A Prospective Validation of the IOTA Logistic Regression Models (LR1 and LR2) in Comparison to Subjective Pattern Recognition for the Diagnosis of Ovarian Cancer

Nunes, Natalie; Ambler, Gareth; Hoo, W.; Naftalin, J.; Foo, X.; Widschwendter, Martin

doi:10.1097/igc.0b013e3182a6171a

Cited by 16 publications

(13 citation statements)

References 16 publications

(11 reference statements)

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“…Our results showed that two experienced sonologists agreed quite well in their classification of masses as benign or malignant using the 10% risk of malignancy cutoff of LR1 and LR2, and that the diagnostic performance of LR1 and LR2 with regard to discrimination between benign and malignant tumors was similar for the two sonologists and similar to that reported by others (14,(26)(27)(28). This is reassuring, because the main purpose of using model LR1 and LR2 is to classify tumors as benign or malignant.…”

Section: Discussionsupporting

confidence: 85%

Interobserver Agreement in Describing the Ultrasound Appearance of Adnexal Masses and in Calculating the Risk of Malignancy Using Logistic Regression Models

Sladkevicius

Valentin

2015

Clinical Cancer Research

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Purpose: To estimate interobserver agreement with regard to describing adnexal masses using the International Ovarian Tumor Analysis (IOTA) terminology and the risk of malignancy calculated using IOTA logistic regression models LR1 and LR2, and to elucidate what explained the largest interobserver differences in calculated risk of malignancy.Experimental Design: One hundred and seventeen women with adnexal masses were examined with transvaginal gray scale and power Doppler ultrasound by two independent experienced sonologists who described the masses using IOTA terminology. The risk of malignancy was calculated using LR1 and LR2. A predetermined risk of malignancy cutoff of 10% indicated malignancy.Results: There were 94 benign, four borderline, and 19 invasively malignant tumors. There was substantial variability between the two sonologists in measurement results and some variability in assessment of categorical variables (agreement 40%-98%, Kappa 0.30-0.91). Interobserver agreement when classifying tumors as benign or malignant was 84% (98/117), Kappa 0.68 for LR1, and for LR2 85% (99/117), Kappa 0.68. When using LR1 and LR2, the interobserver difference in calculated risk was !25 percentage units in 9% (11/117) and 12% (14/117) of tumors, respectively. Differences in assessment of wall irregularity, acoustic shadowing, color score, and color flow in papillary projections explained most of these largest differences.Conclusions: Interobserver agreement in classifying tumors as benign or malignant using the risk of malignancy cutoff of 10% for LR1 and LR2 was good. However, because risk estimates may differ substantially between sonologists, one should be cautious with using the risk value for counseling patients about their individual risk.

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Section: Discussionsupporting

confidence: 85%

Interobserver Agreement in Describing the Ultrasound Appearance of Adnexal Masses and in Calculating the Risk of Malignancy Using Logistic Regression Models

Sladkevicius

Valentin

2015

Clinical Cancer Research

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“…This may explain why the results of IOTA phase 3 confirm those of previous IOTA studies that showed excellent test performance of all IOTA strategies (Timmerman et al , 2005, 2007, 2008, 2010a, 2010b; Van Holsbeke et al , 2009, 2012; Ameye et al , 2012; Kaijser et al , 2013; Sayasneh et al , 2013a, 2013b). On the other hand, validation studies of LR1, LR2 and SRs performed outside IOTA studies reported similar results (Hartman et al , 2012; Nunes et al , 2012, 2013; Alcázar et al , 2013), and there is now evidence that the IOTA strategies retain their performance in the hands of sonographers and relatively inexperienced doctors (Hartman et al , 2012; Nunes et al , 2012, 2013; Alcázar et al , 2013; Sayasneh et al , 2013a, 2013b). …”

Section: Discussionmentioning

confidence: 80%

“…Unfortunately, most gynaecologists, radiologists and sonographers have limited experience with the use of SA of ultrasound images to discriminate between benign and malignant adnexal masses. As SRs, SDs and LR2 have been shown to perform very well in the hands of both sonographers and gynaecologists with limited ultrasound experience (Hartman et al , 2012; Nunes et al , 2012, 2013; Alcázar et al , 2013; Sayasneh et al , 2013a, 2013b), they could be used as first stage tests, and patients with inconclusive or equivocal results of the first stage test could be referred for SA by an experienced ultrasound examiner.…”

Section: Discussionmentioning

confidence: 99%

“…Forest plots for LR2, SRs and RMI were used to present centre-specific and combined results. Subgroup analyses for RMI and the most extensively validated IOTA methods (i.e., LR2 and SRs) (Timmerman et al , 2010a; Hartman et al , 2012; Nunes et al , 2012, 2013; Alcázar et al , 2013; Sayasneh et al , 2013a, 2013b) were performed for pre- and postmenopausal women.…”

Section: Methodsmentioning

confidence: 99%

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

et al. 2014

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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.

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“…[3] An advantage of the LR2 or Simple Rules models over subjective assessment is their objectivity and simplicity, which facilitates their use by ultrasonographers with different backgrounds and various levels of experience. [5, 6]. The vascularity of the mass and the tumour malignant feature M4 was assessed based on some other scans that were not presented in the article.…”

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confidence: 99%

Reply to comment of Prof. Artur Czekierdowski

Jakiel¹

2017

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A Prospective Validation of the IOTA Logistic Regression Models (LR1 and LR2) in Comparison to Subjective Pattern Recognition for the Diagnosis of Ovarian Cancer

Abstract: The AUC of the IOTA LR1 and LR2 were similar in nonexpert's hands when compared to the original and validation IOTA studies. The PR method was the more accurate test to diagnose ovarian cancer than either of the IOTA models.

Cited by 16 publications

References 16 publications

Interobserver Agreement in Describing the Ultrasound Appearance of Adnexal Masses and in Calculating the Risk of Malignancy Using Logistic Regression Models

Interobserver Agreement in Describing the Ultrasound Appearance of Adnexal Masses and in Calculating the Risk of Malignancy Using Logistic Regression Models

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

Reply to comment of Prof. Artur Czekierdowski

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