Evidence map›Paper›PMID 32575717›Full record

ArticleMolecules (Basel, Switzerland)2020

Assessment of Raman Spectroscopy for Reducing Unnecessary Biopsies for Melanoma Screening.

Yao Zhang, Austin J Moy, Xu Feng, Hieu T M Nguyen, Katherine R Sebastian, Jason S Reichenberg, Claus O Wilke, Mia K Markey, James W Tunnell

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Molecules (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 2 pooled it
2.5field-weighted citation impact, top 10% 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

8 citing papers in PubMed, 2 syntheses or guidelines pooled it, 17 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Review
  4. Review
  5. Review
  6. Review
  7. Review
  8. Cutaneous Oncology: Strategies for Melanoma Prevention, Diagnosis, and Therapy.Cancer control : journal of the Moffitt Cancer Center
    Review
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

9 authors at 2 institutions in 1 country.

Yao ZhangDepartment of Biomedical Engineering, The University of Texas at Austin, Austin, TX 78712, USA.
Austin J MoyDepartment of Biomedical Engineering, The University of Texas at Austin, Austin, TX 78712, USA.
Xu FengDepartment of Biomedical Engineering, The University of Texas at Austin, Austin, TX 78712, USA.ORCID 0000-0002-9048-7144
Hieu T M NguyenDepartment of Biomedical Engineering, The University of Texas at Austin, Austin, TX 78712, USA.
Katherine R SebastianDepartment of Medicine, The University of Texas at Austin, Austin, TX 78712, USA.
Jason S ReichenbergDepartment of Medicine, The University of Texas at Austin, Austin, TX 78712, USA.
Claus O WilkeDepartment of Integrative Biology, The University of Texas at Austin, Austin, TX 78712, USA.ORCID 0000-0002-7470-9261
Mia K MarkeyDepartment of Biomedical Engineering, The University of Texas at Austin, Austin, TX 78712, USA.
James W TunnellDepartment of Biomedical Engineering, The University of Texas at Austin, Austin, TX 78712, USA.ORCID 0000-0002-6264-0981
The University of Texas at Austin · USThe University of Texas MD Anderson Cancer Center · US

Funding

Cancer Prevention and Research Institute of Texas RP130702
6 · The paper itself

Abstract

A key challenge in melanoma diagnosis is the large number of unnecessary biopsies on benign nevi, which requires significant amounts of time and money. To reduce unnecessary biopsies while still accurately detecting melanoma lesions, we propose using Raman spectroscopy as a non-invasive, fast, and inexpensive method for generating a "second opinion" for lesions being considered for biopsy. We collected in vivo Raman spectral data in the clinical skin screening setting from 52 patients, including 53 pigmented lesions and 7 melanomas. All lesions underwent biopsies based on clinical evaluation. Principal component analysis and logistic regression models with leave one lesion out cross validation were applied to classify melanoma and pigmented lesions for biopsy recommendations. Our model achieved an area under the receiver operating characteristic (ROC) curve (AUROC) of 0.903 and a specificity of 58.5% at perfect sensitivity. The number needed to treat for melanoma could have been decreased from 8.6 (60/7) to 4.1 (29/7). This study in a clinical skin screening setting shows the potential of Raman spectroscopy for reducing unnecessary skin biopsies with in vivo Raman data and is a significant step toward the application of Raman spectroscopy for melanoma screening in the clinic.

Indexed as

BiopsyHumansLogistic ModelsMelanomaPrincipal Component AnalysisROC CurveSkin NeoplasmsSpectrum Analysis, RamanclassificationmelanomaRaman spectroscopyskin screeningspecificity

Identifiers

PMID32575717
PMCPMC7355922
OpenAlexW3036832556

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.