Validation of a deep neural network-based algorithm supporting clinical management of adnexal mass

Abstract

BackgroundConservative management of adnexal mass is warranted when there is imaging-based and clinical evidence of benign characteristics. Malignancy risk is, however, a concern due to the mortality rate of ovarian cancer. Malignancy occurs in 10–15% of adnexal masses that go to surgery, whereas the rate of malignancy is much lower in masses clinically characterized as benign or indeterminate. Additional diagnostic tests could assist conservative management of these patients. Here we report the clinical validation of OvaWatch, a multivariate index assay, with real-world evidence of performance that supports conservative management of adnexal masses.MethodsOvaWatch utilizes a previously characterized neural network-based algorithm combining serum biomarkers and clinical covariates and was used to examine malignancy risk in prospective and retrospective samples of patients with an adnexal mass. Retrospective data sets were assembled from previous studies using patients who had adnexal mass and were scheduled for surgery. The prospective study was a multi-center trial of women with adnexal mass as identified on clinical examination and indeterminate or asymptomatic by imaging. The performance to detect ovarian malignancy was evaluated at a previously validated score threshold.ResultsIn retrospective, low prevalence (N = 1,453, 1.5% malignancy rate) data from patients that received an independent physician assessment of benign, OvaWatch has a sensitivity of 81.8% [95% confidence interval (CI) 65.1–92.7] for identifying a histologically confirmed malignancy, and a negative predictive value (NPV) of 99.7%. OvaWatch identified 18/22 malignancies missed by physician assessment. A prospective data set had 501 patients where 106 patients with adnexal mass went for surgery. The prevalence was 2% (10 malignancies). The sensitivity of OvaWatch for malignancy was 40% (95% CI: 16.8–68.7%), and the specificity was 87% (95% CI: 83.7–89.7) when patients were included in the analysis who did not go to surgery and were evaluated as benign. The NPV remained 98.6% (95% CI: 97.0–99.4%). An independent analysis set with a high prevalence (45.8%) the NPV value was 87.8% (95% CI: 95% CI: 75.8–94.3%).ConclusionOvaWatch demonstrated high NPV across diverse data sets and promises utility as an effective diagnostic test supporting management of suspected benign or indeterminate mass to safely decrease or delay unnecessary surgeries.

Ovarian Cancer surgical consideration is markedly improved by the neural network powered-MIA3G multivariate index assay

“…We calculated the MIA3G score for each qualified patient as previously described ( 28 , 29 ). The validated MIA3G stratified the malignancy risk of a suspicious adnexal mass, based on an “at risk” score from 0 to 10, into the LP (MIA3G <5.0) or IND (MIA3G ≥ 5.0) category, with negative predictive value >99% ( 28 ).…”

“…All data and samples were obtained from enrolled participants for the clinical study (14–2023) and in the independent prospective study, (RP 04–2019, RP 05–2019, RP 08–2020) ( 29 ), which were carried out according to the Institutional Review Board-reviewed protocols.…”

“…The study protocol directed follow-up visits consistent with the standard of care, with blood draws during the visits. Blood was drawn and batch-tested asynchronously for individual biomarkers, and the MIA3G test score was calculated ( 28 , 29 ). The physicians had no access to MIA3G results in this study cohort.…”

“…MIA3G is a proprietary deep feed-forward neural network-based algorithm, and the development has been described previously ( 28 , 29 ). MIA3G utilizes the clinical features of age, menopausal status, and seven biomarkers in the algorithm, which are CA125, HE4, beta-2 microglobulin, apolipoprotein A-1, transferrin, prealbumin, and follicle-stimulating hormone, to calculate the score to assess malignancy potential of adnexal masses.…”

“…MIA3G utilizes the clinical features of age, menopausal status, and seven biomarkers in the algorithm, which are CA125, HE4, beta-2 microglobulin, apolipoprotein A-1, transferrin, prealbumin, and follicle-stimulating hormone, to calculate the score to assess malignancy potential of adnexal masses. MIA3G outcomes are indicated as low probability of malignancy (LP) or indeterminate (IND) based on whether the MIA3G score is below or above the validated threshold, respectively ( 29 ).…”