Department Artificial Intelligence in Biomedical Engineering (AIBE), Machine Learning and Data Analytics Lab, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany.
Department of Gynecology and Obstetrics, Erlangen University Hospital, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany.
Oncologist. 2023 Oct 3;28(10):e847-e858. doi: 10.1093/oncolo/oyad217.
Breast cancer is affecting millions of people worldwide. If not appropriately handled, the side effects of different modalities of cancer treatment can negatively impact patients' quality of life and cause treatment interruptions. In recent years, mobile health (mHealth) interventions have shown promising opportunities to support breast cancer care. Numerous studies implemented mobile health interventions aiming to support patients with breast cancer, for example, through physical activity promotion or educational content. Nonetheless, current literature reveals that real-world evidence for the actual benefits remains unclear. In this systematic review, we focus on analyzing the methodology used in recent studies to determine the effects of mHealth applications and wearable devices on the outcome of patients with breast cancer. We followed the PRISMA guideline for the selection, analysis, and reporting of relevant studies found in the databases of Medline, Scopus, Web of Science, and Cochrane Library. A total of 276 unique records were identified, and 20 studies met the inclusion criteria. Study quality was assessed with the Effective Public Health Practice Project (EPHPP) Quality Assessment Tool for Quantitative Studies. While many of the studies used standardized questionnaires as patient-reported outcome measures, there was minimal use of objective measurements, such as activity sensors. Adoption, drop-out rates, and usage behavior of users of the mobile health intervention were often not reported. Future work should clearly define the focus and desired outcome of mHealth interventions and select outcome measures accordingly. Greater transparency facilitates the interpretation of results and conclusions about the real-world evidence of mobile health in breast cancer care.
乳腺癌正在影响全球数百万人。如果处理不当，不同癌症治疗方式的副作用可能会对患者的生活质量产生负面影响，并导致治疗中断。近年来，移动医疗（mHealth）干预措施为支持乳腺癌护理提供了有前途的机会。许多研究实施了移动医疗干预措施，旨在通过促进体育锻炼或提供教育内容来支持乳腺癌患者。然而，目前的文献表明，实际效益的真实世界证据仍不清楚。在本次系统评价中，我们重点分析了最近研究中使用的方法，以确定 mHealth 应用程序和可穿戴设备对乳腺癌患者结局的影响。我们遵循 PRISMA 指南，在 Medline、Scopus、Web of Science 和 Cochrane Library 的数据库中选择、分析和报告相关研究。共确定了 276 个独特的记录，其中 20 项研究符合纳入标准。研究质量使用有效公共卫生实践项目（EPHPP）定量研究质量评估工具进行评估。虽然许多研究使用标准化问卷作为患者报告的结果测量，但很少使用活动传感器等客观测量。移动医疗干预措施的使用者的采用率、脱落率和使用行为往往没有报告。未来的工作应该明确界定 mHealth 干预措施的重点和预期结果，并相应选择结果衡量标准。更大的透明度有助于解释关于移动医疗在乳腺癌护理中的真实世界证据的结果和结论。
