Evidence map›Paper›PMID 39369689›Full record

ArticleDermatology (Basel, Switzerland)2024

Validation of a Dermatoscopy-Based Algorithm for the Diagnosis of Acral Melanoma.

Christoph Müller, Harald Kittler, Philipp Tschandl, Christoph Rinner, Marie-Luise Grausenburger, Athanassios Kyrgidis, Hiroshi Koga, Elvira Moscarella, Zoe Apalla, Alessandro Di Stefani and 11 more

Abstract readValidation Study
In one paragraph

Article in Dermatology (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

21 authors.

Christoph MüllerDepartment of Dermatology, Medical University of Vienna, Vienna, Austria.
Harald KittlerDepartment of Dermatology, Medical University of Vienna, Vienna, Austria.
Philipp TschandlDepartment of Dermatology, Medical University of Vienna, Vienna, Austria.
Christoph RinnerCenter for Medical Statistics, Informatics and Intelligent Systems, Medical University of Vienna, Vienna, Austria.
Marie-Luise GrausenburgerCenter for Medical Statistics, Informatics and Intelligent Systems, Medical University of Vienna, Vienna, Austria.
Athanassios KyrgidisDepartment of Maxillofacial Surgery, Papanikolaou General Hospital of Thessaloniki, Aristotle University of Thessaloniki, Thessaloniki, Greece.
Hiroshi KogaDepartment of Dermatology, Shinshu University Hospital, Nagano, Japan.
Elvira MoscarellaDepartment of Dermatology, University of Modena and Reggio Emilia, Modena, Italy.
Zoe ApallaSecond Department of Dermatology, Aristotle University, Thessaloniki, Greece.
Alessandro Di StefaniDermatologia, Dipartimento Universitario di Medicina e Chirurgia Traslazionale, Università Cattolica del Sacro Cuore, Rome, Italy.
Ken KobayashiKobayashi Skin Care Clinic, Tokyo, Japan.
Elisabeth LazaridouSecond Department of Dermatology, Aristotle University, Thessaloniki, Greece.
Caterina LongoDepartment of Dermatology, University of Modena and Reggio Emilia, Modena, Italy.
Alice PhanNephrology-Rheumatology-Dermatology Department, Hôpital Femme Mère Enfant, Hospices Civils de Lyon, Bron, France.
Toshiaki SaidaDepartment of Dermatology, Shinshu University Hospital, Nagano, Japan.
Elena SotiriouFirst Department of Dermatology, School of Medicine, Aristotle University, Thessaloniki, Greece.
Masaru TanakaDepartment of Dermatology, Tokyo Women's Medical University Adachi Medical Center, Adachi, Japan.
Luc ThomasService de Dermatologie, Centre Hospitalier Lyon Sud, Hospices Civils de Lyon, Université Claude-Bernard-Lyon Lyon, Lyon, France.
Iris ZalaudekDepartment of Dermatology, Medical University of Trieste, Trieste, Italy.
Giuseppe ArgenzianoDermatology Unit, Department of Mentals and Physical Health and Preventive Medicine, University of Campania Luigi Vanvitelli Naples, Napoli, Italy.
Aimilios LallasFirst Department of Dermatology, School of Medicine, Aristotle University, Thessaloniki, Greece.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionDiagnosis of acral melanocytic lesions can be challenging. The BRAAFF checklist was introduced as a tool to help differentiate between acral nevi and melanoma but has not been validated.

methodsWe asked raters with varying expertise in dermatoscopy to diagnose dermatoscopic images of 533 acral nevi and 144 melanomas via an online platform with and without use of the BRAAFF checklist. From the ratings, we calculated sensitivity, specificity, and interrater agreement. Additionally, a new simplified version of the checklist was also tested.

resultsWe collected 6,880 ratings from 175 readers. The BRAAFF checklist achieved a sensitivity of 92.5% and a specificity of 65.0%, which was similar to diagnosis from pattern recognition (sensitivity 90.0%, specificity: 72.1%). Interrater agreement for the BRAAFF criteria ranged from fair to moderate, with lowest agreement for parallel ridge and fibrillar pattern (alpha = 0.31) and highest for asymmetry of colors and structures (alpha = 0.46). Agreement and diagnostic accuracy were higher for more experienced readers. A simplified version with only two criteria achieved similar sensitivity (95.0%) and lower specificity (60.0%) as the original BRAAFF checklist.

conclusionThe BRAAFF checklist is a useful tool for the diagnosis of melanocytic acral lesions with acceptable sensitivity and reasonable specificity but is not superior to pattern recognition. A simplified version of the checklist could be easier to use with equal sensitivity while exhibiting a modest reduction in specificity.

Indexed as

AlgorithmsDermoscopyMelanomaSensitivity and SpecificitySkin NeoplasmsChecklistDiagnosis, DifferentialHumansObserver VariationAcralBRAAFFDermoscopyMelanomaNevus

Identifiers

PMID39369689
PMCPMC11651327

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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.