Prospective Validation of a Standardized Ultrasonography-Based Ovarian Cancer Risk Assessment System

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Abstract

OBJECTIVE:

To evaluate the performance of a system that standardizes ovarian cancer risk assessment and reporting on ultrasonography.

METHODS:

We conducted a prospective community-based cohort study of average-risk women undergoing ultrasonography in 2016 using a reporting system that requires adnexal masses to be categorized as 1, 2, 3, or X based on standardized ultrasound criteria including size, presence of solid components, and vascularity assessed by Doppler. With a median follow-up of 18 months, the risk of ovarian cancer or borderline tumor diagnosis for each category was determined.

RESULTS:

Among 43,606 women undergoing ultrasonography, 6,838 (16%) had an abnormal adnexal mass reported: 70% were category 1, 21% category 2, 3.7% category 3, and 5.4% category X. Among these women, 89 (1.3%) were subsequently diagnosed with ovarian cancer and 59 (0.9%) with borderline tumors. The risks of ovarian cancer diagnosis associated with masses reported as categories 1, 2, 3, and X were 0.2% (95% CI 0.05–0.3%), 1.3% (95% CI 0.7–1.9%), 6.0% (95% CI 3.0–8.9%), and 13.0% (95% CI 9.5–16.4%), respectively; risks of either ovarian cancer or borderline tumor were 0.4% (95% CI 0.2–0.6%), 2.3% (95% CI 1.6–3.1%), 10.4% (95% CI 6.6–14.1%), and 18.9% (95% CI 14.9–23.0%) respectively. Among 36,768 (84%) women with normal or benign adnexal findings reported, 38 women were diagnosed with ovarian cancer, for a risk of 0.1% (95% CI 0.07–0.14%).

CONCLUSION:

In a community-based setting with low ovarian cancer prevalence, our standardized reporting system differentiated adnexal masses into four categories with distinct levels of risk with 9–10% of women having higher risk masses and 70% of women having masses associated with a risk of cancer similar to that of normal ultrasound findings. The system supports risk-based management by providing clinicians a more consistent assessment of risk based on ultrasound characteristics.

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