McGill International Tuberculosis Centre, Research Institute of the McGill University Health Centre, Montreal, Quebec, Canada.
TB Centre, London School of Hygiene and Tropical Medicine, London, UK.
BMJ Glob Health. 2024 Jul 16;9(7):e015633. doi: 10.1136/bmjgh-2024-015633.
Digital adherence technologies (DATs), such as phone-based technologies and digital pillboxes, can provide more person-centric approaches to support tuberculosis (TB) treatment. However, there are varying estimates of their performance for measuring medication adherence.
We conducted a systematic review (PROSPERO-CRD42022313526), which identified relevant published literature and preprints from January 2000 to April 2023 in five databases. Studies reporting quantitative data on the performance of DATs for measuring TB medication adherence against a reference standard, with at least 20 participants, were included. Study characteristics and performance outcomes (eg, sensitivity, specificity and predictive values) were extracted. Sensitivity was the proportion correctly classified as adherent by the DAT, among persons deemed adherent by a reference standard. Specificity was the proportion correctly classified as non-adherent by the DAT, among those deemed non-adherent by a reference standard.
Of 5692 studies identified by our systematic search, 13 met inclusion criteria. These studies investigated medication sleeves with phone calls (branded as '99DOTS'; N=4), digital pillboxes N=5), ingestible sensors (N=2), artificial intelligence-based video-observed therapy (N=1) and multifunctional mobile applications (N=1). All but one involved persons with TB disease. For medication sleeves with phone calls, compared with urine testing, reported sensitivity and specificity were 70%-94% and 0%-61%, respectively. For digital pillboxes, compared with pill counts, reported sensitivity and specificity were 25%-99% and 69%-100%, respectively. For ingestible sensors, the sensitivity of dose detection was ≥95% compared with direct observation. Participant selection was the most frequent potential source of bias.
The limited number of studies available suggests suboptimal and variable performance of DATs for dose monitoring, with significant evidence gaps, notably in real-world programmatic settings. Future research should aim to improve understanding of the relationships of specific technologies, settings and user engagement with DAT performance and should measure and report performance in a more standardised manner.
数字依从技术(DATs),如基于电话的技术和数字药盒,可以提供更以患者为中心的方法来支持结核病(TB)治疗。然而,它们在衡量药物依从性方面的性能存在不同的估计。
我们进行了系统评价(PROSPERO-CRD42022313526),该评价从 2000 年 1 月至 2023 年 4 月在五个数据库中确定了相关的已发表文献和预印本。纳入了报告关于 DAT 测量 TB 药物依从性对参考标准的性能的定量数据的研究,至少有 20 名参与者。提取了研究特征和性能结果(例如,敏感性、特异性和预测值)。敏感性是 DAT 正确分类为参考标准中被认为是依从者的比例,在参考标准中被认为是依从者的人中。特异性是 DAT 正确分类为参考标准中被认为是非依从者的比例,在参考标准中被认为是非依从者的人中。
通过我们的系统搜索,确定了 5692 项研究,其中 13 项符合纳入标准。这些研究调查了带有电话的药物袖套(品牌为“99DOTS”;N=4)、数字药盒(N=5)、可摄入传感器(N=2)、基于人工智能的视频观察治疗(N=1)和多功能移动应用程序(N=1)。除了一项研究外,所有研究都涉及结核病患者。对于带有电话的药物袖套,与尿液检测相比,报告的敏感性和特异性分别为 70%-94%和 0%-61%。对于数字药盒,与药丸计数相比,报告的敏感性和特异性分别为 25%-99%和 69%-100%。对于可摄入传感器,剂量检测的灵敏度≥95%与直接观察相比。参与者选择是最常见的潜在偏倚来源。
现有研究数量有限,表明 DATs 对剂量监测的性能不理想且存在差异,特别是在实际方案环境中,证据差距明显。未来的研究应旨在更好地了解特定技术、设置和用户参与与 DAT 性能的关系,并以更标准化的方式测量和报告性能。