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Hosler GA, Goldberg MS, Estrada SI, O'Neil B, Amin SM, Plaza JA. Diagnostic discordance among histopathological reviewers of melanocytic lesions. J Cutan Pathol 2024; 51:624-633. [PMID: 38725224 DOI: 10.1111/cup.14635] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2023] [Revised: 03/25/2024] [Accepted: 04/21/2024] [Indexed: 07/09/2024]
Abstract
BACKGROUND Histopathological examination is adequate for the diagnosis of most cutaneous melanocytic neoplasms. However, there is a subset that is either difficult to definitively diagnose or would have diagnostic disagreement upon review by multiple dermatopathologists if a more exhaustive review was performed. METHODS Melanocytic lesions underwent an independent, blinded diagnostic histopathological review of hematoxylin and eosin-stained sections. Each lesion was reviewed by three to six dermatopathologists and categorized as benign, malignant, or unknown malignant potential (UMP). Diagnoses were grouped as concordant (all the same designation); opposing (received benign and malignant designations); majority (single designation with the highest number of diagnoses, no benign/malignant opposing designations); and non-definitive (equal number of non-opposing designations [i.e., benign/UMP or malignant/UMP]). Lesions with equivocal designations (concordant or majority UMP, opposing, majority, and non-definitive) were utilized in a patient treatment model of projected surgical treatment discrepancies. RESULTS In total, 3317 cases were reviewed, and 23.8% of lesions received equivocal diagnoses. Of these, 7.3% were majority benign, 4.8% were majority malignant, 2.7% were majority UMP, 0.5% were concordant UMP, 6.9% were opposing, and 1.6% were non-definitive. Patient treatment models of those with equivocal lesions (n = 788) revealed a potential of overall surgical treatment variations ranging from 18% to 72%, with the highest variation amongst lesions with opposing, non-definitive, or majority UMP (40%-72%) diagnoses. CONCLUSION Histopathologic review in this large cohort demonstrated substantial diagnostic variation, with 23.8% of cases receiving equivocal diagnoses. We identified diagnostic ambiguity even in lesions where a definitive diagnosis was previously rendered by a single real-world dermatopathologist. The combined clinical impact of diagnostic discordance or a final diagnosis of UMP is highlighted by high diagnosis-dependent treatment variation in the patient treatment model, which could be underreported in a real-world setting, where review by more than one to two dermatopathologists is relatively rare.
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Affiliation(s)
| | - Matthew S Goldberg
- Castle Biosciences, Inc, Friendswood, Texas, USA
- Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | | | - Brendan O'Neil
- Northern Arizona Dermatology Center, Flagstaff, Arizona, USA
| | | | - Jose A Plaza
- Department of Pathology and Dermatology, The Ohio State University Wexner Medical Center, Columbus, Ohio, USA
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Scope A, Liopyris K, Weber J, Barnhill RL, Braun RP, Curiel-Lewandrowski CN, Elder DE, Ferrara G, Grant-Kels JM, Jeunon T, Lallas A, Lin JY, Marchetti MA, Marghoob AA, Navarrete-Dechent C, Pellacani G, Soyer HP, Stratigos A, Thomas L, Kittler H, Rotemberg V, Halpern AC. International Skin Imaging Collaboration-Designated Diagnoses (ISIC-DX): Consensus terminology for lesion diagnostic labeling. J Eur Acad Dermatol Venereol 2024. [PMID: 38733254 DOI: 10.1111/jdv.20055] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2023] [Accepted: 02/16/2024] [Indexed: 05/13/2024]
Abstract
BACKGROUND A common terminology for diagnosis is critically important for clinical communication, education, research and artificial intelligence. Prevailing lexicons are limited in fully representing skin neoplasms. OBJECTIVES To achieve expert consensus on diagnostic terms for skin neoplasms and their hierarchical mapping. METHODS Diagnostic terms were extracted from textbooks, publications and extant diagnostic codes. Terms were hierarchically mapped to super-categories (e.g. 'benign') and cellular/tissue-differentiation categories (e.g. 'melanocytic'), and appended with pertinent-modifiers and synonyms. These terms were evaluated using a modified-Delphi consensus approach. Experts from the International-Skin-Imaging-Collaboration (ISIC) were surveyed on agreement with terms and their hierarchical mapping; they could suggest modifying, deleting or adding terms. Consensus threshold was >75% for the initial rounds and >50% for the final round. RESULTS Eighteen experts completed all Delphi rounds. Of 379 terms, 356 (94%) reached consensus in round one. Eleven of 226 (5%) benign-category terms, 6/140 (4%) malignant-category terms and 6/13 (46%) indeterminate-category terms did not reach initial agreement. Following three rounds, final consensus consisted of 362 terms mapped to 3 super-categories and 41 cellular/tissue-differentiation categories. CONCLUSIONS We have created, agreed upon, and made public a taxonomy for skin neoplasms and their hierarchical mapping. Further study will be needed to evaluate the utility and completeness of the lexicon.
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Affiliation(s)
- Alon Scope
- The Kittner Skin Cancer Screening & Research Institute, Sheba Medical Center and Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
- Dermatology Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - Konstantinos Liopyris
- Dermatology Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, New York, USA
- Department of Dermatology-Venereology, University of Athens Medical School, Athens, Greece
| | - Jochen Weber
- Dermatology Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - Raymond L Barnhill
- Department of Translational Research, Institut Curie, and UFR de Médecine, Université de Paris, Paris, France
| | - Ralph P Braun
- Department of Dermatology, University Hospital Zurich, Zurich, Switzerland
| | - Clara N Curiel-Lewandrowski
- Department of Dermatology, University of Arizona College of Medicine, and the University of Arizona Cancer Center Skin Cancer Institute, Tucson, Arizona, USA
| | - David E Elder
- Department of Pathology and Laboratory Medicine, Hospital of the University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Gerardo Ferrara
- Anatomic Pathology and Cytopathology Unit, Istituto Nazionale Tumori IRCCS Fondazione 'G. Pascale', Naples, Italy
| | - Jane M Grant-Kels
- Department of Dermatology, UConn Health, Farmington, Connecticut, USA
- Department of Dermatology, University of Florida, Gainesville, Florida, USA
| | - Thiago Jeunon
- Departments of Dermatology and Pathology, Hospital Federal de Bonsucesso, Rio de Janeiro, Brazil
| | - Aimilios Lallas
- First Department of Dermatology, Aristotle University, Thessaloniki, Greece
| | - Jennifer Y Lin
- Department of Dermatology, Brigham and Women's Hospital and Melanoma Program, Dana-Farber Cancer Institute, Boston, Massachusetts, USA
| | - Michael A Marchetti
- Dermatology Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - Ashfaq A Marghoob
- Dermatology Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - Cristian Navarrete-Dechent
- Melanoma and Skin Cancer Unit and Department of Dermatology, Escuela de Medicina, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Giovanni Pellacani
- Department of Dermatology, University of Modena and Reggio Emilia, Modena and Dermatology Clinic, University of Rome, Rome, Italy
| | - Hans Peter Soyer
- The University of Queensland Diamantina Institute, University of Queensland, Dermatology Research Centre, Brisbane, Queensland, Australia
| | - Alexander Stratigos
- 1st Department of Dermatology-Venereology, Andreas Sygros Hospital, National and Kapodistrian University of Athens School of Medicine, Athens, Greece
| | - Luc Thomas
- Dermatology Department, Hôpital Universitaire Lyon Sud, Hospices Civils de Lyon, Pierre-Bénite, France
| | - Harald Kittler
- Department of Dermatology, Medical University of Vienna, Vienna, Austria
| | - Veronica Rotemberg
- Dermatology Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - Allan C Halpern
- Dermatology Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, New York, USA
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3
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Ojukwu K, Eguchi MM, Adamson AS, Kerr KF, Piepkorn MW, Murdoch S, Barnhill RL, Elder DE, Knezevich SR, Elmore JG. Immunohistochemistry for Diagnosing Melanoma in Older Adults. JAMA Dermatol 2024; 160:434-440. [PMID: 38446470 PMCID: PMC10918577 DOI: 10.1001/jamadermatol.2023.6417] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2023] [Accepted: 12/23/2023] [Indexed: 03/07/2024]
Abstract
Importance Pathologic assessment to diagnose skin biopsies, especially for cutaneous melanoma, can be challenging, and immunohistochemistry (IHC) staining has the potential to aid decision-making. Currently, the temporal trends regarding the use of IHC for the examination of skin biopsies on a national level have not been described. Objective To illustrate trends in the use of IHC for the examination of skin biopsies in melanoma diagnoses. Design, Setting, and Participants A retrospective cross-sectional study was conducted to examine incident cases of melanoma diagnosed between January 2000 and December 2017. The analysis used the SEER-Medicare linked database, incorporating data from 17 population-based registries. The study focused on incident cases of in situ or malignant melanoma of the skin diagnosed in patients 65 years or older. Data were analyzed between August 2022 and November 2023. Main Outcomes and Measures The main outcomes encompassed the identification of claims for IHC within the month of melanoma diagnoses and extending up to 14 days into the month following diagnosis. The SEER data on patients with melanoma comprised demographic, tumor, and area-level characteristics. Results The final sample comprised 132 547 melanoma tumors in 116 117 distinct patients. Of the 132 547 melanoma diagnoses meeting inclusion criteria from 2000 to 2017, 43 396 cases had accompanying IHC claims (33%). Among these cases, 28 298 (65%) were diagnosed in male patients, 19 019 (44%) were diagnosed in patients aged 65 years to 74 years, 16 444 (38%) in patients aged 75 years to 84 years, and 7933 (18%) in patients aged 85 years and older. In 2000, 11% of melanoma cases had claims for IHC at or near the time of diagnosis. This proportion increased yearly, with 51% of melanoma cases having associated IHC claims in 2017. Increasing IHC use is observed for all stages of melanoma, including in situ melanoma. Claims for IHC in melanomas increased in all 17 SEER registries but at different rates. In 2017, the use of IHC for melanoma diagnosis ranged from 39% to 68% across registries. Conclusions and Relevance Considering the dramatically rising and variable use of IHC in diagnosing melanoma by pathologists demonstrated in this retrospective cross-sectional study, further investigation is warranted to understand the clinical utility and discern when IHC most improves diagnostic accuracy or helps patients.
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Affiliation(s)
- Kenechukwu Ojukwu
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles
| | - Megan M. Eguchi
- Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles
| | - Adewole S. Adamson
- Division of Dermatology, Department of Medicine, Dell Medical School, The University of Texas at Austin
- Deputy Editor and Web Editor, JAMA Dermatology
| | | | - Michael W. Piepkorn
- Division of Dermatology, Department of Medicine, University of Washington School of Medicine, Seattle
- Dermatopathology Northwest, Bellevue, Washington
| | | | - Raymond L. Barnhill
- Department of Translational Research, Institut Curie, Paris Sciences and Lettres Research University, and Faculty of Medicine University of Paris Descartes, Paris, France
| | - David E. Elder
- Department of Pathology and Laboratory Medicine, Hospital of the University of Pennsylvania, Philadelphia
| | | | - Joann G. Elmore
- Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles
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4
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Kerr KF, Elder DE, Piepkorn MW, Knezevich SR, Eguchi MM, Shucard HL, Reisch LM, Elmore JG, Barnhill RL. Pathologist Characteristics Associated With Rendering Higher-Grade Diagnoses for Melanocytic Lesions. JAMA Dermatol 2023; 159:1315-1322. [PMID: 37938821 PMCID: PMC10633399 DOI: 10.1001/jamadermatol.2023.4334] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2023] [Accepted: 07/10/2023] [Indexed: 11/10/2023]
Abstract
Importance The incidence of melanoma diagnoses has been increasing in recent decades, and controlled studies have indicated high histopathologic discordance across the intermediate range of melanocytic lesions. The respective causes for these phenomena remain incompletely understood. Objective To identify pathologist characteristics associated with tendencies to diagnose melanocytic lesions as higher grade vs lower grade or to diagnose invasive melanoma vs any less severe diagnosis. Design, Setting, and Participants This exploratory study used data from 2 nationwide studies (the Melanoma Pathology [M-Path] study, conducted from July 2013 to May 2016, and the Reducing Errors in Melanocytic Interpretations [REMI] study, conducted from August 2018 to March 2021) in which participating pathologists who interpreted melanocytic lesions in their clinical practices interpreted study cases in glass slide format. Each pathologist was randomly assigned to interpret a set of study cases from a repository of skin biopsy samples of melanocytic lesions; each case was independently interpreted by multiple pathologists. Data were analyzed from July 2022 to February 2023. Main Outcomes and Measures The association of pathologist characteristics with diagnosis of a study case as higher grade (including severely dysplastic and melanoma in situ) vs lower grade (including mild to moderately dysplastic nevi) and diagnosis of invasive melanoma vs any less severe diagnosis was assessed using logistic regression. Characteristics included demographics (age, gender, and geographic region), years of experience, academic affiliation, caseload of melanocytic lesions in their practice, specialty training, and history of malpractice suits. Results A total of 338 pathologists were included: 113 general pathologists and 74 dermatopathologists from M-Path and 151 dermatopathologists from REMI. The predominant factor associated with rendering more severe diagnoses was specialist training in dermatopathology (board certification and/or fellowship training). Pathologists with this training were more likely to render higher-grade diagnoses (odds ratio [OR], 2.63; 95% CI, 2.10-3.30; P < .001) and to diagnose invasive melanoma (OR, 1.95; 95% CI, 1.53-2.49; P < .001) than pathologists without this training interpreting the same case. Nonmitogenic pT1a diagnoses (stage pT1a melanomas with no mitotic activity) accounted for the observed difference in diagnosis of invasive melanoma; when these lesions, which carry a low risk of metastasis, were grouped with the less severe diagnoses, there was no observed association (OR, 0.95; 95% CI, 0.74-1.23; P = .71). Among dermatopathologists, those with a higher caseload of melanocytic lesions in their practice were more likely to assign higher-grade diagnoses (OR for trend, 1.27; 95% CI, 1.04-1.56; P = .02). Conclusions and Relevance The findings suggest that specialty training in dermatopathology is associated with a greater tendency to diagnose atypical melanocytic proliferations as pT1a melanomas. These low-risk melanomas constitute a growing proportion of melanomas diagnosed in the US.
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Affiliation(s)
| | - David E. Elder
- Department of Pathology and Laboratory Medicine, Hospital of the University of Pennsylvania, Philadelphia
| | - Michael W. Piepkorn
- Division of Dermatology, Department of Medicine, University of Washington School of Medicine, Seattle
- Dermatopathology Northwest, Bellevue, Washington
| | | | - Megan M. Eguchi
- Department of Medicine, David Geffen School of Medicine at UCLA, Los Angeles, California
| | | | - Lisa M. Reisch
- Department of Biostatistics, University of Washington, Seattle
| | - Joann G. Elmore
- Department of Medicine, David Geffen School of Medicine at UCLA, Los Angeles, California
| | - Raymond L. Barnhill
- Department of Translational Research, Institut Curie, Paris, France
- UFR of Medicine, University of Paris Cité, Paris, France
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Nethanel A, Kyprianou C, Barzilai A, Shapira-Frommer R, Shoham Y, Kornhaber R, Cleary M, Avinoam-Dar G, Grynberg S, Haik J, Debby A, Harats M. The Implications of a Dermatopathologist's Report on Melanoma Diagnosis and Treatment. Life (Basel) 2023; 13:1803. [PMID: 37763207 PMCID: PMC10532537 DOI: 10.3390/life13091803] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2023] [Revised: 08/07/2023] [Accepted: 08/11/2023] [Indexed: 09/29/2023] Open
Abstract
An accurate and comprehensive histopathology report is essential for cutaneous melanoma management, providing critical information for accurate staging and risk estimation and determining the optimal surgical approach. In many institutions, a review of melanoma biopsy specimens by expert dermatopathologists is considered a necessary step. This study examined these reviews to determine the critical primary histopathology Breslow score in which a histopathology review would be most beneficial. Histopathology reports of patients referred to our institute between January 2011 and September 2019 were compared with our in-house review conducted by an expert dermatopathologist. The review focused on assessing fundamental histologic and clinical prognostic features. A total of 177 specimens underwent histopathology review. Significant changes in the Breslow index were identified in 103 cases (58.2%). Notably, in many of these cases (73.2%), the revised Breslow was higher than the initially reported score. Consequently, the T-stage was modified in 51 lesions (28.8%). Substantial discordance rates were observed in Tis (57%), T1b (59%), T3a (67%) and T4a (50%) classifications. The revised histopathology reports resulted in alterations to the surgical plan in 15.3% of the cases. These findings emphasize the importance of having all routine pathologies of pigmented lesions referred to a dedicated cancer center and reviewed by an experienced dermatopathologist. This recommendation is particularly crucial in instances where the histopathology review can potentially alter the diagnosis and treatment plan, such as in melanoma in situ and thinner melanomas measuring 0.6-2.2 mm in thickness. Our study highlights the significant impact of histopathology reviews in cutaneous melanoma cases. The observed changes in Breslow scores and subsequent modifications in T-stage classification underline the need for thorough evaluation by an expert dermatopathologist, especially in cases of melanoma in situ and thin melanomas. Incorporating such reviews into routine practice within dedicated cancer centers can improve diagnostic accuracy and guide appropriate treatment decisions, ultimately leading to better patient outcomes.
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Affiliation(s)
- Asher Nethanel
- Ella Lemelbaum Institute for Immuno-Oncology, Sheba Medical Center, Tel-Hashomer, Ramat Gan 52621, Israel; (R.S.-F.); (S.G.)
| | - Christofis Kyprianou
- Department of Plastic and Reconstructive Surgery, Sheba Medical Center, Tel-Hashomer, Ramat Gan 52621, Israel; (C.K.); (R.K.); (G.A.-D.); (J.H.); (M.H.)
| | - Aviv Barzilai
- Department of Dermatology, Institute of Pathology, Sheba Medical Center, Tel-Hashomer, Ramat Gan 52621, Israel; (A.B.)
| | - Ronnie Shapira-Frommer
- Ella Lemelbaum Institute for Immuno-Oncology, Sheba Medical Center, Tel-Hashomer, Ramat Gan 52621, Israel; (R.S.-F.); (S.G.)
| | - Yaron Shoham
- Plastic Surgery Department, Burn Unit, Soroka University Medical Center, Faculty of Health Sciences, Ben Gurion University of the Negev, Beer Sheba 84105, Israel;
| | - Rachel Kornhaber
- Department of Plastic and Reconstructive Surgery, Sheba Medical Center, Tel-Hashomer, Ramat Gan 52621, Israel; (C.K.); (R.K.); (G.A.-D.); (J.H.); (M.H.)
- School of Nursing, Paramedicine and Healthcare Sciences, Charles Sturt University, Bathurst, NSW 2795, Australia
| | - Michelle Cleary
- School of Nursing, Midwifery & Social Sciences, Central Queensland University, Sydney, NSW 2000, Australia;
| | - Galit Avinoam-Dar
- Department of Plastic and Reconstructive Surgery, Sheba Medical Center, Tel-Hashomer, Ramat Gan 52621, Israel; (C.K.); (R.K.); (G.A.-D.); (J.H.); (M.H.)
- Faculty of Medicine, Tel-Aviv University, Tel-Aviv 69978, Israel
| | - Shirly Grynberg
- Ella Lemelbaum Institute for Immuno-Oncology, Sheba Medical Center, Tel-Hashomer, Ramat Gan 52621, Israel; (R.S.-F.); (S.G.)
| | - Josef Haik
- Department of Plastic and Reconstructive Surgery, Sheba Medical Center, Tel-Hashomer, Ramat Gan 52621, Israel; (C.K.); (R.K.); (G.A.-D.); (J.H.); (M.H.)
- Faculty of Medicine, Tel-Aviv University, Tel-Aviv 69978, Israel
- Talpiot Leadership Program, Sheba Medical Center, Tel-Hashomer, Ramat Gan 52621, Israel
- Institute for Health Research, University of Notre Dame, Fremantle, WA 6160, Australia
| | - Assaf Debby
- Department of Dermatology, Institute of Pathology, Sheba Medical Center, Tel-Hashomer, Ramat Gan 52621, Israel; (A.B.)
| | - Moti Harats
- Department of Plastic and Reconstructive Surgery, Sheba Medical Center, Tel-Hashomer, Ramat Gan 52621, Israel; (C.K.); (R.K.); (G.A.-D.); (J.H.); (M.H.)
- Faculty of Medicine, Tel-Aviv University, Tel-Aviv 69978, Israel
- Talpiot Leadership Program, Sheba Medical Center, Tel-Hashomer, Ramat Gan 52621, Israel
- Institute for Health Research, University of Notre Dame, Fremantle, WA 6160, Australia
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Clayton DA, Eguchi MM, Kerr KF, Miyoshi K, Brunyé TT, Drew T, Weaver DL, Elmore JG. Are Pathologists Self-Aware of Their Diagnostic Accuracy? Metacognition and the Diagnostic Process in Pathology. Med Decis Making 2023; 43:164-174. [PMID: 36124966 PMCID: PMC9825636 DOI: 10.1177/0272989x221126528] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Abstract
BACKGROUND Metacognition is a cognitive process that involves self-awareness of thinking, understanding, and performance. This study assesses pathologists' metacognition by examining the association between their diagnostic accuracy and self-reported confidence levels while interpreting skin and breast biopsies. DESIGN We studied 187 pathologists from the Melanoma Pathology Study (M-Path) and 115 pathologists from the Breast Pathology Study (B-Path). We measured pathologists' metacognitive ability by examining the area under the curve (AUC), the area under each pathologist's receiver operating characteristic (ROC) curve summarizing the association between confidence and diagnostic accuracy. We investigated possible relationships between this AUC measure, referred to as metacognitive sensitivity, and pathologist attributes. We also assessed whether higher metacognitive sensitivity affected the association between diagnostic accuracy and a secondary diagnostic action such as requesting a second opinion. RESULTS We found no significant associations between pathologist clinical attributes and metacognitive AUC. However, we found that pathologists with higher AUC showed a stronger trend to request secondary diagnostic action for inaccurate diagnoses and not for accurate diagnoses compared with pathologists with lower AUC. LIMITATIONS Pathologists reported confidence in specific diagnostic terms, rather than the broader classes into which the diagnostic terms were later grouped to determine accuracy. In addition, while there is no gold standard for the correct diagnosis to determine the accuracy of pathologists' interpretations, our studies achieved a high-quality reference diagnosis by using the consensus diagnosis of 3 experienced pathologists. CONCLUSIONS Metacognition can affect clinical decisions. If pathologists have self-awareness that their diagnosis may be inaccurate, they can request additional tests or second opinions, providing the opportunity to correct inaccurate diagnoses. HIGHLIGHTS Metacognitive sensitivity varied across pathologists, with most showing higher sensitivity than expected by chance.None of the demographic or clinical characteristics we examined was significantly associated with metacognitive sensitivity.Pathologists with higher metacognitive sensitivity were more likely to request additional tests or second opinions for their inaccurate diagnoses.
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Affiliation(s)
- Dayna A. Clayton
- Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles, CA, United States of America
| | - Megan M. Eguchi
- Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles, CA, United States of America
| | - Kathleen F. Kerr
- Department of Biostatistics, University of Washington, Seattle, WA, United States of America
| | - Kiyofumi Miyoshi
- Department of Psychology, University of California, Los Angeles, CA, United States of America
| | - Tad T. Brunyé
- Center for Applied Brain and Cognitive Sciences, Tufts University, Medford, MA, United States of America
| | - Trafton Drew
- Department of Psychology, University of Utah, Salt Lake City, UT, United States of America
| | - Donald L. Weaver
- Department of Pathology & Laboratory Medicine, University of Vermont Larner College of Medicine, Burlington, VT
| | - Joann G. Elmore
- Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles, CA, United States of America
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Requa J, Godard T, Mandal R, Balzer B, Whittemore D, George E, Barcelona F, Lambert C, Lee J, Lambert A, Larson A, Osmond G. High-fidelity detection, subtyping, and localization of five skin neoplasms using supervised and semi-supervised learning. J Pathol Inform 2022; 14:100159. [PMID: 36506813 PMCID: PMC9731861 DOI: 10.1016/j.jpi.2022.100159] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2022] [Revised: 11/16/2022] [Accepted: 11/22/2022] [Indexed: 11/27/2022] Open
Abstract
Background Skin cancers are the most common malignancies diagnosed worldwide. While the early detection and treatment of pre-cancerous and cancerous skin lesions can dramatically improve outcomes, factors such as a global shortage of pathologists, increased workloads, and high rates of diagnostic discordance underscore the need for techniques that improve pathology workflows. Although AI models are now being used to classify lesions from whole slide images (WSIs), diagnostic performance rarely surpasses that of expert pathologists. Objectives The objective of the present study was to create an AI model to detect and classify skin lesions with a higher degree of sensitivity than previously demonstrated, with potential to match and eventually surpass expert pathologists to improve clinical workflows. Methods We combined supervised learning (SL) with semi-supervised learning (SSL) to produce an end-to-end multi-level skin detection system that not only detects 5 main types of skin lesions with high sensitivity and specificity, but also subtypes, localizes, and provides margin status to evaluate the proximity of the lesion to non-epidermal margins. The Supervised Training Subset consisted of 2188 random WSIs collected by the PathologyWatch (PW) laboratory between 2013 and 2018, while the Weakly Supervised Subset consisted of 5161 WSIs from daily case specimens. The Validation Set consisted of 250 curated daily case WSIs obtained from the PW tissue archives and included 50 "mimickers". The Testing Set (3821 WSIs) was composed of non-curated daily case specimens collected from July 20, 2021 to August 20, 2021 from PW laboratories. Results The performance characteristics of our AI model (i.e., Mihm) were assessed retrospectively by running the Testing Set through the Mihm Evaluation Pipeline. Our results show that the sensitivity of Mihm in classifying melanocytic lesions, basal cell carcinoma, and atypical squamous lesions, verruca vulgaris, and seborrheic keratosis was 98.91% (95% CI: 98.27%, 99.55%), 97.24% (95% CI: 96.15%, 98.33%), 95.26% (95% CI: 93.79%, 96.73%), 93.50% (95% CI: 89.14%, 97.86%), and 86.91% (95% CI: 82.13%, 91.69%), respectively. Additionally, our multi-level (i.e., patch-level, ROI-level, and WSI-level) detection algorithm includes a qualitative feature that subtypes lesions, an AI overlay in the front-end digital display that localizes diagnostic ROIs, and reports on margin status by detecting overlap between lesions and non-epidermal tissue margins. Conclusions Our AI model, developed in collaboration with dermatopathologists, detects 5 skin lesion types with higher sensitivity than previously published AI models, and provides end users with information such as subtyping, localization, and margin status in a front-end digital display. Our end-to-end system has the potential to improve pathology workflows by increasing diagnostic accuracy, expediting the course of patient care, and ultimately improving patient outcomes.
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Affiliation(s)
- James Requa
- Pathology Watch, 497 West 4800 South, Suite 201, Murray, UT 84123, USA
| | - Tuatini Godard
- Pathology Watch, 497 West 4800 South, Suite 201, Murray, UT 84123, USA
| | - Rajni Mandal
- Pathology Watch, 497 West 4800 South, Suite 201, Murray, UT 84123, USA
| | - Bonnie Balzer
- Cedars-Sinai Medical Center, 8700 Beverly Blvd, Los Angeles, CA 90048, USA
| | - Darren Whittemore
- Pathology Watch, 497 West 4800 South, Suite 201, Murray, UT 84123, USA
| | - Eva George
- Pathology Watch, 497 West 4800 South, Suite 201, Murray, UT 84123, USA
| | | | - Chalette Lambert
- Kirk Kerkorian School of Medicine at UNLV, University of Nevada, Las Vegas, Mail Stop: 3070, 2040 W Charleston Blvd., Las Vegas, NV 89102-2244, USA
| | - Jonathan Lee
- Bethesda Dermatopathology Laboratory, 1730 Elton Road, Silver Spring, MD 20903, USA
| | - Allison Lambert
- Pathology Watch, 497 West 4800 South, Suite 201, Murray, UT 84123, USA
| | - April Larson
- Pathology Watch, 497 West 4800 South, Suite 201, Murray, UT 84123, USA
| | - Gregory Osmond
- Intermountain Healthcare, Saint George Regional Hospital, Department of Pathology, 1380 East Medical Center Drive, Saint George, Utah 84790, USA,Corresponding author.
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Daneshjou R, Barata C, Betz-Stablein B, Celebi ME, Codella N, Combalia M, Guitera P, Gutman D, Halpern A, Helba B, Kittler H, Kose K, Liopyris K, Malvehy J, Seog HS, Soyer HP, Tkaczyk ER, Tschandl P, Rotemberg V. Checklist for Evaluation of Image-Based Artificial Intelligence Reports in Dermatology: CLEAR Derm Consensus Guidelines From the International Skin Imaging Collaboration Artificial Intelligence Working Group. JAMA Dermatol 2022; 158:90-96. [PMID: 34851366 PMCID: PMC9845064 DOI: 10.1001/jamadermatol.2021.4915] [Citation(s) in RCA: 65] [Impact Index Per Article: 32.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/19/2023]
Abstract
IMPORTANCE The use of artificial intelligence (AI) is accelerating in all aspects of medicine and has the potential to transform clinical care and dermatology workflows. However, to develop image-based algorithms for dermatology applications, comprehensive criteria establishing development and performance evaluation standards are required to ensure product fairness, reliability, and safety. OBJECTIVE To consolidate limited existing literature with expert opinion to guide developers and reviewers of dermatology AI. EVIDENCE REVIEW In this consensus statement, the 19 members of the International Skin Imaging Collaboration AI working group volunteered to provide a consensus statement. A systematic PubMed search was performed of English-language articles published between December 1, 2008, and August 24, 2021, for "artificial intelligence" and "reporting guidelines," as well as other pertinent studies identified by the expert panel. Factors that were viewed as critical to AI development and performance evaluation were included and underwent 2 rounds of electronic discussion to achieve consensus. FINDINGS A checklist of items was developed that outlines best practices of image-based AI development and assessment in dermatology. CONCLUSIONS AND RELEVANCE Clinically effective AI needs to be fair, reliable, and safe; this checklist of best practices will help both developers and reviewers achieve this goal.
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Affiliation(s)
- Roxana Daneshjou
- Stanford Department of Dermatology, Stanford School of Medicine, Redwood City, CA, USA,Stanford Department of Biomedical Data Science, Stanford School of Medicine, Stanford, CA, USA
| | - Catarina Barata
- Institute for Systems and Robotics, Instituto Superior Tecnico, Lisboa, Portugal
| | - Brigid Betz-Stablein
- The University of Queensland Diamantina Institute, The University of Queensland, Dermatology Research Centre, Brisbane, Australia
| | - M. Emre Celebi
- Department of Computer Science and Engineering, University of Central Arkansas, Conway, Arkansas, USA
| | | | - Marc Combalia
- Melanoma Unit, Dermatology Department, Hospital Cĺınic Barcelona, Universitat de Barcelona, IDIBAPS, Barcelona, Spain
| | - Pascale Guitera
- Melanoma Institute Australia, the University of Sydney, Camperdown, Australia,Sydney Melanoma Diagnostic Centre, Royal Prince Alfred Hospital, Camperdown, Australia
| | - David Gutman
- Department of Biomedical Informatics, Emory University School of Medicine, Atlanta, GA, USA
| | - Allan Halpern
- Dermatology Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | | | - Harald Kittler
- Department of Dermatology, Medical University of Vienna, Vienna, Austria
| | - Kivanc Kose
- Dermatology Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | | | - Josep Malvehy
- Melanoma Unit, Dermatology Department, Hospital Cĺınic Barcelona, Universitat de Barcelona, IDIBAPS, Barcelona, Spain
| | - Han Seung Seog
- Department of Dermatology, I Dermatology Clinic, Seoul, Korea.,IDerma, Inc., Seoul, Korea
| | - H. Peter Soyer
- The University of Queensland Diamantina Institute, The University of Queensland, Dermatology Research Centre, Brisbane, Australia
| | - Eric R Tkaczyk
- Dermatology Service and Research Service, Tennessee Valley Healthcare System, Department of Veterans Affairs, Nashville TN, USA,Vanderbilt Dermatology Translational Research Clinic, Department of Dermatology, Vanderbilt University Medical Center, Nashville TN, USA,Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA
| | - Philipp Tschandl
- Department of Dermatology, Medical University of Vienna, Vienna, Austria
| | - Veronica Rotemberg
- Dermatology Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA
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9
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Katz I, O’Brien B, Clark S, Thompson CT, Schapiro B, Azzi A, Lilleyman A, Boyle T, Espartero LJL, Yamada M, Prow TW. Assessment of a Diagnostic Classification System for Management of Lesions to Exclude Melanoma. JAMA Netw Open 2021; 4:e2134614. [PMID: 34889949 PMCID: PMC8665368 DOI: 10.1001/jamanetworkopen.2021.34614] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/15/2021] [Accepted: 09/07/2021] [Indexed: 12/18/2022] Open
Abstract
Importance The proposed MOLEM (Management of Lesion to Exclude Melanoma) schema is more clinically relevant than Melanocytic Pathology Assessment Tool and Hierarchy for Diagnosis (MATH-Dx) for the management classification of melanocytic and nonmelanocytic lesions excised to exclude melanoma. A more standardized way of establishing diagnostic criteria will be crucial in the training of artificial intelligence (AI) algorithms. Objective To examine pathologists' variability, reliability, and confidence in reporting melanocytic and nonmelanocytic lesions excised to exclude melanoma using the MOLEM schema in a population of higher-risk patients. Design, Setting, and Participants This cohort study enrolled higher-risk patients referred to a primary care skin clinic in New South Wales, Australia, between April 2019 and December 2019. Baseline demographic characteristics including age, sex, and related clinical details (eg, history of melanoma) were collected. Patients with lesions suspicious for melanoma assessed by a primary care physician underwent clinical evaluation, dermoscopy imaging, and subsequent excision biopsy of the suspected lesion(s). A total of 217 lesions removed and prepared by conventional histologic method and stained with hematoxylin-eosin were reviewed by up to 9 independent pathologists for diagnosis using the MOLEM reporting schema. Pathologists evaluating for MOLEM schema were masked to the original histopathologic diagnosis. Main Outcomes and Measures Characteristics of the lesions were described and the concordance of cases per MOLEM class was assessed. Interrater agreement and the agreement between pathologists' ratings and the majority MOLEM diagnosis were calculated by Gwet AC1 with quadratic weighting applied. The diagnostic confidence of pathologists was then assessed. Results A total of 197 patients were included in the study (102 [51.8%] male; 95 [48.2%] female); mean (SD) age was 64.2 (15.8) years (range, 24-93 years). Overall, 217 index lesions were assessed with a total of 1516 histological diagnoses. Of 1516 diagnoses, 677 (44.7%) were classified as MOLEM class I; 120 (7.9%) as MOLEM class II; 564 (37.2%) as MOLEM class III; 114 (7.5%) as MOLEM class IV; and 55 (3.6%) as MOLEM class V. Concordance rates per MOLEM class were 88.6% (class I), 50.8% (class II), 76.2% (class III), 77.2% (class IV), and 74.2% (class V). The quadratic weighted interrater agreement was 91.3%, with a Gwet AC1 coefficient of 0.76 (95% CI, 0.72-0.81). The quadratic weighted agreement between pathologists' ratings and majority MOLEM was 94.7%, with a Gwet AC1 coefficient of 0.86 (95% CI, 0.84-0.88). The confidence in diagnosis data showed a relatively high level of confidence (between 1.0 and 1.5) when diagnosing classes I (mean [SD], 1.3 [0.3]), IV (1.3 [0.3]) and V (1.1 [0.1]); while classes II (1.8 [0.2]) and III (1.5 [0.4]) were diagnosed with a lower level of pathologist confidence (≥1.5). The quadratic weighted interrater confidence rating agreement was 95.2%, with a Gwet AC1 coefficient of 0.92 (95% CI, 0.90-0.94) for the 1314 confidence ratings collected. The confidence agreement for each MOLEM class was 95.0% (class I), 93.5% (class II), 95.3% (class III), 96.5% (class IV), and 97.5% (class V). Conclusions and Relevance The proposed MOLEM schema better reflects clinical practice than the MPATH-Dx schema in lesions excised to exclude melanoma by combining diagnoses with similar prognostic outcomes for melanocytic and nonmelanocytic lesions into standardized classification categories. Pathologists' level of confidence appeared to follow the MOLEM schema diagnostic concordance trend, ie, atypical naevi and melanoma in situ diagnoses were the least agreed upon and the most challenging for pathologists to confidently diagnose.
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Affiliation(s)
- Ian Katz
- Southern Sun Pathology, Sydney, New South Wales, Australia
- University of Queensland, Brisbane, Queensland, Australia
| | - Blake O’Brien
- Sullivan Nicolaides Pathology, Brisbane, Queensland, Australia
| | - Simon Clark
- Douglass Hanly Moir Pathology, Sydney, New South Wales, Australia
| | | | | | - Anthony Azzi
- Newcastle Skin Check, Charlestown, New South Wales, Australia
| | | | - Terry Boyle
- Allied Health and Human Performance, University of South Australia, Adelaide, South Australia, Australia
| | - Lore Jane L. Espartero
- Future Industries Institute, University of South Australia, Adelaide, South Australia, Australia
| | - Miko Yamada
- Future Industries Institute, University of South Australia, Adelaide, South Australia, Australia
| | - Tarl W. Prow
- Future Industries Institute, University of South Australia, Adelaide, South Australia, Australia
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10
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Massone C, Hofman-Wellenhof R, Chiodi S, Sola S. Dermoscopic Criteria, Histopathological Correlates and Genetic Findings of Thin Melanoma on Non-Volar Skin. Genes (Basel) 2021; 12:1288. [PMID: 34440462 PMCID: PMC8391530 DOI: 10.3390/genes12081288] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2021] [Revised: 08/19/2021] [Accepted: 08/19/2021] [Indexed: 11/23/2022] Open
Abstract
Dermoscopy is a non-invasive, in vivo technique that allows the visualization of subsurface skin structures in the epidermis, at the dermoepidermal junction, and in the upper dermis. Dermoscopy brought a new dimension in evaluating melanocytic skin neoplasms (MSN) also representing a link between clinical and pathologic examination of any MSN. However, histopathology remains the gold standard in diagnosing MSN. Dermoscopic-pathologic correlation enhances the level of quality of MSN diagnosis and increases the level of confidence of pathologists. Melanoma is one of the most genetically predisposed among all cancers in humans. The genetic landscape of melanoma has been described in the last years but is still a field in continuous evolution. Melanoma genetic markers play a role not only in melanoma susceptibility, initiation, and progression but also in prognosis and therapeutic decisions. Several studies described the dermoscopic specific criteria and predictors for melanoma and their histopathologic correlates, but only a few studies investigated the correlation among dermoscopy, pathology, and genetic of MSN. The aim of this work is to review the published data about dermoscopic features of melanoma, their histopathological correlates with regards also to genetic alterations. Particularly, this review will focus on low-CSD (cumulative sun damage) melanoma or superficial spreading melanoma, high-CSD melanoma, and nevus-associated melanoma.
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Affiliation(s)
| | | | | | - Simona Sola
- Surgical Pathology, Galliera Hospital, 16128 Genoa, Italy;
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11
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Pigmented Lesion Assay for Suspected Melanoma Lesions: A Health Technology Assessment. ONTARIO HEALTH TECHNOLOGY ASSESSMENT SERIES 2021; 21:1-81. [PMID: 34188732 PMCID: PMC8196402] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
BACKGROUND Early detection of melanoma is key, as survival rates are substantially better when the cancer is detected in its early stages. Currently, the standard of care is to biopsy any lesion suspected of melanoma for diagnostic confirmation by histopathology. As a result, most people who undergo biopsy receive negative melanoma results. If effective, a non-invasive alternative, such as pigmented lesion assay, could minimize the number of unnecessary biopsies performed. We conducted a health technology assessment of pigmented lesion assay for people with suspected melanoma lesions, which included an evaluation of diagnostic accuracy, clinical utility, the budget impact of publicly funding pigmented lesion assay, and the preferences and values of people who have undergone biopsy for suspected melanoma. METHODS We performed a systematic literature search of the clinical evidence. We assessed the risk of bias of each included study using the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) and the Risk of Bias Assessment Tool for Non-randomized Studies (RoBANS). We assessed the quality of the body of evidence according to the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) Working Group criteria. We performed a systematic literature search of the economic evidence. We also analyzed the budget impact of publicly funding pigmented lesion assay in adults with suspected melanoma in Ontario. To contextualize the potential value of pigmented lesion assay, we spoke with people who had undergone skin biopsy for melanoma. We also used the qualitative research synthesis from a report by the Canadian Agency for Drugs and Technologies in Health to provide context for the preferences and values of those with suspected melanoma. RESULTS We included seven studies in the clinical evidence review. Pigmented lesion assay has a sensitivity of 79% (95% confidence interval [CI] 58%-93%) and a specificity of 80% (95% CI 73%-85%; GRADE: Low). We found one published cost-effectiveness study with potentially serious limitations. Therefore, the cost-effectiveness of pigmented lesion assay compared with the standard care pathway is currently uncertain. Assuming a very low uptake, we estimated that the budget impact of publicly funding pigmented lesion assay in Ontario over the next 5 years is about $3.44 million if the test is used exclusively by primary care providers, or about $2.56 million if it is used exclusively by specialists. The people with whom we spoke who had experienced biopsy for suspected melanoma responded positively to the potential benefits of pigmented lesion assay, emphasizing its ease-of-use, potential increase in early detection of melanoma, and reduction in physical and emotional burden of unnecessary biopsies. Participants also felt that the accuracy of this tool was essential to ensure minimal false negatives. CONCLUSIONS There is uncertainty because of the low-quality evidence for the diagnostic accuracy of pigmented lesion assay. The cost-effectiveness of pigmented lesion assay compared with standard care is also uncertain. We estimated that publicly funding pigmented lesion assay in Ontario over the next 5 years would result in additional costs of $3.44 million (if used exclusively by primary care providers) or $2.56 million (if used exclusively by specialists). For people who had experienced biopsy for suspected melanoma, it was felt that pigmented lesion assay could represent an effective tool to increase early detection and avoid unnecessary biopsies, if the tool was accurate.
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12
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Kuruoglu D, Weissler JM, Bustos SS, Moran SL, Davis DMR, Bite U, Mardini S, Baum CL, Otley CC, Brewer JD, Lehman JS, Sharaf B. A 28-year single institution experience with primary skin malignancies in the pediatric population. J Plast Surg Hand Surg 2021; 56:53-57. [PMID: 34032193 DOI: 10.1080/2000656x.2021.1914639] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
Abstract
The aim of this study is to report our institution's experience with pediatric skin malignancies. A single institution retrospective review of pediatric patients with a primary skin malignancy from 1992 to 2020 was performed. Demographics, tumor characteristics and treatment outcomes were reviewed. Ninety-nine patients with 109 primary malignant skin lesions were reviewed. The most common lesion was malignant melanoma [MM] (n = 50, 45.9%). Compared to non-melanoma skin cancer (NMSC), MM were more likely to present on trunk or extremities (p=.01, OR = 3.2), and be misdiagnosed (p=.03, OR = 2.7). NMSC were more common in the head and neck region (p=.01, OR = 3.2), and were associated with a personal history of skin cancer (p=.0005, OR = 17.1) or a known risk factor (p=.04, OR = 2.5). Patients with MM were 12.4-times more likely to develop metastatic disease compared to NMSC (p<.0001). Increased Breslow's thickness also increased the odds of developing metastatic disease (p=.03, OR = 1.6 per 1-mm increase). Interval time between lesion recognition and diagnostic biopsy or surgical treatment did not impact overall survival. Malignant melanoma was the most common malignancy in our cohort, followed by basal cell carcinoma. Malignant melanoma was the most likely tumor to be misdiagnosed and/or metastasize. Treatment delays did not impact risk of metastasis, recurrence or survival rate, though some patients succumbed to disease. These results may be attributed to small sample size or the biology of melanoma in pediatric patients. Awareness of skin malignancies in the pediatric population is imperative to providers and the public, with low threshold for specialty consultation and excision when warranted.
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Affiliation(s)
- Doga Kuruoglu
- Division of Plastic Surgery, Mayo Clinic, Rochester, MN, USA
| | | | - Samyd S Bustos
- Division of Plastic Surgery, Mayo Clinic, Rochester, MN, USA
| | - Steven L Moran
- Division of Plastic Surgery, Mayo Clinic, Rochester, MN, USA
| | - Dawn M R Davis
- Department of Dermatology, Mayo Clinic, Rochester, MN, USA.,Department of Pediatrics, Mayo Clinic, Rochester, MN, USA
| | - Uldis Bite
- Division of Plastic Surgery, Mayo Clinic, Rochester, MN, USA
| | - Samir Mardini
- Division of Plastic Surgery, Mayo Clinic, Rochester, MN, USA
| | | | - Clark C Otley
- Department of Dermatology, Mayo Clinic, Rochester, MN, USA
| | - Jerry D Brewer
- Department of Dermatology, Mayo Clinic, Rochester, MN, USA
| | - Julia S Lehman
- Department of Dermatology, Mayo Clinic, Rochester, MN, USA.,Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
| | - Basel Sharaf
- Division of Plastic Surgery, Mayo Clinic, Rochester, MN, USA
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13
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Deacon DC, Smith EA, Judson-Torres RL. Molecular Biomarkers for Melanoma Screening, Diagnosis and Prognosis: Current State and Future Prospects. Front Med (Lausanne) 2021; 8:642380. [PMID: 33937286 PMCID: PMC8085270 DOI: 10.3389/fmed.2021.642380] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2020] [Accepted: 03/17/2021] [Indexed: 12/22/2022] Open
Abstract
Despite significant progress in the development of treatment options, melanoma remains a leading cause of death due to skin cancer. Advances in our understanding of the genetic, transcriptomic, and morphologic spectrum of benign and malignant melanocytic neoplasia have enabled the field to propose biomarkers with potential diagnostic, prognostic, and predictive value. While these proposed biomarkers have the potential to improve clinical decision making at multiple critical intervention points, most remain unvalidated. Clinical validation of even the most commonly assessed biomarkers will require substantial resources, including limited clinical specimens. It is therefore important to consider the properties that constitute a relevant and clinically-useful biomarker-based test prior to engaging in large validation studies. In this review article we adapt an established framework for determining minimally-useful biomarker test characteristics, and apply this framework to a discussion of currently used and proposed biomarkers designed to aid melanoma detection, staging, prognosis, and choice of treatment.
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Affiliation(s)
- Dekker C. Deacon
- Department of Dermatology, University of Utah, Salt Lake City, UT, United States
| | - Eric A. Smith
- Department of Pathology, University of Utah, Salt Lake City, UT, United States
| | - Robert L. Judson-Torres
- Department of Dermatology, University of Utah, Salt Lake City, UT, United States
- Huntsman Cancer Institute, Salt Lake City, UT, United States
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14
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Van Herck Y, Antoranz A, Andhari MD, Milli G, Bechter O, De Smet F, Bosisio FM. Multiplexed Immunohistochemistry and Digital Pathology as the Foundation for Next-Generation Pathology in Melanoma: Methodological Comparison and Future Clinical Applications. Front Oncol 2021; 11:636681. [PMID: 33854972 PMCID: PMC8040928 DOI: 10.3389/fonc.2021.636681] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2020] [Accepted: 03/12/2021] [Indexed: 12/14/2022] Open
Abstract
The state-of-the-art for melanoma treatment has recently witnessed an enormous revolution, evolving from a chemotherapeutic, "one-drug-for-all" approach, to a tailored molecular- and immunological-based approach with the potential to make personalized therapy a reality. Nevertheless, methods still have to improve a lot before these can reliably characterize all the tumoral features that make each patient unique. While the clinical introduction of next-generation sequencing has made it possible to match mutational profiles to specific targeted therapies, improving response rates to immunotherapy will similarly require a deep understanding of the immune microenvironment and the specific contribution of each component in a patient-specific way. Recent advancements in artificial intelligence and single-cell profiling of resected tumor samples are paving the way for this challenging task. In this review, we provide an overview of the state-of-the-art in artificial intelligence and multiplexed immunohistochemistry in pathology, and how these bear the potential to improve diagnostics and therapy matching in melanoma. A major asset of in-situ single-cell profiling methods is that these preserve the spatial distribution of the cells in the tissue, allowing researchers to not only determine the cellular composition of the tumoral microenvironment, but also study tissue sociology, making inferences about specific cell-cell interactions and visualizing distinctive cellular architectures - all features that have an impact on anti-tumoral response rates. Despite the many advantages, the introduction of these approaches requires the digitization of tissue slides and the development of standardized analysis pipelines which pose substantial challenges that need to be addressed before these can enter clinical routine.
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Affiliation(s)
| | - Asier Antoranz
- Laboratory for Translational Cell and Tissue Research, Department of Imaging and Pathology, KU Leuven, Leuven, Belgium
| | - Madhavi Dipak Andhari
- Laboratory for Translational Cell and Tissue Research, Department of Imaging and Pathology, KU Leuven, Leuven, Belgium
| | - Giorgia Milli
- Laboratory for Translational Cell and Tissue Research, Department of Imaging and Pathology, KU Leuven, Leuven, Belgium
| | | | - Frederik De Smet
- Laboratory for Precision Cancer Medicine, Translational Cell and Tissue Research Unit, Department of Imaging and Pathology, KU Leuven, Leuven, Belgium
| | - Francesca Maria Bosisio
- Laboratory for Translational Cell and Tissue Research, Department of Imaging and Pathology, KU Leuven, Leuven, Belgium
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15
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Zito Marino F, Brunelli M, Rossi G, Calabrese G, Caliò A, Nardiello P, Martignoni G, Squire JA, Cheng L, Massi D, Franco R. Multitarget fluorescence in situ hybridization diagnostic applications in solid and hematological tumors. Expert Rev Mol Diagn 2021; 21:161-173. [PMID: 33593207 DOI: 10.1080/14737159.2021.1887733] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Introduction: Multitarget FISH (mFISH) is a technique allowing for simultaneous detection of multiple targets sequences on the same slide through the choice of spectrally distinct fluorophore labels. The mFISH could represent a useful tool in the field of precision oncology.Areas covered: This review discusses the potential applications of mFISH technology in the molecular diagnosis of different solid and hematological tumors, including non-small cell lung cancers, melanomas, renal cell carcinomas, bladder carcinomas, germ cell tumors, and multiple myeloma, as commonly required in the clinical practice.Expert Opinion: In this emerging era of the tailored therapies and newer histo-molecular classifications, there are increasing numbers of predictive and diagnostic biomarkers required for effective clinical care. The mFISH approach may have several applications in the common clinical practice, improving the molecular diagnosis in terms of time, cost and preservation of biomaterial for tumors with a limited amount of tumor available. The mFISH provides several advantages compared to other high-throughput technologies; however, it requires high level of expertise required to interpret complex results.
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Affiliation(s)
- Federica Zito Marino
- Department of Mental and Physic Health and Preventive Medicine, Pathology Unit, University of Campania Luigi Vanvitelli, Napoli, Italy
| | - Matteo Brunelli
- Department of Pathology, University of Verona, Verona, Italy
| | - Giulio Rossi
- Pathology Unit, Ospedale Santa Maria Delle Croci, Ravenna, Italy
| | | | - Anna Caliò
- Department of Pathology, University of Verona, Verona, Italy
| | - Pamela Nardiello
- Section of Pathology, Department of Health Sciences, University of Florence Florence, Italy
| | - Guido Martignoni
- Pathology Unit, Department of Pathology and Diagnostics, University and Hospital Trust of Verona, Verona, Italy
| | - Jeremy A Squire
- Departments of Genetics, University of Sao Paulo, Ribeirão Preto, Brazil
| | - Liang Cheng
- Department of Pathology and Laboratory Medicine, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Daniela Massi
- Section of Pathology, Department of Health Sciences, University of Florence Florence, Italy
| | - Renato Franco
- Department of Mental and Physic Health and Preventive Medicine, Pathology Unit, University of Campania Luigi Vanvitelli, Napoli, Italy
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16
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Ronen S, Al-Rohil RN, Keiser E, Jour G, Nagarajan P, Tetzlaff MT, Curry JL, Ivan D, Middleton LP, Torres-Cabala CA, Gershenwald JE, Aung PP, Prieto VG. Discordance in Diagnosis of Melanocytic Lesions and Its Impact on Clinical Management. Arch Pathol Lab Med 2021; 145:1505-1515. [PMID: 33577643 DOI: 10.5858/arpa.2020-0620-oa] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/04/2020] [Indexed: 11/06/2022]
Abstract
CONTEXT.— Accurate diagnosis of melanocytic lesions is fundamental for appropriate clinical management. OBJECTIVE.— To evaluate the degree of discordance, if any, between histopathologic diagnoses of melanocytic lesions at referring institutions and at a tertiary referral cancer center and the potential impact of such discordance on clinical management. DESIGN.— We retrospectively identified all patients referred to our comprehensive cancer center for evaluation of a melanocytic lesion from January 2010 to January 2011. For each patient, the histopathologic diagnosis from the referring institution was compared with the histopathologic diagnosis from a dermatopathologist at our center. Discordances were classified as major if they resulted in a change in clinical management and minor if they did not. RESULTS.— A total of 1521 cases were included. The concordance rates were 72.2% (52 of 72) for dysplastic nevus, 75.0% (15 of 20) for all other types of nevi, 91.1% (143 of 157) for melanoma in situ, 96.1% (758 of 789) for invasive melanoma, and 99.6% (478 of 480) for metastatic melanoma. Major discordances were found in 20.2% of cases (307 of 1521), and minor discordances were found in 48.8% of cases (742 of 1521). Compared with the guideline-based treatment recommendation based on the referring-institution diagnosis, the guideline-based treatment recommendation based on the cancer center diagnosis was more extensive in 5.9% (89 of 1521) of patients and less extensive in 5.0% (76 of 1521) of patients. CONCLUSIONS.— Our findings underscore the importance of secondary histopathologic review of melanocytic lesions by expert dermatopathologists because significant changes in the diagnosis, tumor classification, and/or staging may be identified; thus, resulting in critical changes in recommendations for clinical management.
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Affiliation(s)
- Shira Ronen
- From the Departments of Pathology (Ronen, Al-Rohil, Keiser, Jour, Nagarajan, Tetzlaff, Curry, Ivan, Middleton, Torres-Cabala, Aung, Prieto).,Ronen, Al-Rohil, and Keiser contributed equally to this work.,Ronen's current affiliation is the Department of Pathology, Cleveland Clinic Foundation, Cleveland, Ohio
| | - Rami N Al-Rohil
- From the Departments of Pathology (Ronen, Al-Rohil, Keiser, Jour, Nagarajan, Tetzlaff, Curry, Ivan, Middleton, Torres-Cabala, Aung, Prieto).,Ronen, Al-Rohil, and Keiser contributed equally to this work.,Al-Rohil's current affiliation is the Department of Pathology, Duke University Hospital, Durham, North Carolina
| | - Elizabeth Keiser
- From the Departments of Pathology (Ronen, Al-Rohil, Keiser, Jour, Nagarajan, Tetzlaff, Curry, Ivan, Middleton, Torres-Cabala, Aung, Prieto).,Ronen, Al-Rohil, and Keiser contributed equally to this work
| | - George Jour
- From the Departments of Pathology (Ronen, Al-Rohil, Keiser, Jour, Nagarajan, Tetzlaff, Curry, Ivan, Middleton, Torres-Cabala, Aung, Prieto).,Jour's current affiliation is the Department of Pathology, New York University, New York City
| | - Priyadharsini Nagarajan
- From the Departments of Pathology (Ronen, Al-Rohil, Keiser, Jour, Nagarajan, Tetzlaff, Curry, Ivan, Middleton, Torres-Cabala, Aung, Prieto)
| | - Michael T Tetzlaff
- From the Departments of Pathology (Ronen, Al-Rohil, Keiser, Jour, Nagarajan, Tetzlaff, Curry, Ivan, Middleton, Torres-Cabala, Aung, Prieto)
| | - Jonathan L Curry
- From the Departments of Pathology (Ronen, Al-Rohil, Keiser, Jour, Nagarajan, Tetzlaff, Curry, Ivan, Middleton, Torres-Cabala, Aung, Prieto)
| | - Doina Ivan
- From the Departments of Pathology (Ronen, Al-Rohil, Keiser, Jour, Nagarajan, Tetzlaff, Curry, Ivan, Middleton, Torres-Cabala, Aung, Prieto)
| | - Lavinia P Middleton
- From the Departments of Pathology (Ronen, Al-Rohil, Keiser, Jour, Nagarajan, Tetzlaff, Curry, Ivan, Middleton, Torres-Cabala, Aung, Prieto)
| | - Carlos A Torres-Cabala
- From the Departments of Pathology (Ronen, Al-Rohil, Keiser, Jour, Nagarajan, Tetzlaff, Curry, Ivan, Middleton, Torres-Cabala, Aung, Prieto)
| | - Jeffrey E Gershenwald
- Surgical Oncology and Cancer Biology (Gershenwald), The University of Texas MD Anderson Cancer Center, Houston
| | - Phyu P Aung
- From the Departments of Pathology (Ronen, Al-Rohil, Keiser, Jour, Nagarajan, Tetzlaff, Curry, Ivan, Middleton, Torres-Cabala, Aung, Prieto).,Aung and Prieto contributed equally to this work
| | - Victor G Prieto
- From the Departments of Pathology (Ronen, Al-Rohil, Keiser, Jour, Nagarajan, Tetzlaff, Curry, Ivan, Middleton, Torres-Cabala, Aung, Prieto).,Aung and Prieto contributed equally to this work
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17
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Lohman ME, Grekin RC, North JP, Neuhaus IM. Impact of second-opinion dermatopathology reviews on surgical management of malignant neoplasms. J Am Acad Dermatol 2021; 84:1385-1392. [PMID: 33333152 DOI: 10.1016/j.jaad.2020.12.022] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2020] [Revised: 11/30/2020] [Accepted: 12/08/2020] [Indexed: 11/28/2022]
Abstract
BACKGROUND Second-opinion review is linked to error reduction and treatment changes in anatomic pathology. OBJECTIVE We sought to establish the rate of diagnostic discrepancy identified by second-opinion dermatopathologic review and the effect on surgical treatment. METHODS Cases referred for treatment of a malignant neoplasm diagnosed by an outside pathologist were reviewed. The external and internal second-opinion dermatopathologic reports were compared. Discordance in diagnosis, subtype, and treatment change owing to second-opinion review was recorded. The referring pathologist's level of dermatopathologic training was also documented. RESULTS A total of 358 cases were included. Dermatopathologic second-opinion diagnosis was discordant with the outside diagnosis in 37 of 358 cases (10.3%). In 32 of 358 cases (8.9%), second-opinion review resulted in a change in treatment, with 28 of 32 (87.5%) of these changes resulting in cancelled surgery. Dermatologists without dermatopathologic fellowship training had the highest rate of discordant diagnoses compared with pathologists and dermatopathologists. LIMITATIONS This was a retrospective study at a tertiary care facility. CONCLUSION Second-opinion dermatopathologic review is associated with identification of discordant diagnoses and a substantial influence on treatment, with both cancellation of surgery and augmented management. Secondary pathologic review should be considered in high-volume surgical practices.
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Affiliation(s)
- Mary E Lohman
- Department of Dermatology, University of California-San Francisco, San Francisco, California
| | - Roy C Grekin
- Department of Dermatology, University of California-San Francisco, San Francisco, California
| | - Jeffrey P North
- Department of Dermatology, University of California-San Francisco, San Francisco, California
| | - Isaac M Neuhaus
- Department of Dermatology, University of California-San Francisco, San Francisco, California.
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18
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Reply to the letter to the editor: ‘Deep learning outperformed 11 pathologists in the classification of histopathological melanoma images’. Eur J Cancer 2020; 130:262-264. [DOI: 10.1016/j.ejca.2019.12.024] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2019] [Accepted: 12/21/2019] [Indexed: 11/21/2022]
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19
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Géraud C, Griewank KG. Re: Deep learning outperformed 11 pathologists in the classification of histopathological melanoma images. Eur J Cancer 2020; 130:259-261. [PMID: 31668521 DOI: 10.1016/j.ejca.2019.09.018] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2019] [Accepted: 09/10/2019] [Indexed: 11/15/2022]
Affiliation(s)
- Cyrill Géraud
- Department of Dermatology, Venereology and Allergology, University Medical Center and Medical Faculty Mannheim, Heidelberg, Mannheim, Germany; Section of Clinical and Molecular Dermatology, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany; European Center for Angioscience, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany.
| | - Klaus G Griewank
- Department of Dermatology, University Hospital Essen, West German Cancer Center, University Duisburg-Essen and the German Cancer Consortium (DKTK), Essen, Germany; Dermatopathologie bei Mainz, Nieder-Olm, Germany.
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20
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Beatson M, Eleryan MG, Reserva J, Kaufman B, Connelly B, Dugan EM, Radfar A, Lucey P, Harvell J, Bhawan J, Jang S, Venna S. Importance of pathology review to complement clinical management of melanoma. J Am Acad Dermatol 2020; 83:1784-1786. [PMID: 32268167 DOI: 10.1016/j.jaad.2020.03.093] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2019] [Revised: 03/10/2020] [Accepted: 03/30/2020] [Indexed: 11/26/2022]
Affiliation(s)
- Meghan Beatson
- Department of Medicine, Memorial Sloan Kettering Cancer Center, New York City, NY.
| | - Misty G Eleryan
- George Washington University School of Medicine, Washington, DC
| | | | | | - Bridget Connelly
- Georgetown University Department of Mathematics and Statistics, Washington, DC
| | - Elizabeth M Dugan
- Department of Dermatology, Georgetown University School of Medicine, Washington, DC
| | | | - Patricia Lucey
- Inova Schar Cancer Institute Melanoma Center, Fairfax, Virginia
| | - Jeff Harvell
- Inova Schar Cancer Institute Melanoma Center, Fairfax, Virginia
| | - Jag Bhawan
- Department of Dermatology, Boston University School of Medicine, Massachusetts
| | - Sekwon Jang
- Inova Schar Cancer Institute Melanoma Center, Fairfax, Virginia
| | - Suraj Venna
- Inova Schar Cancer Institute Melanoma Center, Fairfax, Virginia
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21
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Torres R, Lang UE, Hejna M, Shelton SJ, Joseph NM, Shain AH, Yeh I, Wei ML, Oldham MC, Bastian BC, Judson-Torres RL. MicroRNA Ratios Distinguish Melanomas from Nevi. J Invest Dermatol 2020; 140:164-173.e7. [PMID: 31580842 PMCID: PMC6926155 DOI: 10.1016/j.jid.2019.06.126] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2019] [Revised: 05/27/2019] [Accepted: 06/04/2019] [Indexed: 12/27/2022]
Abstract
The use of microRNAs as biomarkers has been proposed for many diseases, including the diagnosis of melanoma. Although hundreds of microRNAs have been identified as differentially expressed in melanomas as compared to benign melanocytic lesions, a limited consensus has been achieved across studies, constraining the effective use of these potentially useful markers. In this study, we applied a machine learning-based pipeline to a dataset consisting of genetic features, clinical features, and next-generation microRNA sequencing from micro-dissected formalin-fixed paraffin embedded melanomas and their adjacent benign precursor nevi. We identified patient age and tumor cellularity as variables that frequently confound the measured expression of potentially diagnostic microRNAs. By employing the ratios of microRNAs that were either enriched or depleted in melanoma compared to the nevi as a normalization strategy, we developed a model that classified all the available published cohorts with an area under the receiver operating characteristic curve of 0.98. External validation on an independent cohort classified lesions with 81% sensitivity and 88% specificity and was uninfluenced by the tumor content of the sample or patient age.
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Affiliation(s)
- Rodrigo Torres
- Department of Dermatology, University of California, San Francisco, California, USA
| | - Ursula E Lang
- Department of Dermatology, University of California, San Francisco, California, USA; Department of Pathology, University of California, San Francisco, California, USA
| | - Miroslav Hejna
- Department of Physics, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA; Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA
| | - Samuel J Shelton
- Department of Neurological Surgery, University of California, San Francisco, California, USA
| | - Nancy M Joseph
- Department of Pathology, University of California, San Francisco, California, USA
| | - A Hunter Shain
- Department of Dermatology, University of California, San Francisco, California, USA
| | - Iwei Yeh
- Department of Dermatology, University of California, San Francisco, California, USA; Department of Pathology, University of California, San Francisco, California, USA
| | - Maria L Wei
- Department of Dermatology, University of California, San Francisco, California, USA; San Francisco Veterans Affairs Medical Center, San Francisco, California, USA
| | - Michael C Oldham
- Department of Neurological Surgery, University of California, San Francisco, California, USA
| | - Boris C Bastian
- Department of Dermatology, University of California, San Francisco, California, USA; Department of Pathology, University of California, San Francisco, California, USA
| | - Robert L Judson-Torres
- Department of Dermatology, University of California, San Francisco, California, USA; Huntsman Cancer Institute, University of Utah, Salt Lake City, Utah, USA; Department of Dermatology, University of Utah School of Medicine, Salt Lake City, Utah, USA.
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22
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Piepkorn MW, Longton GM, Reisch LM, Elder DE, Pepe MS, Kerr KF, Tosteson ANA, Nelson HD, Knezevich S, Radick A, Shucard H, Onega T, Carney PA, Elmore JG, Barnhill RL. Assessment of Second-Opinion Strategies for Diagnoses of Cutaneous Melanocytic Lesions. JAMA Netw Open 2019; 2:e1912597. [PMID: 31603483 PMCID: PMC6804025 DOI: 10.1001/jamanetworkopen.2019.12597] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/22/2019] [Accepted: 08/15/2019] [Indexed: 11/14/2022] Open
Abstract
Importance Histopathologic criteria have limited diagnostic reliability for a range of cutaneous melanocytic lesions. Objective To evaluate the association of second-opinion strategies by general pathologists and dermatopathologists with the overall reliability of diagnosis of difficult melanocytic lesions. Design, Setting, and Participants This diagnostic study used samples from the Melanoma Pathology Study, which comprises 240 melanocytic lesion samples selected from a dermatopathology laboratory in Bellevue, Washington, and represents the full spectrum of lesions from common nevi to invasive melanoma. Five sets of 48 samples were evaluated independently by 187 US pathologists from July 15, 2013, through May 23, 2016. Data analysis was performed from April 2016 through November 2017. Main Outcomes and Measures Accuracy of diagnosis, defined as concordance with an expert consensus diagnosis of 3 experienced pathologists, was assessed after applying 10 different second-opinion strategies. Results Among the 187 US pathologists examining the 24 lesion samples, 113 were general pathologists (65 men [57.5%]; mean age at survey, 53.7 years [range, 33.0-79.0 years]) and 74 were dermatopathologists (49 men [66.2%]; mean age at survey, 46.4 years [range, 33.0-77.0 years]). Among the 8976 initial case interpretations, physicians desired second opinions for 3899 (43.4%), most often for interpretation of severely dysplastic nevi. The overall misclassification rate was highest when interpretations did not include second opinions and initial reviewers were all general pathologists lacking subspecialty training (52.8%; 95% CI, 51.3%-54.3%). When considering different second opinion strategies, the misclassification of melanocytic lesions was lowest when the first, second, and third consulting reviewers were subspecialty-trained dermatopathologists and when all lesions were subject to second opinions (36.7%; 95% CI, 33.1%-40.7%). When the second opinion strategies were compared with single interpretations without second opinions, the reductions in misclassification rates for some of the strategies were statistically significant, but none of the strategies eliminated diagnostic misclassification. Melanocytic lesions in the middle of the diagnostic spectrum had the highest misclassification rates (eg, moderately or severely dysplastic nevus, Spitz nevus, melanoma in situ, and pathologic stage [p]T1a invasive melanoma). Variability of in situ and thin invasive melanoma was relatively intractable to all examined strategies. Conclusions and Relevance The results of this study suggest that second opinions rendered by dermatopathologists improve reliability of melanocytic lesion diagnosis. However, discordance among pathologists remained high.
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Affiliation(s)
| | - Gary M. Longton
- Program in Biostatistics and Biomathematics, Fred Hutchinson Cancer Research Center, Seattle, Washington
| | - Lisa M. Reisch
- Department of Biostatistics, University of Washington, Seattle
| | - David E. Elder
- Department of Pathology and Laboratory Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia
| | - Margaret S. Pepe
- Program in Biostatistics and Biomathematics, Fred Hutchinson Cancer Research Center, Seattle, Washington
| | | | - Anna N. A. Tosteson
- Department of Medicine, Geisel School of Medicine at Dartmouth, Hanover, New Hampshire
- Department of Community and Family Medicine, Geisel School of Medicine at Dartmouth, Hanover, New Hampshire
- The Dartmouth Institute, Geisel School of Medicine at Dartmouth, Hanover, New Hampshire
| | - Heidi D. Nelson
- Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University, Portland
- Department of Medicine, Oregon Health & Science University, Portland
| | | | - Andrea Radick
- Department of Biostatistics, University of Washington, Seattle
| | - Hannah Shucard
- Department of Biostatistics, University of Washington, Seattle
| | - Tracy Onega
- Department of Epidemiology, Norris Cotton Cancer Center, Geisel School of Medicine at Dartmouth, Hanover, New Hampshire
- Department of Biomedical Data Science, Norris Cotton Cancer Center, Geisel School of Medicine at Dartmouth, Hanover, New Hampshire
| | - Patricia A. Carney
- Department of Family Medicine and of Public Health and Preventive Medicine, Oregon Health and Science University, Portland
| | - Joann G. Elmore
- Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles
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23
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Mancera N, Smalley KSM, Margo CE. Melanoma of the eyelid and periocular skin: Histopathologic classification and molecular pathology. Surv Ophthalmol 2019; 64:272-288. [PMID: 30578807 DOI: 10.1016/j.survophthal.2018.12.002] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2018] [Revised: 12/12/2018] [Accepted: 12/12/2018] [Indexed: 12/29/2022]
Abstract
Cutaneous melanoma, a potentially lethal malignancy of the periocular skin, represents only a small proportion of the roughly 87,000 new cases of cutaneous melanoma diagnosed annually in the United States. Most of our understanding of melanoma of the eyelid skin is extrapolated from studies of cutaneous melanoma located elsewhere. Recent years have witnessed major breakthroughs in molecular biology and genomics of cutaneous melanoma, some of which have led to the development of targeted therapies. The molecular insights have also kindled interest in rethinking how cutaneous melanomas are classified and assessed for risk. We provide a synopsis of the epidemiology, histopathologic classification, and clinical experience of eyelid melanoma since 1990 and then review major advances in the molecular biology of cutaneous melanoma, exploring how this impacts our understanding of classification and predicting risk.
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Affiliation(s)
- Norberto Mancera
- Department of Ophthalmology, Morsani College of Medicine, University of South Florida, Tampa, Florida, USA.
| | - Keiran S M Smalley
- Departments of Tumor Biology, The Moffitt Cancer Center & Research Institute, Tampa, Florida, USA; Cutaneous Oncology The Moffitt Cancer Center & Research Institute, Tampa, Florida, USA
| | - Curtis E Margo
- Department of Ophthalmology, Morsani College of Medicine, University of South Florida, Tampa, Florida, USA; Department of Pathology and Cell Biology, Morsani College of Medicine, University of South Florida, Tampa, Florida, USA
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