Evidence map›Paper›PMID 28137496›Full record

ArticleRespiratory medicine2017

Parametric response mapping on chest computed tomography associates with clinical and functional parameters in chronic obstructive pulmonary disease.

Esther Pompe, Craig J Galbán, Brian D Ross, Leo Koenderman, Nick Ht Ten Hacken, Dirkje S Postma, Maarten van den Berge, Pim A de Jong, Jan-Willem J Lammers, Firdaus Aa Mohamed Hoesein

Abstract read
In one paragraph

Article in Respiratory medicine, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 55 papers.

0numbers the graph read from it
0cells of the map it votes in
55citing 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

55 citing papers in PubMed.

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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

10 authors.

Esther PompeDepartment of Respiratory Medicine, University Medical Center Utrecht, Utrecht, The Netherlands. Electronic address: e.pompe@umcutrecht.nl.
Craig J GalbánDepartment of Radiology, University of Michigan, Ann Arbor, MI, USA; Center for Molecular Imaging, University of Michigan, Ann Arbor, MI, USA.
Brian D RossDepartment of Radiology, University of Michigan, Ann Arbor, MI, USA; Center for Molecular Imaging, University of Michigan, Ann Arbor, MI, USA.
Leo KoendermanDepartment of Respiratory Medicine, University Medical Center Utrecht, Utrecht, The Netherlands.
Nick Ht Ten HackenUniversity of Groningen, University Medical Center Groningen, Department of Pulmonary Disease, Groningen, The Netherlands; University of Groningen, University Medical Center Groningen, Groningen Research Institute for Asthma and COPD (GRIAC), Groningen, The Netherlands.
Dirkje S PostmaUniversity of Groningen, University Medical Center Groningen, Department of Pulmonary Disease, Groningen, The Netherlands; University of Groningen, University Medical Center Groningen, Groningen Research Institute for Asthma and COPD (GRIAC), Groningen, The Netherlands.
Maarten van den BergeUniversity of Groningen, University Medical Center Groningen, Department of Pulmonary Disease, Groningen, The Netherlands; University of Groningen, University Medical Center Groningen, Groningen Research Institute for Asthma and COPD (GRIAC), Groningen, The Netherlands.
Pim A de JongDepartment of Radiology, University Medical Center Utrecht, Utrecht, The Netherlands.
Jan-Willem J LammersDepartment of Respiratory Medicine, University Medical Center Utrecht, Utrecht, The Netherlands.
Firdaus Aa Mohamed HoeseinDepartment of Radiology, University Medical Center Utrecht, Utrecht, The Netherlands.

Funding

QUANTITATION OF HUMAN BRAIN TUMOR THERAPY RESPONSE BY MRP01CA085878 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI ROSS, BRIAN D. · 2001 to 2017
$31.9M
Imaging of Hematologic and Oncologic DisordersR35CA197701 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI ROSS, BRIAN D. · 2016 to 2022
$5.9M
NCI NIH HHS P01 CA085878NCI NIH HHS R35 CA197701
6 · The paper itself

Abstract

backgroundIn the search for specific phenotypes of chronic obstructive pulmonary disease (COPD) computed tomography (CT) derived Parametric Response Mapping (PRM) has been introduced. This study evaluates the association between PRM and currently available biomarkers of disease severity in COPD.

methodsSmokers with and without COPD were characterized based on questionnaires, pulmonary function tests, body plethysmography, and low-dose chest CT scanning. PRM was used to calculate the amount of emphysema (PRM

results166 participants were included with a mean ± SD age of 50.5 ± 17.7 years. Both PRM

conclusionsPRM strongly associates with the presence and severity of COPD. PRM therefore appears to be a valuable tool in differentiating COPD phenotypes.

Indexed as

AdolescentAdultAgedFemaleForced Expiratory VolumeHumansImage Interpretation, Computer-AssistedMaleMiddle AgedPhenotypePulmonary Disease, Chronic ObstructivePulmonary EmphysemaRespiratory Function TestsRetrospective StudiesSeverity of Illness IndexSmokingComputed tomographyCopdEmphysemaParametric response mappingPhenotypesSmall airway disease

Identifiers

PMID28137496
PMCPMC5555031

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Registered trials

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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.