Evidence map›Paper›PMID 30496460›Full record

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

d-Cycloserine Pharmacokinetics/Pharmacodynamics, Susceptibility, and Dosing Implications in Multidrug-resistant Tuberculosis: A Faustian Deal.

Devyani Deshpande, Jan-Willem C Alffenaar, Claudio U Köser, Keertan Dheda, Moti L Chapagain, Noviana Simbar, Thomas Schön, Marieke G G Sturkenboom, Helen McIlleron, Pooi S Lee and 9 more

Open access · bronzeAbstract readSystematic Review
In one paragraph

Synthesis 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 54 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
54citing papers in PubMed, 1 pooled it
5.3field-weighted citation impact, top 4% 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

54 citing papers in PubMed, 1 synthesis or guideline pooled it, 71 citations in OpenAlex.

  1. Treatment of Drug-Resistant Tuberculosis. An Official ATS/CDC/ERS/IDSA Clinical Practice Guideline.American journal of respiratory and critical care medicine · 2019
    Guideline
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  17. Therapeutic drug monitoring in tuberculosis.European journal of clinical pharmacology · 2024
    Review
  18. Role of therapeutic drug monitoring in the treatment of multi-drug resistant tuberculosis.Journal of clinical tuberculosis and other mycobacterial diseases · 2024
    Article
  19. 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

19 authors at 9 institutions in 9 countries.

Devyani DeshpandeCenter for Infectious Diseases Research and Experimental Therapeutics, Baylor Research Institute, Baylor University Medical Center, Dallas, Texas.
Jan-Willem C AlffenaarDepartment of Clinical Pharmacy and Pharmacology, University Medical Center Groningen, University of Groningen, The Netherlands.
Claudio U KöserDepartment of Genetics, University of Cambridge, United Kingdom.
Keertan DhedaLung Immunity Unit, Division of Pulmonology, Department of Medicine, University of Cape Town, Observatory, South Africa.
Moti L ChapagainCenter for Infectious Diseases Research and Experimental Therapeutics, Baylor Research Institute, Baylor University Medical Center, Dallas, Texas.
Noviana SimbarDepartment of Clinical Pharmacy and Pharmacology, University Medical Center Groningen, University of Groningen, The Netherlands.
Thomas SchönDepartment of Infectious Diseases and Clinical Microbiology, Kalmar County Hospital.
Marieke G G SturkenboomDepartment of Clinical Pharmacy and Pharmacology, University Medical Center Groningen, University of Groningen, The Netherlands.
Helen McIlleronDivision of Clinical Pharmacology, Department of Medicine, University of Cape Town, Observatory, South Africa.
Pooi S LeeCenter for Infectious Diseases Research and Experimental Therapeutics, Baylor Research Institute, Baylor University Medical Center, Dallas, Texas.
Thearith KoeuthCenter for Infectious Diseases Research and Experimental Therapeutics, Baylor Research Institute, Baylor University Medical Center, Dallas, Texas.
Stellah G MpagamaKibong'oto Infectious Diseases Hospital, Sanya Juu, Tanzania.
Sayera BanuInternational Centre for Diarrhoeal Disease Research, Bangladesh, Dhaka.
Suporn FoongladdaSiriraj Hospital, Mahidol University, Bangkok, Thailand.
Oleg OgarkovScientific Centre of the Family Health and Human Reproduction Problems, Irkutsk, Russian Federation.
Suporn PholwatDivision of Infectious Diseases and International Health, University of Virginia, Charlottesville.
Eric R HouptDivision of Infectious Diseases and International Health, University of Virginia, Charlottesville.
Scott K HeysellDivision of Infectious Diseases and International Health, University of Virginia, Charlottesville.
Tawanda GumboCenter for Infectious Diseases Research and Experimental Therapeutics, Baylor Research Institute, Baylor University Medical Center, Dallas, Texas.
Baylor University Medical Center · USUniversity Medical Center Groningen · NLUniversity of Virginia · USUniversity of Cape Town · ZAInternational Centre for Diarrhoeal Disease Research · BDLinköping University · SEScientific Center of Family Health Problems and Human Reproduction · RUSiriraj Hospital · THUniversity of Cambridge · GB

Funding

Diagnostics and Pharmacotherapy for Severe Forms of TBU01AI115594 · NIAID · UNIVERSITY OF VIRGINIA · PI HEYSELL, SCOTT K, HOUPT, ERIC R · 2015 to 2019
$3.0M
Pharmacometric optimization of second line drugs for MDR tuberculosis treatmentR01AI116155 · NIAID · UNIVERSITY OF CAPE TOWN · PI GUMBO, TAWANDA, MCILLERON, HELEN · 2015 to 2019
$1.7M
NIAID NIH HHS R01 AI116155NIAID NIH HHS U01 AI115594
6 · The paper itself

Abstract

Background: d-cycloserine is used to treat multidrug-resistant tuberculosis. Its efficacy, contribution in combination therapy, and best clinical dose are unclear, also data on the d-cycloserine minimum inhibitory concentration (MIC) distributions is scant. Methods: We performed a systematic search to identify pharmacokinetic and pharmacodynamic studies performed with d-cycloserine. We then performed a combined exposure-effect and dose fractionation study of d-cycloserine in the hollow fiber system model of tuberculosis (HFS-TB). In parallel, we identified d-cycloserine MICs in 415 clinical Mycobacterium tuberculosis (Mtb) isolates from patients. We utilized these results, including intracavitary concentrations, to identify the clinical dose that would be able to achieve or exceed target exposures in 10000 patients using Monte Carlo experiments (MCEs). Results: There were no published d-cycloserine pharmacokinetics/pharmacodynamics studies identified. Therefore, we performed new HFS-TB experiments. Cyloserine killed 6.3 log10 colony-forming units (CFU)/mL extracellular bacilli over 28 days. Efficacy was driven by the percentage of time concentration persisted above MIC (%TMIC), with 1.0 log10 CFU/mL kill achieved by %TMIC = 30% (target exposure). The tentative epidemiological cutoff value with the Sensititre MYCOTB assay was 64 mg/L. In MCEs, 750 mg twice daily achieved target exposure in lung cavities of 92% of patients whereas 500 mg twice daily achieved target exposure in 85% of patients with meningitis. The proposed MCE-derived clinical susceptibility breakpoint at the proposed doses was 64 mg/L. Conclusions: Cycloserine is cidal against Mtb. The susceptibility breakpoint is 64 mg/L. However, the doses likely to achieve the cidality in patients are high, and could be neurotoxic.

Indexed as

Antitubercular AgentsCycloserineHumansMicrobial Sensitivity TestsMonte Carlo MethodMycobacterium tuberculosisTuberculosis, Multidrug-ResistantAntitubercular AgentsCycloserine

Identifiers

PMID30496460
PMCPMC6260153
OpenAlexW2904314211

What OpenQuestion holds

Textmetadata
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.