title: Interobserver variability in diagnosing high-grade neuroendocrine carcinoma of the lung and comparing it with the morphometric analysis.
abstract: BACKGROUND
  Distinguishing small cell lung carcinoma (SCLC) and large cell neuroendocrine carcinoma (LCNEC) of the lung is difficult with little information about interobserver variability.
  
  
  METHODS
  One hundred twenty-nine cases of resected SCLC and LCNEC were independently evaluated by four pathologists and classified according to the 2004 World Health Organization criteria. Agreement was regarded as "unanimous" if all four pathologists agreed on the classification. The kappa statistic was calculated to measure the degree of agreement between pathologists. We also measured cell size using image analysis, and receiver-operating-characteristic curve analysis was performed to evaluate cell size in predicting the diagnosis of high-grade neuroendocrine (NE) carcinomas in 66 cases.
  
  
  RESULTS
  Unanimous agreement was achieved in 55.0% of 129 cases. The kappa values ranged from 0.35 to 0.81. Morphometric analysis reaffirmed that there was a continuous spectrum of cell size from SCLC to LCNEC and showed that tumors with cells falling in the middle size range were difficult to categorize and lacked unanimous agreement.
  
  
  CONCLUSIONS
  Our results provide an objective explanation for considerable interobserver variability in the diagnosis of high-grade pulmonary NE carcinomas. Further studies would need to define more stringent and objective definitions of cytologic and architectural characteristics to reliably distinguish between SCLC and LCNEC.
authors.affiliation: Department of Pathology, Gachon University Gil Hospital, Gachon University of Medicine and Science, Incheon, Korea.
authors.forename: Seung Yeon
authors.initials: SY
authors.lastname: Ha
authors.forename: Joungho
authors.initials: J
authors.lastname: Han
authors.forename: Wan-Seop
authors.initials: WS
authors.lastname: Kim
authors.forename: Byung Seong
authors.initials: BS
authors.lastname: Suh
authors.forename: Mee Sook
authors.initials: MS
authors.lastname: Roh
keywords: Image analysis; Large cell neuroendocrine carcinoma; Lung; Observer variation; Small cell lung carcinoma