Discussion
death, tuberculosis, Tuberculosis
RECURRENCES, RECURRENCE, DRUG-SENSITIVE TUBERCULOSIS, EVENT, TUBERCULOSIS, TUBERCULOSIS, SECONDARY, EVENTS
In this large, cluster-randomised trial of 2686 patients with drug-sensitive tuberculosis from four prefectures in China, a digital adherence technology intervention had no effect on the risk of the primary composite outcome, and secondary outcomes of death, treatment failure, or loss to follow-up during treatment. Tuberculosis recurrence was uncommon, with a 12-month risk of 1·9% after the end of treatment among patients who had a successful treatment outcome. Non-adherence was reduced by 57–64% in the intervention group compared with the control group, depending on the metric used, which was a greater reduction than in our previous study.The intervention had no effect on loss to follow-up, which accounted for most of the primary composite outcome events (289 [67%] of 433 events); this might have been because there was a paucity of timely adherence data, and because of failure to change management following identification of non-adherence at monthly reviews. Rather than monthly adherence assessment, a more frequent review of adherence data by health-care workers and initiation of intensive management to assist patients who have issues with adherence are likely to be needed to reduce loss to follow-up. The Keheala intervention, evaluated in a study in Kenya, assessed weekly motivational messages, daily text message reminders, an unstructured supplementary service data platform for patients to confirm daily adherence with follow-up by the research team for patients who had not confirmed adherence, and clinic notification of patients with no confirmation for more than 2 days. The intervention was associated with a 68% (95% CI 50–79) reduced risk of poor treatment outcome (composite outcome of on-treatment death, treatment failure, or loss to follow-up), entirely through reducing loss to follow-up.In our trial, despite non-adherence being higher in the control group than in the intervention group, there was no apparent intervention effect on treatment outcomes or tuberculosis recurrence, which contradicts the findings from some other studies. An analysis of the fluoroquinolone treatment trials, albeit a non-randomised comparison, showed a strong relationship between lower adherence and increased risk of unfavourable tuberculosis treatment outcomes.Alternatively, we might have underestimated tuberculosis recurrence, although underestimation was unlikely to be differential by study group. We followed up patients for 12 months after the end of treatment, which would be likely to capture the vast majority of recurrences.This trial did show a reduction in non-adherence, measured by box-opening, in the intervention group compared with the control group, similar to in our previous study,Other digital adherence technologies have been assessed in upper-middle-income and high-income settings, including video-supported therapy, to improve treatment outcomes. These studies have shown similar or increased rates of favourable treatment outcomes with video supported therapy compared with control groups (often directly observed therapy); although, individually, all 95% CIs for the ratio effect estimate overlap 1, so are not significant.This trial has many strengths, including a large sample size and an intervention that was implemented by the national tuberculosis programme rather than a research team in parallel, it was conducted across varied settings, and follow-up continued for 12 months after the end of treatment. The study does, however, have several limitations: more intensive management activities, such as home visits to patients identified as having adherence problems, did not always happen as planned; after randomisation, two intervention clusters were combined, although this had minimal impact on power; solid culture rather than the more sensitive liquid culture was used to measure recurrence; and adherence outcomes were defined using a box-opening as a proxy for doses taken.In conclusion, the digital adherence technology intervention, involving a daily reminder medication monitor, monthly review of adherence data, and differentiated care for patients with adherence issues, was inadequate to influence unfavourable outcomes, which included loss to follow-up during treatment, tuberculosis recurrence, death, and treatment failure. Poor implementation of targeted adherence support might have contributed to no effect of the intervention on outcomes. Other trials have shown that digital adherence technologies (SMS-based and those based on medication event reminder monitors), implemented in real-time, can improve successful treatment outcomes. It is important, though, to understand the cost of delivering such interventions and also how these can be implemented in routine practice. Programmatically, treatment adherence might be substandard and clinicians do not have adequate methods to measure dose-taking. WHO uses treatment success (cured or completed treatment) as an indicator for performance of tuberculosis programmes, although it is a poor indicator of care as treatment completion is often not based on robust measures of adherence. For evaluating digital adherence technologies, rather than relying solely on outcomes at the end of treatment, a combined endpoint of adherence and treatment outcome could be used, with adherence measured in all trial participants using digital technologies with excellent accuracy characteristics. It is important that future trials do measure end of treatment outcomes, ideally incorporating quality treatment completion and possibly recurrence, if measured robustly, to generate strong evidence to influence policy.