Literature DB >> 31930502

Risk of specific types of ovarian cancer after borderline ovarian tumors in Denmark: A nationwide study.

Charlotte G Hannibal1, Kirsten Frederiksen2, Russell Vang3,4, Robert J Kurman3,4,5, Susanne K Kjaer1,6.   

Abstract

Population-based evidence regarding risk of ovarian cancer after a borderline ovarian tumor (BOT) is sparse. We aimed to examine the incidence of specific types of ovarian cancer in women with serous or mucinous BOTs in a nationwide cohort study with up to 36 years of follow-up. Using the nationwide Danish Pathology Data Bank, we identified 4,281 women with a BOT (2,058 serous BOTs and 2,223 mucinous BOTs) in Denmark during 1978-2012. We computed standardized incidence ratios (SIRs) to compare the incidence of ovarian cancer among women with BOTs compared to general population rates. We found that a serous BOT was especially and strongly associated with subsequent serous ovarian cancer (SIR = 9.2; 95% CI: 6.8-12.2), and that a mucinous BOT was strongly related to mucinous ovarian cancer (SIR = 18.6; 95% CI: 10.8-29.8). The SIRs remained elevated ≥10 years after a serous BOT and up to 5-9 years after a mucinous BOT. The increased incidence of serous ovarian cancer in women with a serous BOT was mostly pronounced in women <50 years at the serous BOT diagnosis. In conclusion, women with a serous BOT experience long-term increased incidence of serous ovarian cancer, and women with a mucinous BOT have long-term elevated incidence of mucinous ovarian cancer compared to the general population. This is the first population-based study to show compelling evidence of the histo-specific increased risk of ovarian cancer following specific types of BOTs. Thus, these results are supportive of the hypothesis that BOTs may be precursor lesions to carcinomas of the corresponding histologic type.
© 2020 UICC.

Entities:  

Keywords:  borderline ovarian tumors; cohort study; nationwide; ovarian cancer risk; specific types of tumor; standardized incidence ratios

Mesh:

Year:  2020        PMID: 31930502     DOI: 10.1002/ijc.32864

Source DB:  PubMed          Journal:  Int J Cancer        ISSN: 0020-7136            Impact factor:   7.396


  2 in total

1.  Digital Pathology-based Study of Cell- and Tissue-level Morphologic Features in Serous Borderline Ovarian Tumor and High-grade Serous Ovarian Cancer.

Authors:  Jun Jiang; Burak Tekin; Ruifeng Guo; Hongfang Liu; Yajue Huang; Chen Wang
Journal:  J Pathol Inform       Date:  2021-06-05

2.  T2-weighted MRI-based radiomics for discriminating between benign and borderline epithelial ovarian tumors: a multicenter study.

Authors:  Mingxiang Wei; Yu Zhang; Genji Bai; Cong Ding; Haimin Xu; Yao Dai; Shuangqing Chen; Hong Wang
Journal:  Insights Imaging       Date:  2022-08-09
  2 in total

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