KNCV结核病基金会Salome Charalambous小组近日取得一项新成果。经过不懈努力，他们报道了数字依从技术对药物敏感结核病患者治疗结果的影响。相关论文发表在2025年3月11日出版的《柳叶刀》杂志上。

背景:数字依从性技术对结核病治疗结果的影响仍知之甚少。该课题组人员调查了智能药箱和药物标签是否可以减少结核病患者的不良治疗结果。

方法:该课题组在菲律宾、南非、坦桑尼亚和乌克兰进行了独立、实用的集群随机试验。110组随机分配（1:1）到标准护理组和干预组，进一步随机分配(1:1）到智能药盒或药物标签。研究小组招募了接受药物敏感结核病治疗的成年患者。药盒会发出视听提醒服药，当药盒被打开时，会向依从平台发送信号。标签组的人收到的药物带有标签，标签上有一个代码，他们在服用剂量时发送代码；否则，将发送提醒。主要终点是综合治疗终点差，定义为有记录的治疗失败、失去随访（治疗中断连续≥2个月）、治疗开始后超过28天转为耐多药方案或死亡。试验已完成并在ISRCTN注册，编号17706019。

发现:2021年6月21日至2022年7月8日，我们在四项试验的220个集群中招募了25606名个体（12626名接受标准护理，12980名接受干预），其中23483人（91.7%；11313名接受标准治疗，12170名接受干预治疗）被纳入意向治疗人群。23483人中8208人（35.0%）为女性。对标准护理组11313人中的9717人（85.9%）和干预组12170人中的10540人（86.6%）进行了主要结局分析。所有国家的主要结局风险在干预组之间没有差异（菲律宾调整后的比值比为1.13，95%置信区间为0.72-1.78，p=0.59；坦桑尼亚调整为1.49，0.99-2.23；p=0.056；南非调整为1.19，0.88-1.60；p=0.25；乌克兰调整后的风险比为1.15，95%CI为0.83-1.59；p=0.38）。据报道，由于无意中披露了碉堡手臂的治疗状态，导致参与者退出，造成了两起社会伤害事件。

研究结果表明，在调查的四个国家中，数字依从性技术并没有减少不良的治疗结果。数字依从性技术的使用应基于对经济评估、患者和利益相关者偏好以及对计划性治疗结果以外的其他重要患者结果的影响等额外数据的仔细审查。

附：英文原文

Title: Effect of digital adherence technologies on treatment outcomes in people with drug-susceptible tuberculosis: four pragmatic, cluster-randomised trials

Author: Degu Jerene, Kristian van Kalmthout, Jens Levy, Jason Alacapa, Natasha Deyanova, Tanyaradzwa Dube, Andrew Mganga, Bianca Tasca, Alexsey Bogdanov, Egwuma Efo, Katya Gamazina, Anna Marie Celina Garfin, Volodymyr Kochanov, Adrian Leung, Norma Madden, Noriah Maraba, Christopher Finn McQuaid, Liberate Mleoh, Baraka Onjare, Rachel Powers, Yana Terleiva, Job van Rest, Agnes Gebhard, Katherine Fielding, Salome Charalambous

Issue&Volume: 2025-03-11

Abstract: Background

The impact of digital adherence technologies on tuberculosis treatment outcomes remains poorly understood. We investigated whether smart pillboxes and medication labels can reduce poor treatment outcomes in patients with tuberculosis.

Methods

We did independent pragmatic, cluster-randomised trials in the Philippines, South Africa, Tanzania, and Ukraine. 110 clusters were randomly assigned (1:1) to standard of care versus intervention arms, which were further randomly assigned (1:1; except in Ukraine) to a smart pillbox or medication labels. We enrolled adult patients receiving treatment for drug-susceptible tuberculosis. The pillbox gave an audio-visual reminder to take medication, and when the box was opened, a signal was transmitted to the adherence platform. Those in the labels arm received medications with label attached, showing a code, which they messaged when a dose was taken; otherwise, a reminder was sent. The primary outcome was a composite poor end of treatment outcome, defined as having documented treatment failure, loss to follow-up (treatment interruption for ≥2 consecutive months), switched to a multidrug-resistant regimen more than 28 days after treatment start, or death. The trials are complete and registered with ISRCTN, 17706019.

Findings

Between June 21, 2021, and July 8, 2022, we enrolled 25606 individuals (12626 on standard of care and 12980 on intervention) across 220 clusters in the four trials, of whom 23483 (91·7%; 11313 on standard of care and 12170 on intervention) were included in the intention-to-treat population. 8208 (35·0%) of 23483 individuals were female. 9717 (85·9%) of 11313 individuals in the standard of care arm and 10540 (86·6%) of 12170 individuals in the intervention arm were analysed for the primary outcome. The risk of the primary outcome did not differ by intervention arm for all countries (Philippines adjusted odds ratio 1·13, 95% CI 0·72–1·78, p=0·59; Tanzania 1·49, 0·99–2·23; p=0·056; South Africa 1·19, 0·88–1·60; p=0·25; Ukraine adjusted risk ratio 1·15, 95% CI 0·83–1·59; p=0·38). Two incidents of social harm were reported due to inadvertent disclosure of treatment status in the pillbox arm, resulting in withdrawal of the participants.

Interpretation

Digital adherence technologies did not reduce poor treatment outcomes in the four countries investigated. The use of digital adherence technologies should be based on careful review of additional data on economic evaluation, patient and stakeholder preferences, and the effect on other important patient outcomes beyond programmatic treatment outcomes.

DOI: 10.1016/S0140-6736(24)02847-2

Source: https://www.thelancet.com/journals/lancet/article/PIIS0140-6736(24)02847-2/abstract