| 1. |
- Sladkevicius, Povilas, et al.
(författare)
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Inter-observer agreement in describing the ultrasound appearance of adnexal masses and in calculating the risk of malignancy using logistic regression models.
- 2015
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Ingår i: Clinical Cancer Research. - 1078-0432. ; 21:3, s. 594-601
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Tidskriftsartikel (refereegranskat)abstract
- Purpose: To estimate inter-observer 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 inter-observer differences in calculated risk of malignancy. Experimental Design: 117 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). Inter-observer 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 inter-observer 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: Inter-observer agreement in classifying tumors as benign or malignant using the risk of malignancy cut off of 10% for LR1 and LR2 was good. However, because risks 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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| 2. |
- Van Holsbeke, Caroline, et al.
(författare)
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External Validation of Diagnostic Models to Estimate the Risk of Malignancy in Adnexal Masses
- 2012
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Ingår i: Clinical Cancer Research. - 1078-0432. ; 18:3, s. 815-825
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Tidskriftsartikel (refereegranskat)abstract
- Purpose: To externally validate and compare the performance of previously published diagnostic models developed to predict malignancy in adnexal masses. Experimental Design: We externally validated the diagnostic performance of 11 models developed by the International Ovarian Tumor Analysis (IOTA) group and 12 other (non-IOTA) models on 997 prospectively collected patients. The non-IOTA models included the original risk of malignancy index (RMI), three modified versions of the RMI, six logistic regression models, and two artificial neural networks. The ability of the models to discriminate between benign and malignant adnexal masses was expressed as the area under the receiver operating characteristic curve (AUC), sensitivity, specificity, and likelihood ratios (LR+, LR-). Results: Seven hundred and forty-two (74%) benign and 255 (26%) malignant masses were included. The IOTA models did better than the non-IOTA models (AUCs between 0.941 and 0.956 vs. 0.839 and 0.928). The difference in AUC between the best IOTA and the best non-IOTA model was 0.028 [95% confidence interval (CI), 0.011-0.044]. The AUC of the RMI was 0.911 (difference with the best IOTA model, 0.044; 95% CI, 0.024-0.064). The superior performance of the IOTA models was most pronounced in premenopausal patients but was also observed in postmenopausal patients. IOTA models were better able to detect stage I ovarian cancer. Conclusion: External validation shows that the IOTA models outperform other models, including the current reference test RMI, for discriminating between benign and malignant adnexal masses. Clin Cancer Res; 18(3); 815-25. (C)2011 AACR.
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| 3. |
- Van Holsbeke, Caroline, et al.
(författare)
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External validation of mathematical models to distinguish between benign and malignant adnexal tumors: A multicenter study by the International Ovarian Tumor Analysis group
- 2007
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Ingår i: Clinical Cancer Research. - 1078-0432. ; 13:15, s. 4440-4447
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Tidskriftsartikel (refereegranskat)abstract
- Purpose: Several scoring systems have been developed to distinguish between benign and malignant adnexal tumors. However, few of them have been externally validated in new populations. Our aim was to compare their performance on a prospectively collected large multicenter data set. Experimental Design: In phase I of the International Ovarian Tumor Analysis multicenter study, patients with a persistent adnexal mass were examined with transvaginal ultrasound and color Doppler imaging. More than 50 end point variables were prospectively recorded for analysis. The outcome measure was the histologic classification of excised tissue as malignant or benign. We used the International Ovarian Tumor Analysis data to test the accuracy of previously published scoring systems. Receiver operating characteristic curves were constructed to compare the performance of the models. Results: Data from 1,066 patients were included; 800 patients (75%) had benign tumors and 266 patients (25%) had malignant tumors. The morphologic scoring system used by Lerner gave an area under the receiver operating characteristic curve (AUC) of 0.68, whereas the multimodal risk of malignancy index used by Jacobs gave an AUC of 0.88. The corresponding values for logistic regression and artificial neural network models varied between 0.76 and 0.91 and between 0.87 and 0.90, respectively. Advanced kernel-based classifiers gave an AUC of up to 0.92. Conclusion: The performance of the risk of malignancy index was similar to that of most logistic regression and artificial neural network models. The best result was obtained with a relevance vector machine with radial basis function kernel. Because the models were tested on a large multicenter data set, results are likely to be generally applicable.
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| 4. |
- Van Holsbeke, Caroline, et al.
(författare)
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Prospective Internal Validation of Mathematical Models to Predict Malignancy in Adnexal Masses: Results from the International Ovarian Tumor Analysis Study
- 2009
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Ingår i: Clinical Cancer Research. - 1078-0432. ; 15:2, s. 684-691
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Tidskriftsartikel (refereegranskat)abstract
- Purpose: To prospectively test the mathematical models for calculation of the risk of malignancy in adnexal masses that were developed on the International Ovarian Tumor Analysis (IOTA) phase 1 data set on a new data set and to compare their performance with that of pattern recognition, our standard method. Methods: Three IOTA centers included 507 new patients who all underwent a transvaginal ultrasound using the standardized IOTA protocol. The outcome measure was the histologic classification of excised tissue. The diagnostic performance of 11 mathematical models that had been developed on the phase 1 data set and of pattern recognition was expressed as area under the receiver operating characteristic curve (AUC) and as sensitivity and specificity when using the cutoffs recommended in the studies where the models had been created. For pattern recognition, an AUC was made based on level of diagnostic confidence, Results: All IOTA models performed very well and quite similarly, with sensitivity and specificity ranging between 92% and 96% and 74% and 84%, respectively, and AUCs between 0.945 and 0.950. A least squares support vector machine with linear kernel and a logistic regression model had the largest AUCs. For pattern recognition, the AUC was 0.963, sensitivity was 90.2%, and specificity was 92.9%. Conclusion: This internal validation of mathematical models to estimate the malignancy risk in adnexal tumors shows that the IOTA models had a diagnostic performance similar to that in the original data set. Pattern recognition used by an expert sonologist remains the best method, although the difference in performance between the best mathematical model is not large.
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| 5. |
- Wynants, Laure, et al.
(författare)
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Clinical utility of risk modelsto refer patients with adnexal masses to specialized oncology care : Multicenter external validation using decision curve analysis
- 2017
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Ingår i: Clinical Cancer Research. - 1078-0432. ; 23:17, s. 5082-5090
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Tidskriftsartikel (refereegranskat)abstract
- Purpose: To evaluate the utility of preoperative diagnostic models for ovarian cancer based on ultrasound and/or biomarkers for referring patients to specialized oncology care. The investigated models were RMI, ROMA, and 3 models from the International Ovarian Tumor Analysis (IOTA) group [LR2, ADNEX, and the Simple Rules risk score (SRRisk)]. Experimental Design: A secondary analysis of prospectively collected data from 2 cross-sectional cohort studies was performed to externally validate diagnostic models. A total of 2, 763 patients (2, 403 in dataset 1 and 360 in dataset 2) from 18 centers (11 oncology centers and 7 nononcology hospitals) in 6 countries participated. Excised tissue was histologically classified as benign or malignant. The clinical utility of the preoperative diagnostic models was assessed with net benefit (NB) at a range of risk thresholds (5%-50% risk of malignancy) to refer patients to specialized oncology care. We visualized results with decision curves and generated bootstrap confidence intervals. Results: The prevalence of malignancy was 41% in dataset 1 and 40% in dataset 2. For thresholds up to 10% to 15%, RMI and ROMA had a lower NB than referring all patients. SRRisks and ADNEX demonstrated the highest NB. At a threshold of 20%, the NBs of ADNEX, SRrisks, and RMI were 0.348, 0.350, and 0.270, respectively. Results by menopausal status and type of center (oncology vs. nononcology) were similar. Conclusions: All tested IOTA methods, especially ADNEX and SRRisks, are clinically more useful than RMI and ROMA to select patients with adnexal masses for specialized oncology care.
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