Evidence map›Paper›PMID 36918242›Full record

ArticleBMJ open2023

Effectiveness of digital adherence technologies in improving tuberculosis treatment outcomes in four countries: a pragmatic cluster randomised trial protocol.

Degu Jerene, Jens Levy, Kristian van Kalmthout, Job van Rest, Christopher Finn McQuaid, Matthew Quaife, Salome Charalambous, Katya Gamazina, A M Celina Garfin, Liberate Mleoh and 4 more

Abstract readClinical Trial Protocol
In one paragraph

Article in BMJ open, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

17 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors.

Degu JereneDivision of Tuberculosis Elimination and Health Systems Strengthening, KNCV Tuberculosis Foundation, The Hague, Netherlands degujerene@gmail.com.ORCID 0000-0001-7853-4211
Jens LevyDivision of Tuberculosis Elimination and Health Systems Strengthening, KNCV Tuberculosis Foundation, The Hague, Netherlands.
Kristian van KalmthoutDivision of Tuberculosis Elimination and Health Systems Strengthening, KNCV Tuberculosis Foundation, The Hague, Netherlands.
Job van RestDivision of Tuberculosis Elimination and Health Systems Strengthening, KNCV Tuberculosis Foundation, The Hague, Netherlands.
Christopher Finn McQuaidTB Centre and Department of Infectious Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, UK.ORCID 0000-0001-6199-0931
Matthew QuaifeTB Centre and Department of Infectious Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, UK.ORCID 0000-0001-9291-1511
Salome CharalambousThe Aurum Institute, Johannesburg, South Africa.
Katya GamazinaProgram for Appropriate Technology in Health, Kyiv, Ukraine.
A M Celina GarfinDepartment of Health, Infectious Diseases Prevention and Control Division, Disease Prevention and Control Bureau, Manila, the Philippines.
Liberate MleohDepartment of Preventive Services, National Tuberculosis and Leprosy Programme, Dodoma, United Republic of Tanzania.
Yana TerleievaDepartment of Coordination of TB Treatment Programs, Kyiv, Ukraine.
Alexsey BogdanovProgram for Appropriate Technology in Health, Kyiv, Ukraine.
Noriah MarabaThe Aurum Institute, Johannesburg, South Africa.ORCID 0000-0002-3974-5961
Katherine FieldingTB Centre and Department of Infectious Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, UK.ORCID 0000-0002-6524-3754

Funding

Medical Research Council MR/R010161/1
6 · The paper itself

Abstract

introductionSuccessful treatment of tuberculosis depends to a large extent on good adherence to treatment regimens, which relies on directly observed treatment (DOT). This in turn requires frequent visits to health facilities. High costs to patients, stigma and burden to the health system challenged the DOT approach. Digital adherence technologies (DATs) have emerged as possibly more feasible alternatives to DOT but there is conflicting evidence on their effectiveness and feasibility. Our primary objective is to evaluate whether the implementation of DATs with daily monitoring and a differentiated response to patient adherence would reduce poor treatment outcomes compared with the standard of care (SOC). Our secondary objectives include: to evaluate the proportion of patients lost to follow-up; to compare effectiveness by DAT type; to evaluate the feasibility and acceptability of DATs; to describe factors affecting the longitudinal engagement of patients with the intervention and to use a simple model to estimate the epidemiological impact and cost-effectiveness of the intervention from a health system perspective. METHODS AND ANALYSIS: This is a pragmatic two-arm cluster-randomised trial in the Philippines, South Africa, Tanzania and Ukraine, with health facilities as the unit of randomisation. Facilities will first be randomised to either the DAT or SOC arm, and then the DAT arm will be further randomised into medication sleeve/labels or smart pill box in a 1:1:2 ratio for the smart pill box, medication sleeve/label or the SOC respectively. We will use data from the digital adherence platform and routine health facility records for analysis. In the main analysis, we will employ an intention-to-treat approach to evaluate treatment outcomes. ETHICS AND DISSEMINATION: The study has been approved by the WHO Research Ethics Review Committee (0003296), and by country-specific committees. The results will be shared at national and international meetings and will be published in peer-reviewed journals. TRIAL REGISTRATION NUMBER: ISRCTN17706019.

Indexed as

TuberculosisHumansPatient CompliancePragmatic Clinical Trials as TopicSouth AfricaTanzaniaTreatment OutcomeEpidemiologyPublic healthTropical medicineTuberculosis

Identifiers

PMID36918242
PMCPMC10016242

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.