Increased Diagnostic Accuracy of Adnexal Tumors with A Combination of Established Algorithms and Biomarkers

Abstract

Ovarian cancer is the most lethal gynecologic cancer. Pre-diagnostic testing lacks sensitivity and specificity, and surgery is often the only way to secure the diagnosis. Exploring new biomarkers is of great importance, but the rationale of combining validated well-established biomarkers and algorithms could be a more effective way forward. We hypothesized that we can improve differential diagnostics and reduce false positives by combining (a) risk of malignancy index (RMI) with serum HE4, (b) risk of ovarian malignancy algorithm (ROMA) with a transvaginal ultrasound score or (c) adding HE4 to CA125 in a simple algorithm. With logistic regression modeling, new algorithms were explored and validated using leave-one-out cross validation. The analyses were performed in an existing cohort prospectively collected prior to surgery, 2013–2016. A total of 445 benign tumors and 135 ovarian cancers were included. All presented models improved specificity at cut-off compared to the original algorithm, and goodness of fit was significant (p < 0.001). Our findings confirm that HE4 is a marker that improves specificity without hampering sensitivity or diagnostic accuracy in adnexal tumors. We provide in this study “easy-to-use” algorithms that could aid in the triage of women to the most appropriate level of care when presenting with an unknown ovarian cyst or suspicious ovarian cancer.

Next Generation Plasma Proteomics Identifies High-Precision Biomarker Candidates for Ovarian Cancer

“…MUCIN-16 has also been reported to be elevated above the clinically indicative cut-off for ovarian cancer (35 U/mL) in 5.1% of heart failures among elderly women [ 9 ] and in 45.7% of women with acute pancreatitis [ 10 ]. Additional biomarkers such as the WAP four-disulfide core domain 2 (WFDC2 or HE4) has been shown to increase the specificity in detection of ovarian cancer, especially in fertile women [ 11 ]. A combination of MUCIN-16 and WFDC2 is used in the ovarian malignancy risk algorithm (ROMA) index, which uses two different risk score calculations and cut-offs for pre- and post-menopausal women.…”

Comprehending the Proteomic Landscape of Ovarian Cancer: A Road to the Discovery of Disease Biomarkers

“…A series of other markers have subsequently been identified from OC patient sera, including the Human epididymis protein 4 (HE4) (Uniprot ID Q14508), which is a secreted glycoprotein that is overexpressed in both serous and endometrioid OCs and thus might be useful in specific clinical scenarios [45,54,55]. In the same vein, line protein markers like EGFR, ErbB2, and osteopontin, in combination with the above-mentioned, have been reported to be of relevance in OC.…”

Toward ovarian cancer screening with protein biomarkers using dried, self-sampled cervico-vaginal fluid

“… 13 However, MUCIN-16 alone has low sensitivity for early-stage cancer partly due to a large proportion of false positives resulting from non-cancer gynecological conditions such as endometriosis, infections, or normal pregnancies. 13 Risk-scores using combinations of MUCIN-16 and other biomarkers such as the WAP four-disulfide core domain 2 (WFDC2 or HE4) used in the ROMA Score (Ovarian Malignancy Risk Algorithm), can achieve sensitivities of 90–95% 14 , 15 at a specificity of 75%. A lower sensitivity for detection of early-stage ovarian cancer (stages I and II), high costs and risk of over-treatment due to low specificity prohibits population screening using these biomarkers.…”