Evidence map›Paper›PMID 30140929›Full record

ArticleJAMA dermatology2018

Accuracy of Digital Pathologic Analysis vs Traditional Microscopy in the Interpretation of Melanocytic Lesions.

Tracy Onega, Raymond L Barnhill, Michael W Piepkorn, Gary M Longton, David E Elder, Martin A Weinstock, Stevan R Knezevich, Lisa M Reisch, Patricia A Carney, Heidi D Nelson and 2 more

Abstract readComparative Study
In one paragraph

Article in JAMA dermatology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
  4. Review
  5. Article
  6. Artificial intelligence and skin cancer.Frontiers in medicine · 2024
    Review
  7. Article
  8. Article
  9. Article
  10. Article
  11. Review
  12. 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

12 authors.

Tracy OnegaDepartments of Medicine and Community and Family Medicine, The Dartmouth Institute for Health Policy and Clinical Practice, Hanover, New Hampshire.
Raymond L BarnhillDepartment of Pathology, Institut Curie, Paris Sciences and Lettres Research University, and Faculty of Medicine University of Paris Descartes, Paris, France.
Michael W PiepkornDivision of Dermatology, Department of Medicine, University of Washington School of Medicine, Seattle.
Gary M LongtonProgram in Biostatistics and Biomathematics, Fred Hutchinson Cancer Research Center, Seattle, Washington.
David E ElderDepartment of Pathology and Laboratory Medicine, Hospital of the University of Pennsylvania, Philadelphia.
Martin A WeinstockCenter for Dermatoepidemiology, Providence VA Medical Center, Providence, Rhode Island.
Stevan R KnezevichPathology Associates, Clovis, California.
Lisa M ReischDepartment of Medicine, University of Washington School of Medicine, Seattle.
Patricia A CarneyDepartment of Family Medicine, School of Medicine, Oregon Health & Science University, Portland.
Heidi D NelsonDepartment of Medical Informatics and Clinical Epidemiology, School of Medicine, Oregon Health & Science University, Portland.
Andrea C RadickDepartment of Medicine, University of Washington School of Medicine, Seattle.
Joann G ElmoreDepartment of Medicine, David Geffen School of Medicine at UCLA, Los Angeles, California.

Funding

Accuracy in the Diagnosis of Melanoma & the Impact of Double ReadingR01CA151306 · NCI · UNIVERSITY OF WASHINGTON · PI ELMORE, JOANN G · 2011 to 2015
$4.1M
Reducing Errors in the Diagnosis of Melanoma and Melanocytic LesionsR01CA201376 · NCI · UNIVERSITY OF WASHINGTON · PI ELMORE, JOANN G, KERR, KATHLEEN F. · 2016 to 2020
$3.2M
Improving Melanoma Pathology Accuracy through Computer Vision Techniques - the IMPACT StudyR01CA200690 · NCI · UNIVERSITY OF WASHINGTON · PI ELMORE, JOANN G, SHAPIRO, LINDA · 2016 to 2020
$1.9M
NCI NIH HHS R01 CA151306NCI NIH HHS R01 CA200690NCI NIH HHS R01 CA201376
6 · The paper itself

Abstract

Importance: Use of digital whole-slide imaging (WSI) for dermatopathology in general has been noted to be similar to traditional microscopy (TM); however, concern has been noted that WSI is inferior for interpretation of melanocytic lesions. Since approximately 1 of every 4 skin biopsies is of a melanocytic lesion, the use of WSI requires verification before use in clinical practice. Objective: To compare pathologists' accuracy and reproducibility in diagnosing melanocytic lesions using Melanocytic Pathology Assessment Tool and Hierarchy for Diagnosis (MPATH-Dx) categories when analyzing by TM vs WSI. Design, Setting, and Participants: A total of 87 pathologists in community-based and academic settings from 10 US states were randomized with stratification based on clinical experience to interpret in TM format 180 skin biopsy cases of melanocytic lesions, including 90 invasive melanoma, divided into 5 sets of 36 cases (phase 1). The pathologists were then randomized via stratified permuted block randomization with block size 2 to interpret cases in either TM (n = 46) or WSI format (n = 41), with each pathologist interpreting the same 36 cases on 2 separate occasions (phase 2). Diagnoses were categorized as MPATH-Dx categories I through V, with I indicating the least severe and V the most severe. Main Outcomes and Measures: Accuracy with respect to a consensus reference diagnosis and the reproducibility of repeated interpretations of the same cases. Results: Of the 87 pathologists in the study, 46% (40) were women and the mean (SD) age was 50.7 (10.2) years. Except for class III melanocytic lesions, the diagnostic categories showed no significant differences in diagnostic accuracy between TM and WSI interpretation. Discordance was lower among class III lesions for the TM interpretation arm (51%; 95% CI, 46%-57%) than for the WSI arm (61%; 95% CI, 53%-69%) (P = .05). This difference is likely to have clinical significance, because 6% of TM vs 11% of WSI class III lesions were interpreted as invasive melanoma. Reproducibility was similar between the traditional and digital formats overall (66.4%; 95% CI, 63.3%-69.3%; and 62.7%; 95% CI, 59.5%-65.7%, respectively), and for all classes, although class III showed a nonsignificant lower intraobserver agreement for digital. Significantly more mitotic figures were detected with TM compared with WSI: mean (SD) TM, 6.72 (2.89); WSI, 5.84 (2.56); P = .002. Conclusions and Relevance: Interpretive accuracy for melanocytic lesions was similar for WSI and TM slides except for class III lesions. We found no clinically meaningful differences in reproducibility for any of the diagnostic classes.

Indexed as

AdultBiopsyCutaneous Malignant MelanomaFemaleHumansMaleMelanocytesMelanomaMicroscopyMiddle AgedMitotic IndexNeoplasm InvasivenessObserver VariationRandom AllocationReproducibility of ResultsSkin

Identifiers

PMID30140929
PMCPMC6233746

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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.