TY - JOUR
T1 - Clinical utility of risk modelsto refer patients with adnexal masses to specialized oncology care
T2 - Multicenter external validation using decision curve analysis
AU - Wynants, Laure
AU - Timmerman, Dirk
AU - Verbakel, Jan Y.
AU - Testa, Antonia
AU - Savelli, Luca
AU - Fischerova, Daniela
AU - Franchi, Dorella
AU - Van Holsbeke, Caroline
AU - Epstein, Elisabeth
AU - Froyman, Wouter
AU - Guerriero, Stefano
AU - Rossi, Alberto
AU - Fruscio, Robert
AU - Leone, Francesco P.G.
AU - Bourne, Tom
AU - Valentin, Lil
AU - Van Calster, Ben
PY - 2017/9/1
Y1 - 2017/9/1
N2 - Purpose: 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)]. Experimental Design: 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. Results: 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. Conclusions: 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.
AB - Purpose: 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)]. Experimental Design: 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. Results: 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. Conclusions: 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.
KW - risk models
KW - Adnexal Masses
KW - oncology care
UR - http://www.scopus.com/inward/record.url?scp=85029542806&partnerID=8YFLogxK
U2 - 10.1158/1078-0432.CCR-16-3248
DO - 10.1158/1078-0432.CCR-16-3248
M3 - Article
C2 - 28512173
AN - SCOPUS:85029542806
SN - 1078-0432
VL - 23
SP - 5082
EP - 5090
JO - Clinical Cancer Research
JF - Clinical Cancer Research
IS - 17
ER -