Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 431

The DOI matches its OpenAlex record.

Frequency and Morphologic Characteristics of Invasive Melanomas Lacking Specific Surface Microscopic Features

Scott W. Menzies·1996·Archives of Dermatology

Abstract

OBJECTIVES: To create a simple diagnostic method for invasive melanoma with in vivo cutaneous surface microscopy (epiluminescence microscopy, dermoscopy, dermatoscopy) and to analyze the incidence and characteristics of those invasive melanomas that had no diagnostic features by means of hand-held surface microscopes. DESIGN: Pigmented skin lesions were photographed in vivo with the use of immersion oil. All were excised and reviewed for histological diagnosis. A training set of 62 invasive melanomas and 159 atypical nonmelanomas and a test set of 45 invasive melanomas and 119 atypical non-melanomas were used. Images from the training set were scored for 72 surface microscopic features. Those features with a low sensitivity (0%) and high specificity (> 85%) were used to create a simple diagnostic model for invasive melanoma. SETTING: All patients were recruited from the Sydney (Australia) Melanoma Unit (a primary case and referral center). PATIENTS: A random sample of patients whose lesions were excised, selected from a larger database. MAIN OUTCOME MEASURES: Sensitivity and specificity of the model for diagnosis of invasive melanona. RESULTS: The model gave a sensitivity of 92% (98/107) and specificity of 71%. Of the 9 "featureless" melanomas the model failed to detect, 6 were pigmented and thin and had a pigment network. The other 3 were thicker, hypomelanotic lesions lacking a pigment network, some with prominent telangiectases, and all with only small areas of pigment. All featureless melanomas noted by the patients had a history of change in color, shape, or size. CONCLUSIONS: Surface microscopy does not allow 100% sensitivity in diagnosing invasive melanoma and therefore cannot be used as the sole indicator for excision. Clinical history is an important consideration when featureless lesions are diagnosed.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

OpenAlex · 10.1001/archderm.132.10.1178

Cites

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cited by

Metadata

Authors
Menzies, S. W.
Venue
Archives of Dermatology
Publisher
American Medical Association
Published
1996-10-01
Volume
132
Issue
10
Pages
1178-1178
ISSN
0003-987X (ISSN-L)
OpenAlex
W2017573959
Cited by
431
References
0
FWCI
1.90
Type
journal article
Language
en
Open access
closed

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.