Evidence map›Paper›PMID 32280381›Full record

ReviewBreathe (Sheffield, England)2019

The electronic nose: emerging biomarkers in lung cancer diagnostics.

Wouter H van Geffen, Kevin Lamote, Adrien Costantini, Lizza E L Hendriks, Najib M Rahman, Torsten G Blum, Jan van Meerbeeck

Abstract readReview
In one paragraph

Review in Breathe (Sheffield, England), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Biomedicines · 2022
    Review
  6. Review
  7. 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

7 authors.

Wouter H van GeffenDept of Pulmonary Medicine, Medical Centre Leeuwarden, Leeuwarden, The Netherlands.ORCID https://orcid.org/0000-0002-5976-0974
Kevin LamoteDept of Pulmonology, Antwerp University Hospital, Edegem, Belgium.
Adrien CostantiniDept of Respiratory Diseases and Thoracic Oncology, APHP, Hôpital Ambroise Paré, Boulogne-Billancourt, France.
Lizza E L HendriksDept of Pulmonary Medicine, GROW - School for Oncology and Developmental Biology, Maastricht University Medical Centre, Maastricht, The Netherlands.
Najib M RahmanOxford Respiratory Trials Unit, Nuffield Dept of Medicine, University of Oxford, Oxford, UK.
Torsten G BlumLungenklinik Heckeshorn, Helios Klinikum Emil von Behring, Berlin, Germany.
Jan van MeerbeeckDept of Pulmonology, Antwerp University Hospital, Edegem, Belgium.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Lung cancer is very common and the most common cause of cancer death worldwide. Despite recent progress in the systemic treatment of lung cancer (checkpoint inhibitors and tyrosine kinase inhibitors), each year, >1.5 million people die due to this disease. Most lung cancer patients already have advanced disease at the time of diagnosis. Computed tomography screening of high-risk individuals can detect lung cancer at an earlier stage but at a cost of false-positive findings. Biomarkers could lead towards a reduction of these false-positive findings and earlier lung cancer diagnosis, and have the potential to improve outcomes and treatment monitoring. To date, there is a lack of such biomarkers for lung cancer and other thoracic malignancies, although electronic nose (e-nose)-derived biomarkers are of interest. E-nose techniques using exhaled breath component measurements can detect lung cancer with a sensitivity ranging from 71% to 96% and specificity from 33 to 100%. In some case series, such results have been validated but this is mostly using internal validation and hence, more work is needed. Furthermore, standardised sampling and analysis methods are lacking, impeding interstudy comparison and clinical implementation. In this narrative review, we provide an overview of the currently available data on E-nose technology for lung cancer detection.

Identifiers

PMID32280381
PMCPMC7121878

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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.