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Population-Based Analysis of Histologically Confirmed Melanocytic Proliferations Using Natural Language Processing.
Lott, Jason P; Boudreau, Denise M; Barnhill, Ray L; Weinstock, Martin A; Knopp, Eleanor; Piepkorn, Michael W; Elder, David E; Knezevich, Steven R; Baer, Andrew; Tosteson, Anna N A; Elmore, Joann G.
Affiliation
  • Lott JP; Cornell Scott-Hill Health Center, New Haven, Connecticut.
  • Boudreau DM; Kaiser Permanente Washington Health Research Institute, Seattle.
  • Barnhill RL; Departments of Pharmacy and Epidemiology, University of Washington, Seattle.
  • Weinstock MA; Department of Pathology, Institut Curie, and Faculty of Medicine, University of Paris Descartes, Paris, France.
  • Knopp E; Departments of Dermatology and Epidemiology, Brown University, Providence, Rhode Island.
  • Piepkorn MW; Center for Dermatoepidemiology, Department of Veterans Affairs Medical Center, Providence, Rhode Island.
  • Elder DE; Department of Dermatology, Rhode Island Hospital, Providence, Rhode Island.
  • Knezevich SR; Division of Dermatology, Department of Medicine, University of Washington, Seattle.
  • Baer A; Group Health Capitol Hill Campus, Seattle, Washington.
  • Tosteson ANA; Division of Dermatology, Department of Medicine, University of Washington, Seattle.
  • Elmore JG; Dermatopathology Northwest, Bellevue, Washington.
JAMA Dermatol ; 154(1): 24-29, 2018 01 01.
Article in En | MEDLINE | ID: mdl-29094145
ABSTRACT
Importance Population-based information on the distribution of histologic diagnoses associated with skin biopsies is unknown. Electronic medical records (EMRs) enable automated extraction of pathology report data to improve our epidemiologic understanding of skin biopsy outcomes, specifically those of melanocytic origin.

Objective:

To determine population-based frequencies and distribution of histologically confirmed melanocytic lesions. Design, Setting, and

Participants:

A natural language processing (NLP)-based analysis of EMR pathology reports of adult patients who underwent skin biopsies at a large integrated health care delivery system in the US Pacific Northwest from January 1, 2007, through December 31, 2012. Exposures Skin biopsy procedure. Main Outcomes and

Measures:

The primary outcome was histopathologic diagnosis, obtained using an NLP-based system to process EMR pathology reports. We determined the percentage of diagnoses classified as melanocytic vs nonmelanocytic lesions. Diagnoses classified as melanocytic were further subclassified using the Melanocytic Pathology Assessment Tool and Hierarchy for Diagnosis (MPATH-Dx) reporting schema into the following categories class I (nevi and other benign proliferations such as mildly dysplastic lesions typically requiring no further treatment), class II (moderately dysplastic and other low-risk lesions that may merit narrow reexcision with <5-mm margins), class III (eg, melanoma in situ and other higher-risk lesions warranting reexcision with 5-mm to 1-cm margins), and class IV/V (invasive melanoma requiring wide reexcision with ≥1-cm margins and potential adjunctive therapy). Health system cancer registry data were used to define the percentage of invasive melanoma cases within MPATH-Dx class IV (stage T1a) vs V (≥stage T1b).

Results:

A total of 80 368 skin biopsies, performed on 47 529 patients, were examined. Nearly 1 in 4 skin biopsies were of melanocytic lesions (23%; n = 18 715), which were distributed according to MPATH-Dx categories as follows class I, 83.1% (n = 15 558); class II, 8.3% (n = 1548); class III, 4.5% (n = 842); class IV, 2.2% (n = 405); and class V, 1.9% (n = 362). Conclusions and Relevance Approximately one-quarter of skin biopsies resulted in diagnoses of melanocytic proliferations. These data provide the first population-based estimates across the spectrum of melanocytic lesions ranging from benign through dysplastic to malignant. These results may serve as a foundation for future research seeking to understand the epidemiology of melanocytic proliferations and optimization of skin biopsy utilization.
Subject(s)

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Skin Neoplasms / Natural Language Processing / Electronic Health Records / Melanocytes / Melanoma Type of study: Observational_studies / Prevalence_studies / Risk_factors_studies Limits: Adult / Aged / Female / Humans / Male / Middle aged Country/Region as subject: America do norte Language: En Journal: JAMA Dermatol Year: 2018 Document type: Article

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Skin Neoplasms / Natural Language Processing / Electronic Health Records / Melanocytes / Melanoma Type of study: Observational_studies / Prevalence_studies / Risk_factors_studies Limits: Adult / Aged / Female / Humans / Male / Middle aged Country/Region as subject: America do norte Language: En Journal: JAMA Dermatol Year: 2018 Document type: Article