Evaluating the risk of ovarian cancer before surgery using the ADNEX model to differentiate between benign, borderline, early and advanced stage invasive, and secondary metastatic tumours: prospective multicentre diagnostic study

Ben Van Calster(KU Leuven), Kirsten Van Hoorde(iMinds), L. Valentin(Skåne University Hospital), A. C. Testa(Università Cattolica del Sacro Cuore), D. Fischerová(Charles University), C. Van Holsbeke(Ziekenhuis Oost-Limburg), L. Savelli(University of Bologna), D. Franchi(European Institute of Oncology), E. Epstein(Karolinska University Hospital), J. Kaijser(KU Leuven), V. Van Belle(KU Leuven), Artur Czekierdowski(Medical University of Lublin), S. Guerriero(Azienda Ospedaliero-Universitaria Cagliari), Robert Fruscio(University of Milano-Bicocca), Chiara Lanzani(University of Milan), Felice Scala(Fondazione IRCCS Istituto Nazionale dei Tumori), T. Bourne(Queen Charlotte's and Chelsea Hospital), D. Timmerman(KU Leuven), International Ovarian Tumour Analysis (IOTA) group
BMJ
October 15, 2014
Cited by 497Open Access
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Abstract

OBJECTIVES: To develop a risk prediction model to preoperatively discriminate between benign, borderline, stage I invasive, stage II-IV invasive, and secondary metastatic ovarian tumours. DESIGN: Observational diagnostic study using prospectively collected clinical and ultrasound data. SETTING: 24 ultrasound centres in 10 countries. PARTICIPANTS: Women with an ovarian (including para-ovarian and tubal) mass and who underwent a standardised ultrasound examination before surgery. The model was developed on 3506 patients recruited between 1999 and 2007, temporally validated on 2403 patients recruited between 2009 and 2012, and then updated on all 5909 patients. MAIN OUTCOME MEASURES: Histological classification and surgical staging of the mass. RESULTS: The Assessment of Different NEoplasias in the adneXa (ADNEX) model contains three clinical and six ultrasound predictors: age, serum CA-125 level, type of centre (oncology centres v other hospitals), maximum diameter of lesion, proportion of solid tissue, more than 10 cyst locules, number of papillary projections, acoustic shadows, and ascites. The area under the receiver operating characteristic curve (AUC) for the classic discrimination between benign and malignant tumours was 0.94 (0.93 to 0.95) on temporal validation. The AUC was 0.85 for benign versus borderline, 0.92 for benign versus stage I cancer, 0.99 for benign versus stage II-IV cancer, and 0.95 for benign versus secondary metastatic. AUCs between malignant subtypes varied between 0.71 and 0.95, with an AUC of 0.75 for borderline versus stage I cancer and 0.82 for stage II-IV versus secondary metastatic. Calibration curves showed that the estimated risks were accurate. CONCLUSIONS: The ADNEX model discriminates well between benign and malignant tumours and offers fair to excellent discrimination between four types of ovarian malignancy. The use of ADNEX has the potential to improve triage and management decisions and so reduce morbidity and mortality associated with adnexal pathology.


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