Investigator

Sophia Apostolidou

University College London

SASophia Apostolidou
Papers(2)
Estimating the Opport…Improving Specificity…
Collaborators(10)
Usha MenonAleksandra Gentry-Mah…Troy B. HawkinsAndy RyanAnthony D. CouvillonBrendan J. ManningDawn R. MattoonEmily S. Winn-DeenJane LangeJason Xu
Institutions(5)
Mrc Clinical Trials U…University College Lo…Mercy BioAnalytics, I…Oregon Health & Scien…Duke University

Papers

Estimating the Opportunity for Early Detection of Ovarian Cancer Using Individual-Patient Data from a Large Randomized Controlled Trial

Abstract Background: The UK Collaborative Trial of Ovarian Cancer Screening did not detect a reduction in ovarian cancer mortality with either multimodal screening (MMS) or transvaginal ultrasound screening (USS) compared with no screening. The trial data provide an invaluable resource to quantify the opportunity for interception in ovarian cancer. Methods: We used Bayesian inference to estimate ovarian cancer natural history based on individual screening and cancer diagnosis records from the UK Collaborative Trial of Ovarian Cancer Screening, a randomized controlled ovarian cancer screening trial conducted in England, Wales, and Northern Ireland. The trial included 202,638 women ages 50 to 74 years with no family history of ovarian cancer, randomized in a 1:1:2 ratio to annual MMS (serum CA125 interpreted using the risk of ovarian cancer algorithm), annual USS, or no screening. The current analysis included 199,499 women, with 674,806 screens and 2,025 cancer diagnoses. Results: Among high-grade serous cancers (HGSC), the estimated preclinical detectable phase was 1.7 years (95% credible interval, 1.3–2.2), compared with 7.8 years (95% credible interval, 5.7–10.6) for non-HGSCs. The preclinical detectable phase depended on screening modality: for HGSCs, it was longer in the MMS arm (2.2 years) compared with the USS arm (0.8 years), whereas for non-HGSCs, it was shorter in the MMS arm (2.7 years) compared with the USS arm (8.2 years). Conclusions: The interception opportunity for ovarian cancer strongly depends on histologic subtype and screening modality. Impact: Achieving a clinically significant benefit of ovarian cancer early detection will require prolonging the interception window through judicious combination of first- and second-line tests.

Improving Specificity for Ovarian Cancer Screening Using a Novel Extracellular Vesicle–Based Blood Test

The low incidence of ovarian cancer (OC) dictates that any screening strategy needs to be both highly sensitive and highly specific. This study explored the utility of detecting multiple colocalized proteins or glycosylation epitopes on single tumor-associated extracellular vesicles from blood. The novel Mercy Halo Ovarian Cancer Test (OC Test) uses immunoaffinity capture of tumor-associated extracellular vesicles, followed by proximity-ligation real-time quantitative PCR to detect combinations of up to three biomarkers to maximize specificity, and measures multiple combinations to maximize sensitivity. A high-grade serous carcinoma (HGSC) case-control training set of EDTA plasma samples from 397 women was used to lock down the test design, the data interpretation algorithm, and the cutoff between cancer and noncancer. Performance was verified and compared with cancer antigen 125 in an independent blinded case-control set of serum samples from 390 women (132 controls, 66 HGSC, 83 non-HGSC OC, and 109 benign). In the verification study, the OC Test showed a specificity of 97.0% (128/132; 95% CI, 92.4%-99.6%), a HGSC sensitivity of 97.0% (64/66; 95% CI, 87.8%-99.2%), and an area under the curve of 0.97 (95% CI, 0.93-0.99) and detected 73.5% (61/83; 95% CI, 62.7%-82.6%) of the non-HGSC OC cases. This test exhibited fewer false positives in subjects with benign ovarian tumors, nonovarian cancers, and inflammatory conditions when compared with cancer antigen 125. The combined sensitivity and specificity of this new test suggests that it may have potential in OC screening.

103Works
2Papers
21Collaborators
Ovarian NeoplasmsEarly Detection of Cancer

Positions

Researcher

University College London