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IODA DEFINE 9 SOFTWARE

This is based on a logistic regression model with the ten features and the type of center (oncology center vs other) as predictors. This was overcome by the development of the SRrisk calculation tool15. The Simple Rules have the important drawback that they do not give a predicted risk, and hence not a level of confidence in the classification. The Simple Rules risk (SRrisk) calculation (2016)

IODA DEFINE 9 SOFTWARE

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The original SR is implemented electronically in various formats: The parameters used in the Simple Rules are based on the terms and definitions as published by the IOTA group.14 The Simple Rules cannot replace training and experience in ultrasonography and cannot compensate for poor quality ultrasound equipment. The manuscript describing the Simple Rules is published in Ultrasound in Obstetrics and Gynecology (Timmerman et al, 2008).1The Simple Rules have been successfully validated in several studies.2-13 patients selected for expectant management were excluded when creating the model.

IOTA models, RMI, ROMA) have been created for patients undergoing surgery, i.e. All current diagnostic models for adnexal tumors (e.g. All patients included required surgery as judged by a local clinician. The Simple Rules were developed by clinicians and statisticians from the International Ovarian Tumor Analysis (IOTA) group, based on clinical and ultrasound data from 1066 women recruited at 9 centers in 5 countries (Italy, Belgium, Sweden, France, and UK).

Inconclusive - no features apply, or both B- and M-features applyįigure 1.

Based on which of the B- and M-features that apply, tumors are classified as Benign, Malignant or Inconclusive:

The Simple Rules can be used to diagnose ovarian cancer in women who have at least one persistent adnexal (ovarian, para-ovarian, and tubal) tumor and are considered to require surgery. The Simple Rules are a preoperative classification system for ovarian tumors, consisting of five features typical for benign tumors (B-features) and five features typical for malignant tumors (M-features), see Figure 1.