Evidence map›Paper›PMID 39653087›Full record

ArticleInternational journal of antimicrobial agents2025

Analysis of time-to-positivity data in tuberculosis treatment studies: Identifying a new limit of quantification.

Suzanne M Dufault, Geraint R Davies, Elin M Svensson, Derek J Sloan, Andrew D McCallum, Anu Patel, Pieter Van Brantegem, Paolo Denti, Patrick P J Phillips

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in International journal of antimicrobial agents, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Trial
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

9 authors.

Suzanne M DufaultDivision of Biostatistics, University of California, San Francisco, San Francisco, California, USA; UCSF Center for Tuberculosis, University of California, San Francisco, San Francisco, California, USA. Electronic address: suzanne.dufault@ucsf.edu.
Geraint R DaviesInstitute of Infection and Global Health, University of Liverpool, Liverpool, UK.
Elin M SvenssonDepartment of Pharmacy, Radboud University Medical Center, Nijmegen, the Netherlands; Department of Pharmacy, Uppsala University, Uppsala, Sweden.
Derek J SloanSchool of Medicine, University of St Andrews, St Andrews, UK.
Andrew D McCallumDepartment of Infectious Diseases, Oxford University Hospitals NHS Foundation Trust, Oxford, UK.
Anu PatelDivision of Pulmonary and Critical Care Medicine, University of California, San Francisco, San Francisco, California, USA.
Pieter Van BrantegemDepartment of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, California, USA.
Paolo DentiDivision of Clinical Pharmacology, Department of Medicine, University of Cape Town, South Africa.
Patrick P J PhillipsUCSF Center for Tuberculosis, University of California, San Francisco, San Francisco, California, USA; Division of Pulmonary and Critical Care Medicine, University of California, San Francisco, San Francisco, California, USA.

Funding

Tuberculosis Research and Mentorship Program (TB RAMP II)R25AI147375 · NIAID · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI Elizabeth Fair, PAYAM NAHID · 2020 to 2026
$2.8M
Pharmaceutical Sciences and PharmacogenomicsT32GM142516 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI Su Guo · 2022 to 2026
$2.4M
NIAID NIH HHS R25 AI147375NIGMS NIH HHS T32 GM142516
6 · The paper itself

Abstract

backgroundThe BACTEC Mycobacteria Growth Indicator Tube (MGIT) machine is the standard globally for detecting viable mycobacteria in patients' sputum. Samples are observed for no longer than 42 days, at which point the sample is declared 'negative' for tuberculosis (TB). This time to detection of bacterial growth, referred to as time-to-positivity (TTP), is increasingly of interest, not solely as a diagnostic tool but also as a continuous biomarker wherein change in TTP can be used for comparing the bactericidal activity of different TB treatments. However, as a continuous measure, there are oddities in the distribution of TTP values observed, particularly at higher values.

methodsWe explored whether there is evidence to suggest setting an upper limit of quantification for modeling purposes (ULOQ

resultsAcross all trials, less than 7.1% of weekly samples returned TTP measurements between 25 and 42 days. Further, the relative absolute prediction error (%) was highest in this range. When modelling with ULOQ

conclusionsAlthough TTP measurements between 25 days and the diagnostic LOD may be important for diagnostic purposes, TTP values in this range may not contribute meaningfully to its use as a quantitative measure, particularly when assessing treatment response, and may lead to underpowered clinical trials.

Indexed as

Antitubercular AgentsMycobacterium tuberculosisSputumTuberculosisHumansLimit of DetectionRandomized Controlled Trials as TopicTime FactorsAntitubercular AgentsBiomarkersClinical trialsEarly bactericidal activityGrowth indicator tube (MGIT)Limit of quantificationMycobacteriaTime-to-positivityTuberculosis

Identifiers

PMID39653087
PMCPMC12767140

What OpenQuestion holds

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LicenceCC BY
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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.