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Am J Surg Pathol. 2008 Jan;32(1):128-38.

Distinction of primary and metastatic mucinous tumors involving the ovary: analysis of size and laterality data by primary site with reevaluation of an algorithm for tumor classification.

Author information

1
Department of Pathology , The Johns Hopkins University School of Medicine and Hospital, Baltimore, MD 21231, USA.

Abstract

Distinction of primary ovarian mucinous tumors from metastatic/secondary mucinous tumors involving the ovaries is often challenging, not only at the time of intraoperative assessment when requested for surgical management (staging decisions) but also for final pathologic diagnosis. Previous studies have shown that a simple algorithm using tumor size and laterality (bilateral tumors of any size, or unilateral tumor <10 cm=metastatic; unilateral tumor > or =10 cm=primary) can accurately classify a substantial majority of tumors. To assess the general utility of this algorithm for distinction of primary and secondary mucinous tumors in the ovary and address the occurrence of exceptions (large unilateral metastases), analysis of tumor size and laterality data was performed using 194 tumors (52 primary tumors and 142 metastases), with metastases subclassified by primary site [colorectum (46), appendix (28 low-grade tumors, 20 carcinomas), pancreaticobiliary tract (20), small intestine (3), stomach (5), and endocervix (20)]. Performance of the algorithm was evaluated using the originally proposed method and modified size criteria were analyzed to optimize tumor classification. The original algorithm correctly classified 84% of tumors overall, including 100% of primary ovarian tumors and 77% of all metastases (colorectal: 74%; appendiceal: 79% of low-grade tumors, 100% of carcinomas; pancreaticobiliary: 95%; small intestinal: 33%; gastric: 80%; endocervical: 55%). By adjusting the size criterion to 12 cm, performance of the algorithm was both maintained for primary ovarian tumors and improved for metastases, with correct classification of 86% of tumors overall, including 100% of primary tumors and 80% of metastases. Performance was optimized at 13 cm, with correct classification of 87% of tumors overall, including 98% of primary tumors and 82% of metastases (colorectal: 80%; appendiceal: 79% of low-grade tumors, 100% of carcinomas; pancreaticobiliary: 100%; small intestinal: 33%; gastric: 100%; endocervical: 70%). Of the more common metastases, metastatic colorectal and endocervical carcinomas provided the greatest number of exceptions, even when analyzed with the optimized size criterion. Recognition that metastatic colorectal carcinomas represent the most common metastases and have a greater tendency to violate the algorithm should prompt lowering of the threshold for suggesting the possibility of metastatic colorectal carcinoma for tumors displaying any microscopic features suggestive of that diagnosis, even when a history of primary colorectal carcinoma is lacking. Use of the algorithm is intended as an adjunct to the complete clinicopathologic evaluation that ideally should occur when problematic mucinous tumors in the ovary are encountered.

PMID:
18162780
DOI:
10.1097/PAS.0b013e3180690d2d
[Indexed for MEDLINE]

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