Year: 2026
Type: review
Study design: Systematic Review
Abstract: BackgroundAccurate preoperative discrimination between benign and malignant ovarian or adnexal masses is essential for appropriate surgical planning and referral. The Risk of Malignancy Index 1 (RMI 1) incorporates ultrasound findings, menopausal status, and serum CA125, whereas the International Ovarian Tumor Analysis (IOTA) Simple Rules provide an ultrasound-based classification without requiring CA125. This systematic review evaluated whether IOTA Simple Rules perform better than RMI 1 in distinguishing benign from malignant ovarian masses. MethodsMEDLINE/PubMed, Embase, Cochrane Library, and Web of Science were searched from database inception to April 2026 for studies directly applying both IOTA Simple Rules and RMI 1 to the same patients, using histopathology as the reference standard. Eligible studies were assessed for methodological quality using QUADAS-2. Because only a small number of heterogeneous studies met the strict head-to-head eligibility criteria, findings were synthesised narratively rather than by quantitative meta-analysis. ResultsThree studies involving 804 women met the inclusion criteria. IOTA Simple Rules demonstrated sensitivity ranging from 83.8% to 88.9%, compared with 45.5% to 77.2% for RMI 1. Specificity ranged from 92.0% to 94.1% for IOTA Simple Rules and from 86.8% to 93.2% for RMI 1. IOTA Simple Rules were inconclusive in approximately 14–18% of masses in studies reporting this outcome. ConclusionsThe available direct evidence suggests that IOTA Simple Rules perform at least as well as, and generally better than, RMI 1, particularly for sensitivity. However, the evidence is limited by the small number of eligible studies and substantial heterogeneity. IOTA Simple Rules also have the practical advantage of not requiring CA125 testing. Need for future research Larger, prospective, standardised head-to-head studies across diverse populations are required before IOTA Simple Rules can be considered a definitive replacement for RMI 1.
DOI: 10.51168/wgc0ds79
Authors: Ruby Kumari, Shaesta Iqbal, Sweta Gupta, Vijya
Institution: Anugrah Narayan Magadh Medical College & Hospital
Language: English
Subfield: Oncology
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
OpenAlex ID: W7203578491