Accelerating type‐specific ovarian carcinoma research: Calculator for Ovarian Subtype Prediction (COSP) is a reliable high‐throughput tool for case review. Issue 5 (2nd September 2013)

• Record Type: Journal Article
• Authors: Kommoss, Stefan; Gilks, Cyril Blake; Kommoss, Friedrich; Chow, Christine; Hilpert, Felix; du Bois, Andreas; Köbel, Martin; Huntsman, David G; Anglesio, Michael; Kalloger, Steve E; Pfisterer, Jacobus
• Is Part Of: Histopathology. Volume 63:Issue 5(2014)
• Page Start: 704
• Page End: 712
• Publication Date: 2013-09-02
• Subjects: Histology, Pathological -- Periodicals; 611.018
• DOI: 10.1111/his.12219
• Languages: English
• ISSNs: 0309-0167

Abstract

<abstract abstract-type="main" id="his12219-abs-0001"> <title> <x xml:space="preserve">Abstract</x> </title> <sec id="his12219-sec-0001" sec-type="section"> <title>Aims</title> <p>The recent recognition that ovarian carcinoma is composed of five distinct disease entities has served to increase the value of accurate histotyping. Reliable identification of histotypes is essential for the success of studies testing novel therapies, as well as for biomarker discovery research. The aim of this study was to examine the utility of a nine‐marker immunohistochemical (IHC) panel, designated the Calculator for Ovarian Subtype Prediction (COSP), to reliably reproduce the consensus diagnosis of two expert gynaecological pathologists.</p> </sec> <sec id="his12219-sec-0002" sec-type="section"> <title>Methods and results</title> <p>A total of 423 cases from the AGO‐OVAR11 trial were evaluated using the COSP IHC panel, and compared to original diagnoses from >100 local contributing pathologists and independent expert gynaecopathology review. The overall concordance between COSP and expert review was 89%; in cases where a local pathologist's diagnosis was confirmed by COSP, the expert gynaecopathologist also agreed in 97.5% of cases.</p> </sec> <sec id="his12219-sec-0003" sec-type="section"> <title>Conclusions</title> <p>The incorporation of COSP into a high‐throughput diagnostic review algorithm will decrease the need for expert review by identifying a small number of difficult cases that truly require expert review. This modification will serve to increase the efficiency of the diagnostic review process, which will probably serve to reduce operational costs and expedite translational studies on ovarian carcinoma.</p> </sec> </abstract>