A novel algorithm for better distinction of primary mucinous ovarian carcinomas and mucinous carcinomas metastatic to the ovary

• DOI: 10.1007/s00428-018-2504-0
• Publication Date: 2019-01-10T03:54:52Z
• Authors: Michiel Simons; Thomas Bolhuis; Anton F. De Haan; Annette H. Bruggink; Johan Bulten; Leon F. Massuger; Iris D. Nagtegaal
• Keywords: Histology; Nomogram

Primary mucinous ovarian carcinomas (MOC) are notoriously difficult to distinguish from metastatic the ovary (mMC). Studies performed on small cohorts reported algorithms based tumor size and laterality aid in distinguishing MOC mMC. We evaluated improved these by performing a large-scale, nationwide search Dutch Pathology Registry. All registered pathology reports fulfilling our criteria concerning Netherlands 2000 2011 were collected. Age, histology, laterality, extracted. An existing database covering same timeline containing tumors was used, extracting all mMC, age, size, primary location. Existing applied cohort. Subsequently, an algorithm nomogram age created for differentiating identified 735 1018 Patients with significantly younger larger more often unilateral than Signet ring cell rarely primary. Our used signet bilaterality, integrating patient diagnose Sensitivity specificity mMC 90.1% 59.0%, respectively. Applying cohort yielded far lower sensitivity. The described here using has higher sensitivity but compared earlier aids indicating origin, conclusive diagnosis, careful integration of morphology, immunohistochemistry, clinical imaging data is recommended.