通过 NeuroDetect iOS 应用程序远程监测化疗引起的周围神经病变:癌症患者观察性队列研究》。

IF 6 2区 医学 Q1 HEALTH CARE SCIENCES & SERVICES Journal of Medical Internet Research Pub Date : 2025-02-05 DOI:10.2196/65615
Ciao-Sin Chen, Michael P Dorsch, Sarah Alsomairy, Jennifer J Griggs, Reshma Jagsi, Michael Sabel, Amro Stino, Brian Callaghan, Daniel L Hertz
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引用次数: 0

摘要

背景:化疗引起的周围神经病变(CIPN)是一种常见的神经毒性化疗不良反应,其特征是麻木、刺痛和虚弱。有效监测和检测CIPN对于避免发展为不可逆症状至关重要。由于临床客观评估的不便,CIPN的检测主要依赖于患者对主观症状的报告,并且使用患者报告的结果来促进CIPN的检测。我们之前的研究发现,在智能手机应用程序中完成的客观功能评估可以在治疗后区分患有和没有CIPN的患者。目的:本前瞻性、纵向观察队列研究旨在确定基于app的CIPN远程监测在接受神经毒性化疗的癌症患者中的可行性和准确性,并对基于app的功能CIPN监测与患者报告的仅结果监测进行探索性比较。方法:NeuroDetect应用程序(Medable Inc)包括主观的EORTC(欧洲癌症研究和治疗组织)生活质量问卷(QLQ)-20项量表(CIPN20)和6个客观功能评估,使用智能手机传感器模拟神经学检查,如行走、站立和手灵巧性测试。收集接受神经毒性化疗的癌症患者的功能评估数据,并在治疗结束时进行神经学检查以诊断足部CIPN (CIPN-f)或手部CIPN (CIPN-h)。各种分类模型,包括仅神经检测特征(神经检测模型)仅CIPN20 (CIPN20模型)或两者的组合(组合模型)进行训练并评估预测CIPN概率的准确性。结果:在完成功能评估和神经学检查的45例患者中,24例CIPN-f, 29例CIPN-h。NeuroDetect模型可以区分有CIPN-f和没有CIPN-f的患者(曲线下面积=83.8%,与无信息率P= 0.02相比),但不能区分有CIPN-h的患者(曲线下面积=67.9%,P= 0.18)。Romberg姿态评估中闭眼阶段的滚动旋转特征对CIPN-f的贡献最大(占总变量重要性的40%),而手指敲击评估对CIPN-h的贡献最大(占总变量重要性的85%)。在数值上,在某些时间点上,NeuroDetect模型在CIPN-f和CIPN-h上的表现优于CIPN20模型,特别是在治疗前和早期。联合模型在数值上(尽管不是统计上)单独优于两种评估策略,这表明智能手机内功能和患者报告评估的结合可能是CIPN检测的最佳选择。结论:我们的研究结果证明了将主客观CIPN评估整合到智能手机应用程序中进行CIPN远程纵向监测的可行性。需要对更大的患者群体进行研究,以完善基于应用程序的CIPN检测模型,并确定它们在实践中的使用是否改善了CIPN检测。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Remote Monitoring of Chemotherapy-Induced Peripheral Neuropathy by the NeuroDetect iOS App: Observational Cohort Study of Patients With Cancer.

Background: Chemotherapy-induced peripheral neuropathy (CIPN) is a common and debilitating adverse effect of neurotoxic chemotherapy characterized by symptoms such as numbness, tingling, and weakness. Effective monitoring and detection of CIPN are crucial for avoiding progression to irreversible symptoms. Due to the inconvenience of clinic-based objective assessment, CIPN detection relies primarily on patients' reporting of subjective symptoms, and patient-reported outcomes are used to facilitate CIPN detection. Our previous study found evidence that objective functional assessments completed within a smartphone app may differentiate patients with and those without CIPN after treatment.

Objective: This prospective, longitudinal observational cohort study aimed to determine the feasibility and accuracy of app-based remote monitoring of CIPN in patients with cancer undergoing neurotoxic chemotherapeutic treatment and to conduct exploratory comparisons of app-based functional CIPN monitoring versus patient-reported outcome-only monitoring.

Methods: The NeuroDetect app (Medable Inc) includes subjective EORTC (European Organization for Research and Treatment of Cancer) Quality of Life Questionnaire (QLQ)-20-item scale (CIPN20) and 6 objective functional assessments that use smartphone sensors to mimic neurological examinations, such as walking, standing, and manual dexterity tests. The functional assessment data were collected from patients with cancer undergoing neurotoxic chemotherapy, and a neurological examination was conducted at the end of treatment to diagnose CIPN in the feet (CIPN-f) or CIPN in the hands (CIPN-h). Various classification models including NeuroDetect features only (NeuroDetect Model) CIPN20-only (CIPN20 Model) or a combination of both (Combined Model) were trained and evaluated for accuracy in predicting CIPN probability.

Results: Of the 45 patients who completed functional assessments and neurological examinations, 24 had CIPN-f, and 29 had CIPN-h. The NeuroDetect Model could discriminate between patients with and those without CIPN-f (area under the curve=83.8%, comparison with no information rate P=.02) but not CIPN-h (area under the curve=67.9%, P=.18). The rolling rotation features from the eyes-closed phase of the Romberg Stance assessment showed the greatest contribution to CIPN-f (40% of total variable importance) and the Finger Tapping assessment showed the greatest contribution to CIPN-h (85% of total variable importance). The NeuroDetect Model had numerically, and at some time points statistically, superior performance to the CIPN20 Model in both CIPN-f and CIPN-h, particularly before and early in treatment. The Combined Model numerically, though not statistically, outperformed either assessment strategy individually, indicating that the combination of functional and patient-reported assessment within a smartphone may be optimal to CIPN detection.

Conclusions: Our findings demonstrate the feasibility of integrating subjective and objective CIPN assessment into a smartphone app for remote, longitudinal CIPN monitoring. Studies of larger patient cohorts are needed to refine the app-based CIPN detection models and determine whether their use in practice improves CIPN detection.

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来源期刊
CiteScore
14.40
自引率
5.40%
发文量
654
审稿时长
1 months
期刊介绍: The Journal of Medical Internet Research (JMIR) is a highly respected publication in the field of health informatics and health services. With a founding date in 1999, JMIR has been a pioneer in the field for over two decades. As a leader in the industry, the journal focuses on digital health, data science, health informatics, and emerging technologies for health, medicine, and biomedical research. It is recognized as a top publication in these disciplines, ranking in the first quartile (Q1) by Impact Factor. Notably, JMIR holds the prestigious position of being ranked #1 on Google Scholar within the "Medical Informatics" discipline.
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