Evidence map›Paper›PMID 35559123›Full record

ArticleOpen forum infectious diseases2021

Measuring Tuberculosis Medication Adherence: A Comparison of Multiple Approaches in Relation to Urine Isoniazid Metabolite Testing Within a Cohort Study in India.

Ramnath Subbaraman, Beena E Thomas, J Vignesh Kumar, Maya Lubeck-Schricker, Amit Khandewale, William Thies, Misha Eliasziw, Kenneth H Mayer, Jessica E Haberer

Open access · goldAbstract read
In one paragraph

Article in Open forum infectious diseases, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 3 pooled it
3.3field-weighted citation impact, top 8% of its field
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

13 citing papers in PubMed, 3 syntheses or guidelines pooled it, 21 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Treatment Adherence With an Oral 9-Month Regimen for Rifampicin-Resistant Tuberculosis in South Africa.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2026
    Observational
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  12. Assessment of TB treatment adherence using computer-assisted self-interviewing.The international journal of tuberculosis and lung disease : the official journal of the International Union against Tuberculosis and Lung Disease · 2023
    Article
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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

9 authors at 5 institutions in 2 countries.

Ramnath SubbaramanDepartment of Public Health and Community Medicine and Center for Global Public Health, Tufts University School of Medicine, Boston, Massachusetts, USA.ORCID https://orcid.org/0000-0002-2063-943X
Beena E ThomasDepartment of Social and Behavioural Research, ICMR-National Institute for Research in Tuberculosis, Chennai, India.
J Vignesh KumarDepartment of Social and Behavioural Research, ICMR-National Institute for Research in Tuberculosis, Chennai, India.
Maya Lubeck-SchrickerDepartment of Public Health and Community Medicine and Center for Global Public Health, Tufts University School of Medicine, Boston, Massachusetts, USA.
Amit KhandewaleDepartment of Social and Behavioural Research, ICMR-National Institute for Research in Tuberculosis, Chennai, India.
William ThiesMicrosoft Research India, Bangalore, Karnataka, India.
Misha EliasziwDepartment of Public Health and Community Medicine and Center for Global Public Health, Tufts University School of Medicine, Boston, Massachusetts, USA.
Kenneth H MayerThe Fenway Institute, Fenway Health and Department of Medicine, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA.
Jessica E HabererCenter for Global Health, Massachusetts General Hospital and Department of Medicine, Harvard Medical School, Boston, Massachusetts, USA.
National Institute of Research in Tuberculosis · INTufts University · USBeth Israel Deaconess Medical Center · USHarvard University · USMicrosoft Research (India) · IN

Funding

The impact of HIV viral diversity and cellular immunity on HIV pathogenesisP30AI060354 · NIAID · HARVARD UNIVERSITY (MEDICAL SCHOOL) · PI ARTHUR Y KIM · 2004 to 2026
$94.4M
Harvard Clinical and Translational Science CenterKL2TR001100 · NCATS · HARVARD MEDICAL SCHOOL · PI NADLER, LEE MARSHALL · 2013 to 2017
$8.5M
Optimizing mHealth for adherence monitoring and interventionK24MH114732 · NIMH · MASSACHUSETTS GENERAL HOSPITAL · PI HABERER, JESSICA ELIZABETH · 2017 to 2021
$800k
Doris Duke Charitable Foundation 2018095NCATS NIH HHS KL2 TR001100NIAID NIH HHS P30 AI060354NIMH NIH HHS K24 MH114732
6 · The paper itself

Abstract

Background: Nonadherence to tuberculosis medications is associated with poor outcomes. However, measuring adherence in practice is challenging. In this study, we evaluated the accuracy of multiple tuberculosis adherence measures. Methods: We enrolled adult Indians with drug-susceptible tuberculosis who were monitored using 99DOTS, a cellphone-based technology. During an unannounced home visit with each participant, we assessed adherence using a pill estimate, 4-day dose recall, a last missed dose question, and urine isoniazid metabolite testing. We estimated the area under the receiver operating characteristic curve (AUC) for each alternate measure in comparison to urine testing. 99DOTS data were analyzed using patient-reported doses alone and patient- and provider-reported doses, the latter reflecting how 99DOTS is implemented in practice. We assessed each measure's operating characteristics, with particular interest in specificity-that is, the percentage of participants detected as being nonadherent by each alternate measure, among those who were nonadherent by urine testing. Results: Compared with urine testing, alternate measures had the following characteristics: 99DOTS patient-reported doses alone (area under the curve [AUC], 0.65; specificity, 70%; 95% CI, 58%-81%), 99DOTS patient- and provider-reported doses (AUC, 0.61; specificity, 33%; 95% CI, 22%-45%), pill estimate (AUC, 0.55; specificity, 21%; 95% CI, 12%-32%), 4-day recall (AUC, 0.60; specificity, 23%; 95% CI, 14%-34%), and last missed dose question (AUC, 0.65; specificity, 52%; 95% CI, 40%-63%). Conclusions: Alternate measures missed detecting at least 30% of people who were nonadherent by urine testing. The last missed dose question performed similarly to 99DOTS using patient-reported doses alone. Tuberculosis programs should evaluate the feasibility of integrating more accurate, objective measures, such as urine testing, into routine care.

Indexed as

drug metabolite testingIndiameasurementmedication adherencetuberculosis

Identifiers

PMID35559123
PMCPMC9088502
OpenAlexW3206651846

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.