Evidence map›Paper›PMID 25299667›Full record

ArticlePloS one2014

Buccal spectral markers for lung cancer risk stratification.

Andrew J Radosevich, Nikhil N Mutyal, Jeremy D Rogers, Bradley Gould, Thomas A Hensing, Daniel Ray, Vadim Backman, Hemant K Roy

Abstract read
In one paragraph

Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing 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

16 citing papers in PubMed.

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  12. Microscope objective based 4Biomedical optics express · 2017
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  15. Rectal Optical Markers for In Vivo Risk Stratification of Premalignant Colorectal Lesions.Clinical cancer research : an official journal of the American Association for Cancer Research · 2015
    Article
  16. 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

8 authors.

Andrew J RadosevichBiomedical Engineering Department, Northwestern University, Evanston, Illinois, United States of America.
Nikhil N MutyalBiomedical Engineering Department, Northwestern University, Evanston, Illinois, United States of America.
Jeremy D RogersBiomedical Engineering Department, University of Wisconsin, Madison, Wisconsin, United States of America.
Bradley GouldBiomedical Engineering Department, Northwestern University, Evanston, Illinois, United States of America.
Thomas A HensingDepartment of Medicine, NorthShore University HealthSystems, Evanston, Illinois, United States of America.
Daniel RayDepartment of Medicine, NorthShore University HealthSystems, Evanston, Illinois, United States of America.
Vadim BackmanBiomedical Engineering Department, Northwestern University, Evanston, Illinois, United States of America.
Hemant K RoyDepartment of Medicine, Boston University, Boston, Massachusetts, United States of America.

Funding

Novel Biophotonics Methodology for Colon Cancer ScreeningR01CA128641 · NCI · NORTHWESTERN UNIVERSITY · PI BACKMAN, VADIM · 2008 to 2012
$7.3M
Optical Nanoscale Analysis of Buccal Cells: Transforming Lung Cancer ScreeningR01CA155284 · NCI · NORTHWESTERN UNIVERSITY · PI BACKMAN, VADIM, ROY, HEMANT K. · 2011 to 2014
$2.3M
NCI NIH HHS R01 CA128641NCI NIH HHS R01CA128641NCI NIH HHS R01 CA155284NCI NIH HHS R01CA155284
6 · The paper itself

Abstract

Lung cancer remains the leading cause of cancer deaths in the US with >150,000 deaths per year. In order to more effectively reduce lung cancer mortality, more sophisticated screening paradigms are needed. Previously, our group demonstrated the use of low-coherence enhanced backscattering (LEBS) spectroscopy to detect and quantify the micro/nano-architectural correlates of colorectal and pancreatic field carcinogenesis. In the lung, the buccal (cheek) mucosa has been suggested as an excellent surrogate site in the "field of injury". We, therefore, wanted to assess whether LEBS could similarly sense the presence of lung. To this end, we applied a fiber-optic LEBS probe to a dataset of 27 smokers without diagnosed lung cancer (controls) and 46 with lung cancer (cases), which was divided into a training and a blinded validation set (32 and 41 subjects, respectively). LEBS readings of the buccal mucosa were taken from the oral cavity applying gentle contact. The diagnostic LEBS marker was notably altered in patients harboring lung cancer compared to smoking controls. The prediction rule developed on training set data provided excellent diagnostics with 94% sensitivity, 80% specificity, and 95% accuracy. Applying the same threshold to the blinded validation set yielded 79% sensitivity and 83% specificity. These results were not confounded by patient demographics or impacted by cancer type or location. Moreover, the prediction rule was robust across all stages of cancer including stage I. We envision the use of LEBS as the first part of a two-step paradigm shift in lung cancer screening in which patients with high LEBS risk markers are funnelled into more invasive screening for confirmation.

Indexed as

CarcinogenesisEarly Detection of CancerFiber Optic TechnologyAgedAged, 80 and overBiomarkers, TumorFemaleHumansLung NeoplasmsMaleMiddle AgedMouth MucosaNanostructuresRisk FactorsSmokingBiomarkers, Tumor

Identifiers

PMID25299667
PMCPMC4192585

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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.