Strategies to diagnose ovarian cancer: New evidence from phase 3 of the multicentre international IOTA study

A. Testa, J. Kaijser, L. Wynants, D. Fischerova, C. Van Holsbeke, D. Franchi, L. Savelli, E. Epstein, A. Czekierdowski, S. Guerriero, R. Fruscio, F. P G Leone, I. Vergote, T. Bourne, L. Valentin, B. Van Calster, D. Timmerman

Research output: Contribution to journalArticlepeer-review

Abstract

Background:To compare different ultrasound-based international ovarian tumour analysis (IOTA) strategies and risk of malignancy index (RMI) for ovarian cancer diagnosis using a meta-analysis approach of centre-specific data from IOTA3.Methods:This prospective multicentre diagnostic accuracy study included 2403 patients with 1423 benign and 980 malignant adnexal masses from 2009 until 2012. All patients underwent standardised transvaginal ultrasonography. Test performance of RMI, subjective assessment (SA) of ultrasound findings, two IOTA risk models (LR1 and LR2), and strategies involving combinations of IOTA simple rules (SRs), simple descriptors (SDs) and LR2 with and without SA was estimated using a meta-analysis approach. Reference standard was histology after surgery.Results:The areas under the receiver operator characteristic curves of LR1, LR2, SA and RMI were 0.930 (0.917-0.942), 0.918 (0.905-0.930), 0.914 (0.886-0.936) and 0.875 (0.853-0.894). Diagnostic one-step and two-step strategies using LR1, LR2, SR and SD achieved summary estimates for sensitivity 90-96%, specificity 74-79% and diagnostic odds ratio (DOR) 32.8-50.5. Adding SA when IOTA methods yielded equivocal results improved performance (DOR 57.6-75.7). Risk of Malignancy Index had sensitivity 67%, specificity 91% and DOR 17.5.Conclusions:This study shows all IOTA strategies had excellent diagnostic performance in comparison with RMI. The IOTA strategy chosen may be determined by clinical preference.

Original languageEnglish
Pages (from-to)680-688
Number of pages9
JournalBritish Journal of Cancer
Volume111
Issue number4
DOIs
Publication statusPublished - Aug 12 2014

Keywords

  • diagnosis
  • meta-analysis
  • ovarian cancer

ASJC Scopus subject areas

  • Cancer Research
  • Oncology

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