Serial Patterns of Ovarian Cancer Biomarkers in a Prediagnosis Longitudinal Dataset

Early detection of ovarian cancer through screening may have impact on mortality from the disease. Approaches based on CA125 cut-off have not been effective. Longitudinal algorithms such as the Risk of Ovarian Cancer Algorithm (ROCA) to interpret CA125 have been shown to have higher sensitivity and specificity than a single cut-off. The aim of this study was to investigate whether other ovarian cancer-related biomarkers, Human Epididymis 4 (HE4), glycodelin, mesothelin, matrix metalloproteinase 7 (MMP7), and cytokeratin 19 fragment (CYFRA 21-1), could improve the performance of CA125 in detecting ovarian cancer earlier. Serum samples (single and serial) predating diagnosis from 47 women taking part in the UK Collaborative Trial of Ovarian Cancer Screening (UKCTOCS) who went on to develop primary invasive ovarian, fallopian tube, or peritoneal cancer (index cancer) (170 samples) and 179 matched controls (893 samples) were included in the study. A multiplex immunobased assay platform (Becton Dickinson) allowing simultaneous measurement of the six serum markers was used. The area under the ROC curve for the panel of three biomarkers (CA125, HE4, and glycodelin) was higher than for CA125 alone for all analysed time groups, indicating that these markers can improve on sensitivity of CA125 alone for ovarian cancer detection.