A mobile sensing system to monitor symptoms during chemotherapy

用于监测化疗期间症状的移动传感系统

• 批准号: 10437841
• 负责人: Carissa A Low
• 金额: $ 35.87万
• 依托单位: UNIVERSITY OF PITTSBURGH AT PITTSBURGH
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-07-01 至 2024-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10437841
• 关键词: Behavior; Behavioral; Cellular Phone; Chemotherapy-Oncologic Procedure; Classification; Clinic; Clinic Visits; Clinical; Communication; Computer Models; Coupled; Data; Detection; Development; Devices; Early Diagnosis; Enrollment; Goals; Health Status; Heart Rate; Impairment; Lead; Life; Light; Location; Machine Learning; Medical; Modeling; Monitor; Noise; Notification; Oncology; Outcome; Participant; Patient Monitoring; Patients; Pattern; Phase; Physical activity; Population; Prospective cohort study; Provider; Quality of life; Reporting; Research; Running; Secure; Severities; Sleep; Sleep disturbances; Support System; Symptoms; System; Telephone; Time; Toxic effect; Work; acceptability and feasibility; arm; base; cancer care; cancer therapy; care delivery; care outcomes; chemotherapy; common treatment; feasibility testing; health care service utilization; improved; machine learning method; mobile computing; mobile sensing; mobile sensor; multi-site trial; novel; patient-clinician communication; patient-provider contact; prospective; public health relevance; remote monitoring; sedentary lifestyle; sensor; standard of care; symptom management; trial comparing; wearable sensor technology

Cancer treatments can cause a variety of poorly-managed symptoms and toxicities that can impair quality of life and functioning and lead to early discontinuation of life-prolonging medical treatment. The goals of the proposed study are (1) to develop a novel mobile sensing system to passively monitor symptom burden during chemotherapy and (2) to evaluate the feasibility and acceptability of using this system to recommend patient-provider communication. To accomplish Aim 1, we will enroll 200 oncology patients starting a new chemotherapy regimen and will collect smartphone and wearable sensor data continuously as well as daily patient-reported symptoms via smartphones for 90 days. Using machine learning methods, we will retrospectively analyze data from the first 100 participants and develop a generalizable and parsimonious population-level model to identify severe symptom days. For the second 100 participants, we will run these computational models in real-time and prospectively evaluate the accuracy of our classifications relative to patient-reported symptoms. For Aim 2, we will enroll 50 patients in a prospective single-arm trial of a system that uses inferences based on sensing and machine learning to recommend contact with providers and will evaluate patient accrual, attrition, and compliance as well as information from both patients and their providers about acceptability and perceived usefulness of the system. The scientific premise of this proposal is that mobile sensing of subtle fluctuations in behavior coupled with real-time computational modeling could enable earlier detection and ultimately better management of severe symptoms during cancer treatment. The proposed project builds on our prior research and completes the necessary development and feasibility work to support a large multisite trial comparing the mobile sensing system to standard of care to determine effects on symptom burden, quality of life, health care utilization, and survival.

癌症治疗可能会导致各种管理不良的症状和毒性 损害生活质量和功能，并导致早期终止生命 医疗。拟议的研究的目标是（1）开发一种新型的移动感应 在化学疗法期间被动监测症状负担的系统，（2）评估 使用该系统推荐患者提供者的可行性和可接受性 沟通。为了完成AIM 1，我们将招募200名肿瘤学患者开始新的 化学疗法方案，并将连续收集智能手机和可穿戴传感器数据 以及日常通过智能手机报告的症状90天。使用机器学习 方法，我们将回顾性地分析前100名参与者的数据，并开发 可鉴定出严重症状的日子的可概括和副群体级别模型。为了 第二名参与者，我们将实时运行这些计算模型 前瞻性评估我们的分类相对于患者报告的症状的准确性。 对于AIM 2，我们将在一个使用的系统的前瞻性单臂试验中注册50名患者 基于感应和机器学习的推论，建议与提供者联系，并 将评估患者的应计，流失和依从性以及两名患者的信息 以及他们的提供者关于系统的可接受性和感知有用性。科学 该提议的前提是，行为中微妙波动的移动感以及 实时计算建模可以实现早期检测，最终可以更好 癌症治疗期间严重症状的治疗。拟议的项目建立在我们的基础上 事先研究并完成必要的发展和可行性工作，以支持大型 将移动传感系统与护理标准进行比较的多站点试验，以确定对 症状负担，生活质量，医疗保健利用和生存。