Clinical Utility of Risk Models to Refer Patients with Adnexal Masses to Specialized Oncology Care: Multicenter External Validation Using Decision Curve Analysis

Abstract

To evaluate the utility of preoperative diagnostic models for ovarian cancer based on ultrasound and/or biomarkers for referring patients to specialized oncology care. The investigated models were RMI, ROMA, and 3 models from the International Ovarian Tumor Analysis (IOTA) group [LR2, ADNEX, and the Simple Rules risk score (SRRisk)]. A secondary analysis of prospectively collected data from 2 cross-sectional cohort studies was performed to externally validate diagnostic models. A total of 2,763 patients (2,403 in dataset 1 and 360 in dataset 2) from 18 centers (11 oncology centers and 7 nononcology hospitals) in 6 countries participated. Excised tissue was histologically classified as benign or malignant. The clinical utility of the preoperative diagnostic models was assessed with net benefit (NB) at a range of risk thresholds (5%-50% risk of malignancy) to refer patients to specialized oncology care. We visualized results with decision curves and generated bootstrap confidence intervals. The prevalence of malignancy was 41% in dataset 1 and 40% in dataset 2. For thresholds up to 10% to 15%, RMI and ROMA had a lower NB than referring all patients. SRRisks and ADNEX demonstrated the highest NB. At a threshold of 20%, the NBs of ADNEX, SRrisks, and RMI were 0.348, 0.350, and 0.270, respectively. Results by menopausal status and type of center (oncology vs. nononcology) were similar. All tested IOTA methods, especially ADNEX and SRRisks, are clinically more useful than RMI and ROMA to select patients with adnexal masses for specialized oncology care. .

New nomogram predicts the recurrence of hepatocellular carcinoma in patients with negative preoperative serum AFP subjected to curative resection

“…Decision curve analysis is a method used to evaluate the clinical utility of a diagnostic test while taking into account the subjective nature of risk . In this study, we assessed the clinical application of our nomogram.…”

“…Decision curve analysis is a method used to evaluate the clinical utility of a diagnostic test while taking into account the subjective nature of risk. 25,26 In this study, we assessed the clinical application of our nomogram. The results indicated that the constructed tool presented a better net benefit with a higher threshold probability and improved performance for predicting 2-, 3-, and 5-year RFS than the BCLC stage and CLIP score in the training cohort (Figure 2A-C).…”

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

“…The TVU score, CA125, and menopausal status are combined in RMI [9,19]. In recent years HE4, approved by the US Food and Drug Administration (FDA), has been shown to be a good complement to CA125 in the differential diagnostics between benign and malignant ovarian tumors.To improve specificity for TVU a doppler ultrasound and morphology index have been tested in different models, such as logistic regression models 1 and 2 (LR1 and LR2), simple rules, the ADNEX model, and simple rules risk score from the International Ovarian Tumor Analysis (IOTA) group [20,21]. The majority of these models require considerable experience in TVU, which might not be provided in a general gynecologic setting [22].…”

Performance of Selected Models for Predicting Malignancy in Ovarian Tumors in Relation to the Degree of Diagnostic Uncertainty by Subjective Assessment With Ultrasound

“…Therefore, multiple diagnostic and predictive models, based on US, clinical variables, and cancer biomarker assessment, have been developed to better facilitate the evaluation and diagnosis of tumors. The idea behind the development of predictive models for a differential diagnosis of ovarian tumors was to enable inexperienced sonographers to undertake diagnoses . In that context, physicians who are less experienced in gynecologic US have another diagnostic tool for differentiating malignant from benign ovarian tumors at their disposal.…”

“…Most studies report that internal validation is performed at the time of the original reports. In general, the studies provide detailed characterizations of the tumors (eg, the US structure and histopathologic type); however, data are sparse about the level of diagnostic confidence in relationship to the SA of the tumor . This is of clinical importance because from a practical point of view, the predictive models should prove to have been effective when the use of SA by a nonexpert is unequivocal.…”