Evidence map›Paper›PMID 25037162›Full record

ArticleOral oncology2014

Assessment of the sensitivity and specificity of tissue-specific-based and anatomical-based optical biomarkers for rapid detection of human head and neck squamous cell carcinoma.

Fangyao Hu, Karthik Vishwanath, H Wolfgang Beumer, Liana Puscas, Hamid R Afshari, Ramon M Esclamado, Richard Scher, Samuel Fisher, Justin Lo, Christine Mulvey and 2 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Oral oncology, 2014. 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
0.8field-weighted citation impact, top 25% 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

7 citing papers in PubMed, 12 citations in OpenAlex.

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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

12 authors at 3 institutions in 1 country.

Fangyao Hu *Duke University, Biomedical Engineering Department, Durham, NC, USA.
Karthik Vishwanath *Duke University, Biomedical Engineering Department, Durham, NC, USA.
H Wolfgang BeumerDivision of Otolaryngology - Head and Neck Surgery, Duke University Medical Center, Durham, NC, USA.
Liana PuscasDivision of Otolaryngology - Head and Neck Surgery, Duke University Medical Center, Durham, NC, USA.
Hamid R AfshariDental Service, Durham Veterans Administration Medical Center, Durham, NC, USA.
Ramon M EsclamadoDivision of Otolaryngology - Head and Neck Surgery, Duke University Medical Center, Durham, NC, USA.
Richard ScherDivision of Otolaryngology - Head and Neck Surgery, Duke University Medical Center, Durham, NC, USA.
Samuel FisherDivision of Otolaryngology - Head and Neck Surgery, Duke University Medical Center, Durham, NC, USA.
Justin LoDuke University, Biomedical Engineering Department, Durham, NC, USA.
Christine MulveyDuke University, Biomedical Engineering Department, Durham, NC, USA.
Nirmala RamanujamDuke University, Biomedical Engineering Department, Durham, NC, USA.
Walter T LeeDivision of Otolaryngology - Head and Neck Surgery, Duke University Medical Center, Durham, NC, USA.
Duke University · USDuke Medical Center · USDurham VA Medical Center · US

Funding

Can Optical Spectroscopy Predict Early Treatment Response in Solid TumorsK99CA140783 · NCI · DUKE UNIVERSITY · PI VISHWANATH, KARTHIK · 2010 to 2011
$206k
PKC Epsilon in Vascular DysfunctionI01BX001398 · VA · VETERANS ADMIN PALO ALTO HEALTH CARE SYS · PI ZHOU, WEI · 2012 to 2015
–
BLRD VA I01 BX001398NCI NIH HHS 5K99CA140783-02NCI NIH HHS K99 CA140783
6 · The paper itself

Abstract

objectivesWe propose the use of morphological optical biomarkers for rapid detection of human head and neck squamous cell carcinoma (HNSCC) by leveraging the underlying tissue characteristics in aerodigestive tracts. MATERIALS AND

methodsDiffuse reflectance spectra were obtained from malignant and contra-lateral normal tissues of 57 patients undergoing panendoscopy and biopsy. Oxygen saturation, total hemoglobin concentration, and the reduced scattering coefficient were extracted. Differences in malignant and normal tissues were examined based on two different groupings: anatomical site and morphological tissue type. RESULTS AND

conclusionsMeasurements were acquired from 252 sites, of which 51 were pathologically classified as SCC. Optical biomarkers exhibited statistical differences between malignant and normal samples. Contrast was enhanced when parsing tissues by morphological classification rather than anatomical subtype for unpaired comparisons. Corresponding linear discriminant models using multiple optical biomarkers showed improved predictive ability when accounting for morphological classification, particularly in node-positive lesions. The false-positive rate was retrospectively found to decrease by 34.2% in morphologically- vs. anatomically-derived predictive models. In glottic tissue, the surgeon exhibited a false-positive rate of 45.7% while the device showed a lower false-positive rate of 12.4%. Additionally, comparisons of optical parameters were made to further understand the physiology of tumor staging and potential causes of high surgeon false-positive rates. Optical spectroscopy is a user-friendly, non-invasive tool capable of providing quantitative information to discriminate malignant from normal head and neck tissues. Predictive models demonstrated promising results for real-time diagnostics. Furthermore, the strategy described appears to be well suited to reduce the clinical false-positive rate.

Indexed as

Biomarkers, TumorCarcinoma, Squamous CellHead and Neck NeoplasmsHumansSensitivity and SpecificitySpectrum AnalysisBiomarkers, TumorCancer detectionCancer screeningDiffuse reflectanceGlobal healthHead and neck cancerHypoxia

Identifiers

PMID25037162
PMCPMC4229069
OpenAlexW2063117062

What OpenQuestion holds

Textmetadata
LicenceTDM
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.