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利用数字健康客观评估癌症相关疲劳:疲劳对移动性能的影响。

Harnessing digital health to objectively assess cancer-related fatigue: The impact of fatigue on mobility performance.

机构信息

Department of Medicine, Section of Hematology and Oncology, Dan L Duncan Cancer Center, Baylor College of Medicine, Houston, Texas, United States of America.

Houston VA Center for Innovations in Quality, Effectiveness, and Safety, Michael E. DeBakey VA Medical Center, Houston, Texas, United States of America.

出版信息

PLoS One. 2021 Feb 26;16(2):e0246101. doi: 10.1371/journal.pone.0246101. eCollection 2021.

DOI:10.1371/journal.pone.0246101
PMID:33636720
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7910036/
Abstract

OBJECTIVE

Cancer-related fatigue (CRF) is highly prevalent among cancer survivors, which may have long-term effects on physical activity and quality of life. CRF is assessed by self-report or clinical observation, which may limit timely diagnosis and management. In this study, we examined the effect of CRF on mobility performance measured by a wearable pendant sensor.

METHODS

This is a secondary analysis of a clinical trial evaluating the benefit of exercise in cancer survivors with chemotherapy-induced peripheral neuropathy (CIPN). CRF status was classified based on a Functional Assessment of Chronic Illness Therapy-Fatigue (FACIT-F) score ≤ 33. Among 28 patients (age = 65.7±9.8 years old, BMI = 26.9±4.1kg/m2, sex = 32.9%female) with database variables of interest, twenty-one subjects (75.9%) were classified as non-CRF. Mobility performance, including behavior (sedentary, light, and moderate to vigorous activity (MtV)), postures (sitting, standing, lying, and walking), and locomotion (e.g., steps, postural transitions) were measured using a validated pendant-sensor over 24-hours. Baseline psychosocial, Functional Assessment of Cancer Therapy-General (FACT-G), Falls Efficacy Scale-International (FES-I), and motor-capacity assessments including gait (habitual speed, fast speed, and dual-task speed) and static balance were also performed.

RESULTS

Both groups had similar baseline clinical and psychosocial characteristics, except for body-mass index (BMI), FACT-G, FACIT-F, and FES-I (p<0.050). The groups did not differ on motor-capacity. However, the majority of mobility performance parameters were different between groups with large to very large effect size, Cohen's d ranging from 0.91 to 1.59. Among assessed mobility performance, the largest effect sizes were observed for sedentary-behavior (d = 1.59, p = 0.006), light-activity (d = 1.48, p = 0.009), and duration of sitting+lying (d = 1.46, p = 0.016). The largest correlations between mobility performance and FACIT-F were observed for sitting+lying (rho = -0.67, p<0.001) and the number of steps per day (rho = 0.60, p = 0.001).

CONCLUSION

The results of this study suggest that sensor-based mobility performance monitoring could be considered as a potential digital biomarker for CRF assessment. Future studies warrant evaluating utilization of mobility performance to track changes in CRF over time, response to CRF-related interventions, and earlier detection of CRF.

摘要

目的

癌症相关性疲劳(CRF)在癌症幸存者中普遍存在,这可能对他们的身体活动和生活质量产生长期影响。CRF 通过自我报告或临床观察进行评估,这可能限制了其及时诊断和管理。在这项研究中,我们研究了 CRF 对可穿戴吊坠传感器测量的移动性能的影响。

方法

这是一项评估运动对化疗诱导周围神经病(CIPN)癌症幸存者益处的临床试验的二次分析。CRF 状态基于功能评估慢性疾病治疗-疲劳量表(FACIT-F)评分≤33 进行分类。在具有数据库变量的 28 名患者(年龄=65.7±9.8 岁,BMI=26.9±4.1kg/m2,性别=32.9%女性)中,21 名患者(75.9%)被归类为非 CRF。使用经过验证的吊坠传感器在 24 小时内测量移动性能,包括行为(久坐、轻度和中度至剧烈活动(MtV))、姿势(坐、站、躺和行走)和运动(例如,步数、姿势转换)。还进行了基线心理社会、癌症治疗功能评估一般量表(FACT-G)、国际跌倒效能量表(FES-I)以及运动能力评估,包括步态(习惯性速度、快速速度和双重任务速度)和静态平衡。

结果

两组的基线临床和心理社会特征相似,但体重指数(BMI)、FACT-G、FACIT-F 和 FES-I 除外(p<0.050)。两组的运动能力无差异。然而,两组之间的大多数移动性能参数存在差异,效应量较大,Cohen's d 范围为 0.91 至 1.59。在评估的移动性能中,观察到最大的效应量为久坐行为(d=1.59,p=0.006)、轻度活动(d=1.48,p=0.009)和坐卧时长(d=1.46,p=0.016)。移动性能与 FACIT-F 之间的最大相关性观察到的是坐卧时长(rho=-0.67,p<0.001)和每天步数(rho=0.60,p=0.001)。

结论

本研究结果表明,基于传感器的移动性能监测可以作为 CRF 评估的潜在数字生物标志物。未来的研究需要评估利用移动性能来跟踪 CRF 随时间的变化、对 CRF 相关干预的反应以及更早发现 CRF。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4b74/7910036/41fdd5a089fd/pone.0246101.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4b74/7910036/90941ebc9ee2/pone.0246101.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4b74/7910036/41fdd5a089fd/pone.0246101.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4b74/7910036/90941ebc9ee2/pone.0246101.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4b74/7910036/41fdd5a089fd/pone.0246101.g002.jpg

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