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. 2016 Sep 15;22(18):4664-75.
doi: 10.1158/1078-0432.CCR-16-0316. Epub 2016 Apr 8.

A Prospective Evaluation of Early Detection Biomarkers for Ovarian Cancer in the European EPIC Cohort

Affiliations

A Prospective Evaluation of Early Detection Biomarkers for Ovarian Cancer in the European EPIC Cohort

Kathryn L Terry et al. Clin Cancer Res. .

Abstract

Purpose: About 60% of ovarian cancers are diagnosed at late stage, when 5-year survival is less than 30% in contrast to 90% for local disease. This has prompted search for early detection biomarkers. For initial testing, specimens taken months or years before ovarian cancer diagnosis are the best source of information to evaluate early detection biomarkers. Here we evaluate the most promising ovarian cancer screening biomarkers in prospectively collected samples from the European Prospective Investigation into Cancer and Nutrition study.

Experimental design: We measured CA125, HE4, CA72.4, and CA15.3 in 810 invasive epithelial ovarian cancer cases and 1,939 controls. We calculated the sensitivity at 95% and 98% specificity as well as area under the receiver operator curve (C-statistic) for each marker individually and in combination. In addition, we evaluated marker performance by stage at diagnosis and time between blood draw and diagnosis.

Results: We observed the best discrimination between cases and controls within 6 months of diagnosis for CA125 (C-statistic = 0.92), then HE4 (0.84), CA72.4 (0.77), and CA15.3 (0.73). Marker performance declined with longer time between blood draw and diagnosis and for earlier staged disease. However, assessment of discriminatory ability at early stage was limited by small numbers. Combinations of markers performed modestly, but significantly better than any single marker.

Conclusions: CA125 remains the single best marker for the early detection of invasive epithelial ovarian cancer, but can be slightly improved by combining with other markers. Identifying novel markers for ovarian cancer will require studies including larger numbers of early-stage cases. Clin Cancer Res; 22(18); 4664-75. ©2016 AACRSee related commentary by Skates, p. 4542.

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Figures

Figure 1
Figure 1
Locally estimated scatterplot smoothing (Loess) curves over time prior to diagnosis. The blue line represents controls, the green line stage I cases, the yellow line stage II cases, and the red line stage III/IV cases. For CA125 and CA15.3 data are shown only for lag-times between blood donation and cancer diagnosis up to 6 years.
Figure 2
Figure 2
ROC curves and C-statistics for diagnosis ≤6 months, ≤12 months, 1-2 years and 2-3 years after blood collection

References

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