Evidence map›Paper›PMID 30496464›Full record

ArticleClinical infectious diseases : an official publication of the Infectious Diseases Society of America2018

Transformation Morphisms and Time-to-Extinction Analysis That Map Therapy Duration From Preclinical Models to Patients With Tuberculosis: Translating From Apples to Oranges.

Gesham Magombedze, Jotam G Pasipanodya, Shashikant Srivastava, Devyani Deshpande, Marianne E Visser, Emmanuel Chigutsa, Helen McIlleron, Tawanda Gumbo

Abstract read
In one paragraph

Article in Clinical infectious diseases : an official publication of the Infectious Diseases Society of America, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed, 2 pooled it
–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

28 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
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  4. Novel regimens for treatment ofbioRxiv : the preprint server for biology · 2026
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  8. Examining effective monotherapy hypothesis for TB therapy failure and resistance emergence.The international journal of tuberculosis and lung disease : the official journal of the International Union against Tuberculosis and Lung Disease · 2024
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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

8 authors.

Gesham MagombedzeCenter for Infectious Diseases Research and Experimental Therapeutics, Baylor Research Institute, Dallas, Texas.
Jotam G PasipanodyaCenter for Infectious Diseases Research and Experimental Therapeutics, Baylor Research Institute, Dallas, Texas.
Shashikant SrivastavaCenter for Infectious Diseases Research and Experimental Therapeutics, Baylor Research Institute, Dallas, Texas.
Devyani DeshpandeCenter for Infectious Diseases Research and Experimental Therapeutics, Baylor Research Institute, Dallas, Texas.
Marianne E VisserDivision of Pharmacology, Department of Medicine, University of Cape Town, Observatory, South Africa.
Emmanuel ChigutsaDivision of Pharmacology, Department of Medicine, University of Cape Town, Observatory, South Africa.
Helen McIlleronDivision of Pharmacology, Department of Medicine, University of Cape Town, Observatory, South Africa.
Tawanda GumboCenter for Infectious Diseases Research and Experimental Therapeutics, Baylor Research Institute, Dallas, Texas.

Funding

Efflux pump inhibitors to reduce duration of antituberculosis therapyDP2OD001886 · OD · UT SOUTHWESTERN MEDICAL CENTER · PI GUMBO, TAWANDA · 2007 to 2007
$2.4M
PK-PD of combination antituberculosis therapy for suppression of drug-resistanceR01AI079497 · NIAID · UT SOUTHWESTERN MEDICAL CENTER · PI GUMBO, TAWANDA · 2008 to 2011
$2.3M
Short course therapy for MDR-TB based on PK/PD answers for biological variabilityR56AI111985 · NIAID · UT SOUTHWESTERN MEDICAL CENTER · PI GUMBO, TAWANDA · 2014 to 2014
$900k
NIAID NIH HHS R01 AI079497NIAID NIH HHS R56 AI111985NIH HHS DP2 OD001886
6 · The paper itself

Abstract

Background: A major challenge in medicine is translation of preclinical model findings to humans, especially therapy duration. One major example is recent shorter-duration therapy regimen failures in tuberculosis. Methods: We used set theory mapping to develop a computational/modeling framework to map the time it takes to extinguish the Mycobacterium tuberculosis population on chemotherapy from multiple hollow fiber system model of tuberculosis (HFS-TB) experiments to that observed in patients. The predictive accuracy of the derived translation transformations was then tested using data from 108 HFS-TB Rapid Evaluation of Moxifloxacin in Tuberculosis (REMoxTB) units, including 756 colony-forming units (CFU)/mL. Derived transformations, and Latin hypercube sampling-guided simulations were used to predict cure and relapse after 4 and 6 months of therapy. Outcomes were compared to observations, in 1932 patients in the REMoxTB clinical trial. Results: HFS-TB serial bacillary burden and serial sputum data in the derivation dataset formed a structure-preserving map. Bactericidal effect was mapped with a single step transformation, while the sterilizing effect was mapped with a 3-step transformation function. Using the HFS-TB REMoxTB data, we accurately predicted the proportion of patients cured in the 4-month REMoxTB clinical trial. Model-predicted vs clinical trial observations were (i) the ethambutol arm (77.0% [95% confidence interval {CI}, 74.4%-79.6%] vs 77.7% [95% CI, 74.3%-80.9%]) and (ii) the isoniazid arm (76.4% [95% CI, 73.9%-79.0%] vs 79.5% [95% CI, 76.1%-82.5%]). Conclusions: We developed a method to translate duration of therapy outcomes from preclinical models to tuberculosis patients.

Indexed as

Antitubercular AgentsClinical Trials as TopicDrug DiscoveryDrug Evaluation, PreclinicalEthambutolHumansIsoniazidModels, BiologicalMoxifloxacinMycobacterium tuberculosisRecurrenceSputumTuberculosisAntitubercular AgentsEthambutolIsoniazidMoxifloxacin

Identifiers

PMID30496464
PMCPMC6260172

What OpenQuestion holds

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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.