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Novel risk models for early detection and screening of ovarian cancer

Russell, MR; D'Amato, A; Graham, C; Crosbie, EJ; Gentry-Maharaj, A; Ryan, A; Kalsi, JK; ... Graham, RL; + view all (2017) Novel risk models for early detection and screening of ovarian cancer. Oncotarget , 8 (1) pp. 785-797. 10.18632/oncotarget.13648. Green open access

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Abstract

PURPOSE: Ovarian cancer (OC) is the most lethal gynaecological cancer. Early detection is required to improve patient survival. Risk estimation models were constructed for Type I (Model I) and Type II (Model II) OC from analysis of Protein Z, Fibronectin, C-reactive protein and CA125 levels in prospectively collected samples from the United Kingdom Collaborative Trial of Ovarian Cancer Screening (UKCTOCS). RESULTS: Model I identifies cancers earlier than CA125 alone, with a potential lead time of 3-4 years. Model II detects a number of high grade serous cancers at an earlier stage (Stage I/II) than CA125 alone, with a potential lead time of 2-3 years and assigns high risk to patients that the ROCA Algorithm classified as normal. MATERIALS AND METHODS: This nested case control study included 418 individual serum samples serially collected from 49 OC cases and 31 controls up to six years pre-diagnosis. Discriminatory logit models were built combining the ELISA results for candidate proteins with CA125 levels. CONCLUSIONS: These models have encouraging sensitivities for detecting pre-clinical ovarian cancer, demonstrating improved sensitivity compared to CA125 alone. In addition we demonstrate how the models improve on ROCA for some cases and outline their potential future use as clinical tools.

Type: Article
Title: Novel risk models for early detection and screening of ovarian cancer
Location: United States
Open access status: An open access version is available from UCL Discovery
DOI: 10.18632/oncotarget.13648
Publisher version: http://dx.doi.org/10.18632/oncotarget.13648
Language: English
Additional information: Licensed under a Creative Commons Attribution 3.0 License (http://creativecommons.org/licenses/by/3.0/).
Keywords: UKCTOCS, early detection, logit, ovarian cancer, risk estimation
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Inst of Clinical Trials and Methodology
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Inst of Clinical Trials and Methodology > MRC Clinical Trials Unit at UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Epidemiology and Health
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Epidemiology and Health > Epidemiology and Public Health
URI: https://discovery.ucl.ac.uk/id/eprint/1532748
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