Abstract
Adherence to treatment for tuberculosis (TB) has been a concern for many decades, resulting in the World Health Organization's recommendation of the direct observation of treatment in the 1990s. Recent advances in digital adherence technologies (DATs) have renewed discussion on how to best address nonadherence, as well as offering important information on dose-by-dose adherence patterns and their variability between countries and settings. Previous studies have largely focussed on percentage thresholds to delineate sufficient adherence, but this is misleading and limited, given the complex and dynamic nature of adherence over the treatment course. Instead, we apply a standardised taxonomy – as adopted by the international adherence community – to dose-by-dose medication-taking data, which divides missed doses into 1) late/noninitiation (starting treatment later than expected/not starting), 2) discontinuation (ending treatment early), and 3) suboptimal implementation (intermittent missed doses). Using this taxonomy, we can consider the implications of different forms of nonadherence for intervention and regimen design. For example, can treatment regimens be adapted to increase the “forgiveness” of common patterns of suboptimal implementation to protect against treatment failure and the development of drug resistance? Is it reasonable to treat all missed doses of treatment as equally problematic and equally common when deploying DATs? Can DAT data be used to indicate the patients that need enhanced levels of support during their treatment course? Critically, we pinpoint key areas where knowledge regarding treatment adherence is sparse and impeding scientific progress.
Abstract
Digital adherence technologies (DATs) provide a wealth of information on dose-by-dose anti-TB medication-taking. Studies of DAT data should place nonadherence in standardised taxonomic frameworks in order to best inform intervention and regimen design. https://bit.ly/3jq1D8a
Footnotes
Author contributions: All authors contributed to the conception of the work. M. Flook, H.R. Stagg, A. Martinecz and P. Abel zur Wiesch contributed to the acquisition, analysis and interpretation of data/literature for the work. All authors drafted the work/revised it critically for important intellectual content. All authors give final approval of the manuscript version to be published and agree to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.
Conflict of interest: H.R. Stagg reports that she is the Chief Investigator on, and supported by, Medical Research Council MR/R008345/1; and a co-applicant on NIHR grant 16/88/06 (the IMPACT study), which contains a small salary contribution. She also reports travel and subsistence support from events organised by the Korean CDC and the Latvian Society Against Tuberculosis, some of the sponsorship for which was obtained from Otsuka and Johnson and Johnson.
Conflict of interest: M. Flook reports grants from the Medical Research Council, UK, during the conduct of the study.
Conflict of interest: A. Martinecz has nothing to disclose.
Conflict of interest: K. Kielmann has nothing to disclose.
Conflict of interest: P. Abel zur Wiesch has nothing to disclose.
Conflict of interest: A.S. Karat reports grants awarded to the London School of Hygiene & Tropical Medicine (LSHTM) from the World Health Organization and the Medical Research Council, UK; grants awarded to University College London (subcontract to Queen Mary University) from the National Institute of Health Research, UK; grants awarded to the LSHTM from the Economic and Social Research Council, UK, and The Bloomsbury SET (Research England); grants awarded to Imperial College London from The Colt Foundation, UK; grants awarded to the LSHTM from Viiv Healthcare, USA; consultancy fees from The Aurum Institute, South Africa, Edanz Group, Japan, and Pastest, UK; an external marker fee from The University of Cape Town, South Africa; travel and subsistence support from Kyoto University, Japan, Vital Strategies, Singapore, and Bloomberg Philanthropies, USA; and costs of open access publishing from the Bill & Melinda Gates Foundation, USA, all outside the submitted work.
Conflict of interest: M.C.I. Lipman reports grants from National Institute for Health Research, UK, during the conduct of the study.
Conflict of interest: D.J. Sloan has nothing to disclose.
Conflict of interest: E.F. Walker has nothing to disclose.
Conflict of interest: K.L. Fielding has nothing to disclose.
Support statement: H.R. Stagg and M. Flook are supported by the Medical Research Council (grant number MR/R008345/1). H.R. Stagg, A.S. Karat and M.C.I. Lipman are supported by the National Institute for Health Research (NIHR) Health Technology Assessment Programme, UK (grant number 16/88/06). The views expressed are those of the author(s) and not necessarily those of the UK's National Health Service, the NIHR or the Department of Health and Social Care. The funders did not play a role in the writing of the manuscript or the decision to submit for publication. None of the authors have been paid to write this article by a pharmaceutical company or other agency. The corresponding author had full access to all the data in the study and has final responsibility for the decision to submit for publication. Funding information for this article has been deposited with the Crossref Funder Registry.
- Received May 26, 2020.
- Accepted July 16, 2020.
- Copyright ©ERS 2020
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