and Biomedical Informatics, Faculty of Medical Technology, Mahidol University, Nakhon Pathom, Thailand.
The George Washington University School of Engineering & Applied Science Science & Engineering Hall, Washington, DC, USA.
BMC Palliat Care. 2024 Mar 2;23(1):62. doi: 10.1186/s12904-024-01392-9.
Breakthrough cancer pain (BTCP) is primarily managed at home and can stem from physical exertion and emotional distress triggers. Beyond these triggers, the impact of ambient environment on pain occurrence and intensity has not been investigated. This study explores the impact of environmental factors on the frequency and severity of breakthrough cancer pain (BTCP) in the home context from the perspective of patients with advanced cancer and their primary family caregiver.
A health monitoring system was deployed in the homes of patient and family caregiver dyads to collect self-reported pain events and contextual environmental data (light, temperature, humidity, barometric pressure, ambient noise.) Correlation analysis examined the relationship between environmental factors with: 1) individually reported pain episodes and 2) overall pain trends in a 24-hour time window. Machine learning models were developed to explore how environmental factors may predict BTCP episodes.
Variability in correlation strength between environmental variables and pain reports among dyads was found. Light and noise show moderate association (r = 0.50-0.70) in 66% of total deployments. The strongest correlation for individual pain events involved barometric pressure (r = 0.90); for pain trends over 24-hours the strongest correlations involved humidity (r = 0.84) and barometric pressure (r = 0.83). Machine learning achieved 70% BTCP prediction accuracy.
Our study provides insights into the role of ambient environmental factors in BTCP and offers novel opportunities to inform personalized pain management strategies, remotely support patients and their caregivers in self-symptom management. This research provides preliminary evidence of the impact of ambient environmental factors on BTCP in the home setting. We utilized real-world data and correlation analysis to provide an understanding of the relationship between environmental factors and cancer pain which may be helpful to others engaged in similar work.
突破性癌症疼痛（BTCP）主要在家庭中进行管理，可能由身体活动和情绪困扰引发。除了这些诱因之外，环境因素对疼痛发生和强度的影响尚未得到研究。本研究从晚期癌症患者及其主要家庭照顾者的角度探讨了环境因素对家庭环境中突破性癌症疼痛（BTCP）发生频率和严重程度的影响。
在患者和家庭照顾者二人组的家中部署健康监测系统，以收集自我报告的疼痛事件和环境数据（光线、温度、湿度、大气压、环境噪声）。相关性分析检查了环境因素与以下方面的关系：1）单独报告的疼痛发作和 2）24 小时时间窗口内的总体疼痛趋势。机器学习模型用于探索环境因素如何预测 BTCP 发作。
在二人组之间，环境变量与疼痛报告之间的相关性强度存在差异。光和噪声在 66%的总部署中显示出中等关联（r=0.50-0.70）。个体疼痛事件的最强相关性涉及大气压（r=0.90）；24 小时内疼痛趋势的最强相关性涉及湿度（r=0.84）和大气压（r=0.83）。机器学习实现了 70%的 BTCP 预测准确率。
我们的研究提供了有关环境因素在 BTCP 中的作用的见解，并为告知个性化疼痛管理策略、远程支持患者及其照顾者进行自我症状管理提供了新的机会。本研究初步证明了环境因素对家庭环境中 BTCP 的影响。我们利用真实世界的数据和相关性分析，了解了环境因素与癌症疼痛之间的关系，这可能对从事类似工作的其他人有所帮助。
