4.5 Article

Diagnosis of Serous Tubal Intraepithelial Carcinoma Based on Morphologic and Immunohistochemical Features: A Reproducibility Study

Journal

AMERICAN JOURNAL OF SURGICAL PATHOLOGY
Volume 35, Issue 12, Pages 1766-1775

Publisher

LIPPINCOTT WILLIAMS & WILKINS
DOI: 10.1097/PAS.0b013e31822f58bc

Keywords

serous tubular intraepithelial carcinoma (STIC); reproducibility; ovarian cancer

Funding

  1. Department of Defense [OC100517]
  2. KO7 Preventive Oncology Award [KO7Ca111948]

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There is compelling evidence that serous tubal intraepithelial carcinoma (STIC) is a precursor of high-grade serous ovarian carcinoma. Large-scale studies are now required to determine its biological significance and clinical implication. Before conducting these studies, a reproducible classification for STIC is needed, and that is the goal of this study. This study involved 6 gynecologic pathologists from 4 academic institutions and 3 independent rounds of review. In round 1, sixty-seven lesions ranging from normal, atypical, to STICs were classified by 5 pathologists on the basis of predetermined morphologic criteria. Interobserver agreement for the diagnosis of STIC versus not STIC was fair [kappa = 0.39; 95% confidence interval (CI) 0.26, 0.52], and intraobserver reproducibility ranged from fair to moderate on the basis of percentage agreement and k. Round 2 involved testing revised criteria that incorporated morphology and immunohistochemistry (IHC) for p53 protein expression and Ki-67 labeling in 10 sets by 3 of the pathologists. The result was an improvement in interobserver agreement for the classification of STIC (kappa = 0.62; 95% CI 0.18, 1.00). An algorithm was then created combining morphology and IHC for p53 and Ki-67, and reproducibility was assessed as part of round 3. In 37 lesions reviewed by 6 pathologists, substantial agreement for STIC versus no STIC was observed (kappa = 0.73; 95% CI 0.58, 0.86). In conclusion, we have developed reproducible criteria for the diagnosis of STIC that incorporate morphologic and IHC markers for p53 and Ki-67. The algorithm we propose is expected to help standardize the classification of STIC for future studies.

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