Evidence map›Paper›PMID 26270185›Full record

ArticleChest2016

Transcriptional Profiling of Endobronchial Ultrasound-Guided Lymph Node Samples Aids Diagnosis of Mediastinal Lymphadenopathy.

Gillian S Tomlinson, Niclas Thomas, Benjamin M Chain, Katharine Best, Nandi Simpson, Georgia Hardavella, James Brown, Angshu Bhowmik, Neal Navani, Samuel M Janes and 2 more

Open access · hybridAbstract readComparative Study
PubMed Full text at PMC Publisher
In one paragraph

Article in Chest, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
1.2field-weighted citation impact, top 19% 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

9 citing papers in PubMed, 17 citations in OpenAlex.

  1. Review
  2. Review
  3. Article
  4. Review
  5. Article
  6. Observational
  7. Video-assisted thoracoscopic surgery for the treatment of mediastinal lymph node tuberculous abscesses.Journal of Huazhong University of Science and Technology. Medical sciences = Hua zhong ke ji da xue xue bao. Yi xue Ying De wen ban = Huazhong keji daxue xuebao. Yixue Yingdewen ban · 2017
    Article
  8. Review
  9. Article
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

12 authors at 2 institutions in 1 country.

Gillian S TomlinsonDepartment of Infection and Immunity, University College London, London, England. Electronic address: g.tomlinson@ucl.ac.uk.
Niclas ThomasDepartment of Infection and Immunity, University College London, London, England.
Benjamin M ChainDepartment of Infection and Immunity, University College London, London, England.
Katharine BestDepartment of Infection and Immunity, University College London, London, England.
Nandi SimpsonDepartment of Infection and Immunity, University College London, London, England.
Georgia HardavellaLungs for Living Research Centre, University College London, London, England.
James BrownLungs for Living Research Centre, University College London, London, England.
Angshu BhowmikDepartment of Respiratory Medicine, Homerton University Hospital, London, England.
Neal NavaniLungs for Living Research Centre, University College London, London, England; Department of Thoracic Medicine, University College London Hospital, London, England.
Samuel M JanesLungs for Living Research Centre, University College London, London, England.
Robert F MillerResearch Department of Infection and Population Health, University College London, London, England.
Mahdad NoursadeghiDepartment of Infection and Immunity, University College London, London, England.
University College London · GBHomerton University Hospital · GB

Funding

Medical Research Council G0800465Wellcome Trust 091730Wellcome Trust WT091730AIA
6 · The paper itself

Abstract

backgroundEndobronchial ultrasound (EBUS)-guided biopsy is the mainstay for investigation of mediastinal lymphadenopathy for laboratory diagnosis of malignancy, sarcoidosis, or TB. However, improved methods for discriminating between TB and sarcoidosis and excluding malignancy are still needed. We sought to evaluate the role of genomewide transcriptional profiling to aid diagnostic processes in this setting.

methodsMediastinal lymph node samples from 88 individuals were obtained by EBUS-guided aspiration for investigation of mediastinal lymphadenopathy and subjected to transcriptional profiling in addition to conventional laboratory assessments. Computational strategies were used to evaluate the potential for using the transcriptome to distinguish between diagnostic categories.

resultsMolecular signatures associated with granulomas or neoplastic and metastatic processes were clearly discernible in granulomatous and malignant lymph node samples, respectively. Support vector machine (SVM) learning using differentially expressed genes showed excellent sensitivity and specificity profiles in receiver operating characteristic curve analysis with area under curve values > 0.9 for discriminating between granulomatous and nongranulomatous disease, TB and sarcoidosis, and between cancer and reactive lymphadenopathy. A two-step decision tree using SVM to distinguish granulomatous and nongranulomatous disease, then between TB and sarcoidosis in granulomatous cases, and between cancer and reactive lymphadenopathy in nongranulomatous cases, achieved > 90% specificity for each diagnosis and afforded greater sensitivity than existing tests to detect TB and cancer. In some diagnostically ambiguous cases, computational classification predicted granulomatous disease or cancer before pathologic abnormalities were evident.

conclusionsMachine learning analysis of transcriptional profiling in mediastinal lymphadenopathy may significantly improve the clinical utility of EBUS-guided biopsies.

Indexed as

TranscriptomeAdultAgedAged, 80 and overBronchoscopyEndoscopic Ultrasound-Guided Fine Needle AspirationFemaleHumansLymphatic DiseasesLymph NodesMaleMediastinal DiseasesMediastinumMiddle AgedRNAROC CurveRNAcancermachine learningsarcoidosistranscriptometuberculosis

Identifiers

PMID26270185
PMCPMC4740456
OpenAlexW2281400799

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.