Evidence map›Paper›PMID 41815037›Full record

ArticleSkin research and technology : official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging (ISSI)2026

Near-Infrared Spectroscopy Combined With Skin Impedance for Detection of Skin Cancer in Primary Care.

Maria Fragkou Dragka, Tommy Löfstedt, Magnus Falk

Abstract read
In one paragraph

Article in Skin research and technology : official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging (ISSI), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Near-Infrared Spectroscopy Combined With Skin Impedance for Detection of Skin Cancer in Primary Care.Skin research and technology : official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging (ISSI) · 2026
    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

3 authors.

Maria Fragkou DragkaDepartment of Health, and Department of Dermatology and Venerology, Linkoping University, Medicine and Caring Sciences, Linköping University, Linköping, Sweden.
Tommy LöfstedtDepartment of Computing Science, Department of Health, Umeå University, Umeå, Sweden.ORCID https://orcid.org/0000-0001-7119-7646
Magnus FalkMedicine and Caring Sciences, and Kärna primary Healthcare Center, Region Östergötland, Linkoping University, Linköping, Sweden.

Funding

Region ÖstergötlandThe Research Council of Southeast Sweden (FORSS)
6 · The paper itself

Abstract

backgroundThe established method in primary care to distinguish skin cancer from benign lesions is clinical examination, with or without dermoscopy. The experience among primary care physicians in assessing skin tumours varies, as does the accessibility to teledermoscopy. To enhance diagnostic performance, improved methods for skin tumour assessment are warranted. The aim of this study was to investigate the diagnostic performance of a non-invasive method that combines near-infrared spectroscopy with skin impedance measurement (NIRIMP) to detect skin cancer in primary care. MATERIAL AND

methodsNIRIMP measurements were collected prospectively from patients seeking primary care for skin lesion examination. The measurements were compared to the true lesion diagnosis using several machine learning methods, to determine the best machine learning methods to use and to determine the diagnostic performance of NIRIMP in distinguishing skin cancer from benign lesions.

resultsEighty participants with 109 lesions were included. Among these, 50 skin cancers or in situ cancers were detected: eight melanomas/in situ melanomas, four in situ squamous cell carcinomas, and 38 basal cell carcinomas. The ability of NIRIMP to distinguish any skin cancer/in situ cancer, as illustrated by the area under the receiver operating characteristics curve (AUC), was 0.776 and for melanomas/in situ melanomas alone the AUC was 0.911. When detecting any skin cancer, the AUC was slightly higher for NIR alone (0.826) compared to NIRIMP (0.776), whereas for IMP alone it was slightly lower (0.693).

conclusionsNear infrared spectroscopy appears to be a promising bioengineering technique to detect skin cancer in primary care settings, of potential benefit for future skin lesion assessment. However, there was no compelling evidence supporting the benefit of adding skin impedance to improve diagnostic performance.

Indexed as

Skin NeoplasmsAdultAgedAged, 80 and overBasal Cell CarcinomaCarcinoma, Squamous CellCutaneous Squamous Cell CarcinomaElectric ImpedanceFemaleHumansMachine LearningMaleMelanomaMiddle AgedPrimary Health CareProspective Studiesbasal cell carcinomadiagnostic accuracymachine learningmelanomanear infrared spectroscopyskin impedancesquamous cell carcinoma

Identifiers

PMID41815037
PMCPMC13097356

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.