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Validation of an Algorithm for the Diagnosis of Serous Tubal Intraepithelial Carcinoma

Vang, Russell M.D.; Visvanathan, Kala M.B.B.S., F.R.A.C.P., M.H.S.; Gross, Amy M.H.S.; Maambo, Emily M.D.; Gupta, Mamta M.B.B.S.; Kuhn, Elisabetta M.D.; Li, Rose Fanghong M.D.; Ronnett, Brigitte M. M.D.; Seidman, Jeffrey D. M.D.; Yemelyanova, Anna M.D.; Shih, Ie-Ming M.D., Ph.D.; Shaw, Patricia A. M.D.; Soslow, Robert A. M.D.; Kurman, Robert J. M.D

International Journal of Gynecological Pathology: May 2012 - Volume 31 - Issue 3 - p 243–253
doi: 10.1097/PGP.0b013e31823b8831

It has been reported that the diagnosis of serous tubal intraepithelial carcinoma (STIC) is not optimally reproducible on the basis of only histologic assessment. Recently, we reported that the use of a diagnostic algorithm that combines histologic features and coordinate immunohistochemical expression of p53 and Ki-67 substantially improves reproducibility of the diagnosis. The goal of the current study was to validate this algorithm by testing a group of 6 gynecologic pathologists who had not participated in the development of the algorithm (3 faculty and 3 fellows) but who were trained in its use by referring to a website designed for the purpose. They then reviewed a set of microscopic slides, which contained 41 mucosal lesions of the fallopian tube. Overall consensus (≥4 of 6 pathologists) for the 4 categories of STIC, serous tubal intraepithelial lesion (our atypical intermediate category), p53 signature, and normal/reactive was achieved in 76% of the lesions, with no consensus in 24%. Combining diagnoses into 2 categories (STIC versus non-STIC) resulted in an overall consensus of 93% and no consensus in 7%. The κ value for STIC versus non-STIC among all 6 observers was also high at 0.67 and did not significantly differ, whether for faculty (κ=0.66) or fellows (κ=0.60). These findings confirm the reproducibility of this algorithm by a group of gynecologic pathologists who were trained on a website for that purpose. Accordingly, we recommend its use in research studies. Before applying it to routine clinical practice, the algorithm should be evaluated by general surgical pathologists in a community setting.

Departments of Pathology, Division of Gynecologic Pathology (R.V., E.M., M.G., E.K., R.F.L., B.M.R., A.Y., I.-M.S., R.J.K.)

Department of Gynecology & Obstetrics (R.V., B.M.R., I.-M.S., R.J.K.)

Department of Oncology (K.V., I.-M.S., R.J.K.), The Johns Hopkins University School of Medicine

Department of Epidemiology (K.V., A.G.), The Johns Hopkins Bloomberg School of Public Health, Baltimore, MD

Department of Pathology (J.D.S.), Washington Hospital Center, Washington, DC

Department of Pathology (P.A.S.), University of Toronto, University Health Network, Toronto, Canada

Department of Pathology (R.A.S.), Memorial Sloan-Kettering Cancer Center, New York, New York

This work was funded by CDMRP Grant OC100517 from the Department of Defense.

Address correspondence and reprint requests to Russell Vang, MD, The Johns Hopkins Hospital, Department of Pathology, Division of Gynecologic Pathology, The Johns Hopkins University School of Medicine, Weinberg Bldg., Rm. 2242, 401 North Broadway, Baltimore, MD 21231. E-mail:

©2012International Society of Gynecological Pathologists