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Histological classification of ovarian cancer

Overview of attention for article published in Medical Molecular Morphology, March 2003
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Title
Histological classification of ovarian cancer
Published in
Medical Molecular Morphology, March 2003
DOI 10.1007/s007950300002
Pubmed ID
Authors

T. Kaku, Shinji Ogawa, Yoshiaki Kawano, Yoshihiro Ohishi, Hiroaki Kobayashi, Toshio Hirakawa, Hitoo Nakano

Abstract

The histology of ovarian tumors exhibits a wide variety of histological features. The histological classification of ovarian tumors by the World Health Organization (WHO) is based on histogenetic principles, and this classification categorizes ovarian tumors with regard to their derivation from coelomic surface epithelial cells, germ cells, and mesenchyme (the stroma and the sex cord). Epithelial ovarian tumors, which are the majority of malignant ovarian tumors, are further grouped into histological types as follows: serous, mucinous, endometrioid, clear cell, transitional cell tumors (Brenner tumors), carcinosarcoma, mixed epithelial tumor, undifferentiated carcinoma, and others. Clear cell and endometrioid carcinomas are highly associated with endometriosis. In stage distribution, serous carcinoma is found predominantly is stage III or IV. In contrast, clear cell and endometrioid carcinomas tend to remain confined to the ovary. Clear cell and endometrioid carcinomas may be unique histological types compared with serous carcinomas with respect to stage distribution and association with endometriosis.

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Mendeley readers

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Geographical breakdown

Country Count As %
Canada 2 <1%
Colombia 1 <1%
United Kingdom 1 <1%
Chile 1 <1%
Mexico 1 <1%
United States 1 <1%
Unknown 214 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 39 18%
Student > Master 31 14%
Student > Bachelor 28 13%
Student > Doctoral Student 19 9%
Researcher 16 7%
Other 38 17%
Unknown 50 23%
Readers by discipline Count As %
Medicine and Dentistry 70 32%
Agricultural and Biological Sciences 44 20%
Biochemistry, Genetics and Molecular Biology 24 11%
Engineering 7 3%
Chemistry 6 3%
Other 15 7%
Unknown 55 25%