title: A framework for evaluating diagnostic discordance in pathology discovered during research studies.
abstract: BACKGROUND
  Little is known about the frequency of discordant diagnoses identified during research.
  
  
  OBJECTIVE
  To describe diagnostic discordance identified during research and apply a newly designed research framework for investigating discordance.
  
  
  METHODS
  Breast biopsy cases (N = 407) from registries in Vermont and New Hampshire were independently reviewed by a breast pathology expert. The following research framework was developed to assess those cases: (1) compare the expert review and study database diagnoses, (2) determine the clinical significance of diagnostic discordance, (3) identify and correct data errors and verify the existence of true diagnostic discrepancies, (4) consider the impact of borderline cases, and (5) determine the notification approach for verified disagreements.
  
  
  RESULTS
  Initial overall discordance between the original diagnosis recorded in our research database and a breast pathology expert was 32.2% (131 of 407). This was reduced to less than 10% after following the 5-step research framework. Detailed review identified 12 cases (2.9%) with data errors (2 in the underlying pathology registry, 3 with incomplete slides sent for expert review, and 7 with data abstraction errors). After excluding the cases with data errors, 38 cases (9.6%) among the remaining 395 had clinically meaningful discordant diagnoses (κ = 0.82; SE, 0.04; 95% confidence interval, 0.76-0.87). Among these 38 cases, 20 (53%) were considered borderline between 2 diagnoses by either the original pathologist or the expert. We elected to notify the pathology registries and facilities regarding discordant diagnoses.
  
  
  CONCLUSIONS
  Understanding the types and sources of diagnostic discordance uncovered in research studies may lead to improved scientific data and better patient care.
authors: From the School of Medicine (Ms Feng), the Division of General Internal Medicine (Dr Reisch and Dr Elmore), and the Department of Anatomic Pathology (Dr Rendi), University of Washington, Seattle; the Departments of Pathology, College of Medicine, and the Vermont Cancer Center (Dr Weaver), Family Medicine and Radiology (Dr Geller), and Pathology (Dr Goodwin), University of Vermont, Burlington; the Departments of Family Medicine and Public Health & Preventive Medicine (Dr Carney) and Medical Informatics & Clinical Epidemiology and Medicine (Dr Nelson), Oregon Health and Science University, Portland; the Section of Biostatistics and Epidemiology (Dr Onega), and the Department of Community & Family Medicine (Dr Tosteson), Dartmouth College, Lebanon, New Hampshire; the Department of Pathology, Stanford University, Stanford, California (Dr Allison); Biostatistics Modeling and Methods (Mr Longton) and Biostatistics and Biomathematics (Dr Pepe), Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle.
authors: Sherry
authors: S
authors: Feng
authors: Donald L
authors: DL
authors: Weaver
authors: Patricia A
authors: PA
authors: Carney
authors: Lisa M
authors: LM
authors: Reisch
authors: Berta M
authors: BM
authors: Geller
authors: Andrew
authors: A
authors: Goodwin
authors: Mara H
authors: MH
authors: Rendi
authors: Tracy
authors: T
authors: Onega
authors: Kim H
authors: KH
authors: Allison
authors: Anna N A
authors: AN
authors: Tosteson
authors: Heidi D
authors: HD
authors: Nelson
authors: Gary
authors: G
authors: Longton
authors: Margaret
authors: M
authors: Pepe
authors: Joann G
authors: JG
authors: Elmore
mesh_terms: D000328:Adult; D000368:Aged; D001943:Breast Neoplasms / Q000175:diagnosis*; D018270:Carcinoma, Ductal, Breast / Q000175:diagnosis; D002285:Carcinoma, Intraductal, Noninfiltrating / Q000175:diagnosis; D003951:Diagnostic Errors / Q000706:statistics & numerical data*; D005104:Expert Testimony; D005260:Female; D006801:Humans; D008875:Middle Aged; D009513:New Hampshire; D010338:Pathology, Clinical / Q000706:statistics & numerical data*; D012042:Registries / Q000706:statistics & numerical data; D014707:Vermont