TY - JOUR
T1 - Predicting the risk of malignancy in adnexal masses based on the Simple Rules from the International Ovarian Tumor Analysis group
AU - Timmerman, Dirk
AU - Van Calster, Ben
AU - Testa, Antonia
AU - Savelli, Luca
AU - Fischerova, Daniela
AU - Froyman, Wouter
AU - Wynants, Laure
AU - Van Holsbeke, Caroline
AU - Epstein, Elisabeth
AU - Franchi, Dorella
AU - Kaijser, Jeroen
AU - Czekierdowski, Artur
AU - Guerriero, Stefano
AU - Fruscio, Robert
AU - Leone, Francesco P G
AU - Rossi, Alberto
AU - Landolfo, Chiara
AU - Vergote, Ignace
AU - Bourne, Tom
AU - Valentin, Lil
PY - 2015/11/3
Y1 - 2015/11/3
N2 - Background: Accurate methods to preoperatively characterize adnexal tumors are pivotal for optimal patient management. A recent metaanalysis concluded that the International Ovarian Tumor Analysis algorithms such as the Simple Rules are the best approaches to preoperatively classify adnexal masses as benign or malignant. Objective: We sought to develop and validate a model to predict the risk of malignancy in adnexal masses using the ultrasound features in the Simple Rules. Study Design: This was an international cross-sectional cohort study involving 22 oncology centers, referral centers for ultrasonography, and general hospitals. We included consecutive patients with an adnexal tumor who underwent a standardized transvaginal ultrasound examination and were selected for surgery. Data on 5020 patients were recorded in 3 phases from 2002 through 2012. The 5 Simple Rules features indicative of a benign tumor (B-features) and the 5 features indicative of malignancy (M-features) are based on the presence of ascites, tumor morphology, and degree of vascularity at ultrasonography. Gold standard was the histopathologic diagnosis of the adnexal mass (pathologist blinded to ultrasound findings). Logistic regression analysis was used to estimate the risk of malignancy based on the 10 ultrasound features and type of center. The diagnostic performance was evaluated by area under the receiver operating characteristic curve, sensitivity, specificity, positive likelihood ratio (LR+), negative likelihood ratio (LR-), positive predictive value (PPV), negative predictive value (NPV), and calibration curves. Results: Data on 4848 patients were analyzed. The malignancy rate was 43% (1402/3263) in oncology centers and 17% (263/1585) in other centers. The area under the receiver operating characteristic curve on validation data was very similar in oncology centers (0.917; 95% confidence interval, 0.901-0.931) and other centers (0.916; 95% confidence interval, 0.873-0.945). Risk estimates showed good calibration. In all, 23% of patients in the validation data set had a very low estimated risk (
AB - Background: Accurate methods to preoperatively characterize adnexal tumors are pivotal for optimal patient management. A recent metaanalysis concluded that the International Ovarian Tumor Analysis algorithms such as the Simple Rules are the best approaches to preoperatively classify adnexal masses as benign or malignant. Objective: We sought to develop and validate a model to predict the risk of malignancy in adnexal masses using the ultrasound features in the Simple Rules. Study Design: This was an international cross-sectional cohort study involving 22 oncology centers, referral centers for ultrasonography, and general hospitals. We included consecutive patients with an adnexal tumor who underwent a standardized transvaginal ultrasound examination and were selected for surgery. Data on 5020 patients were recorded in 3 phases from 2002 through 2012. The 5 Simple Rules features indicative of a benign tumor (B-features) and the 5 features indicative of malignancy (M-features) are based on the presence of ascites, tumor morphology, and degree of vascularity at ultrasonography. Gold standard was the histopathologic diagnosis of the adnexal mass (pathologist blinded to ultrasound findings). Logistic regression analysis was used to estimate the risk of malignancy based on the 10 ultrasound features and type of center. The diagnostic performance was evaluated by area under the receiver operating characteristic curve, sensitivity, specificity, positive likelihood ratio (LR+), negative likelihood ratio (LR-), positive predictive value (PPV), negative predictive value (NPV), and calibration curves. Results: Data on 4848 patients were analyzed. The malignancy rate was 43% (1402/3263) in oncology centers and 17% (263/1585) in other centers. The area under the receiver operating characteristic curve on validation data was very similar in oncology centers (0.917; 95% confidence interval, 0.901-0.931) and other centers (0.916; 95% confidence interval, 0.873-0.945). Risk estimates showed good calibration. In all, 23% of patients in the validation data set had a very low estimated risk (
KW - Simple Rules
KW - Adnexa
KW - Color Doppler
KW - Diagnosis
KW - Diagnostic algorithm
KW - International Ovarian Tumor Analysis
KW - Logistic regression analysis
KW - Ovarian cancer
KW - Ovarian neoplasms
KW - Preoperative evaluation
KW - Risk assessment
KW - Ultrasonography
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UR - http://www.scopus.com/inward/citedby.url?scp=84975783313&partnerID=8YFLogxK
U2 - 10.1016/j.ajog.2016.01.007
DO - 10.1016/j.ajog.2016.01.007
M3 - Article
C2 - 26800772
AN - SCOPUS:84975783313
JO - American Journal of Obstetrics and Gynecology
JF - American Journal of Obstetrics and Gynecology
SN - 0002-9378
ER -