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Sökning: WFRF:(Vergote I) > Bourne T.

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1.
  • Ameye, L., et al. (författare)
  • A scoring system to differentiate malignant from benign masses in specific ultrasound-based subgroups of adnexal tumors
  • 2009
  • Ingår i: Ultrasound in Obstetrics & Gynecology. - : Wiley. - 1469-0705 .- 0960-7692. ; 33:1, s. 92-101
  • Tidskriftsartikel (refereegranskat)abstract
    • Objective To investigate if the prediction of malignant adnexal masses can be improved by considering different ultrasound-based subgroups of tumors and constructing a scoring system for each subgroup instead of using a risk estimation model applicable to all tumors. Methods We used a multicenter database of 1573 patients with at least one persistent adnexal mass. The masses were categorized into four subgroups based on their ultrasound appearance: ( 1) unilocular cyst; ( 2) multilocular cyst; ( 3) presence of a solid component but no papillation; and ( 4) presence of papillation. For each of the four subgroups a scoring system to predict malignancy was developed in a development set consisting of 754 patients in total ( respective numbers of patients: ( 1) 228; ( 2) 143; ( 3) 183; and ( 4) 200). The subgroup scoring system was then tested in 312 patients and prospectively validated in 507 patients. The sensitivity and specificity, with regard to the prediction of malignancy, of the scoring system were compared with that of the subjective evaluation of ultrasound images by an experienced examiner ( pattern recognition) and with that of a published logistic regression (LR) model for the calculation of risk of malignancy in adnexal masses. The gold standard was the pathological classification of the mass as benign or malignant ( borderline, primary invasive, or metastatic). Results In the prospective validation set, the sensitivity of pattern recognition, the LR model and the subgroup scoring system was 90% (129/143), 95% (136/143) and 88% (126/143), respectively, and the specificity was 93% (338/364), 74% (270/364) and 90% (329/364), respectively. Conclusions In the hands of experienced ultrasound examiners, the subgroup scoring system for diagnosing malignancy has a performance that is similar to that of pattern recognition, the latter method being the best diagnostic method currently available. The scoring system is less sensitive but more specific than the LR model. Copyright (C) 2008 ISUOG. Published by John Wiley & Sons, Ltd.
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2.
  • Daemen, A., et al. (författare)
  • Improving the preoperative classification of adnexal masses as benign or malignant by second-stage tests
  • 2011
  • Ingår i: Ultrasound in Obstetrics & Gynecology. - : Wiley. - 1469-0705 .- 0960-7692. ; 37:1, s. 100-106
  • Tidskriftsartikel (refereegranskat)abstract
    • Objective The aim of this study was to establish when a second-stage diagnostic test may be of value in cases where a primary diagnostic test has given an uncertain diagnosis of the benign or malignant nature of an adnexal mass. Methods The diagnostic performance with regard to discrimination between benign and malignant adnexal masses for mathematical models including ultrasound variables and for subjective evaluation of ultrasound findings by an experienced ultrasound examiner was expressed as area under the receiver-operating characteristics curve (AUC), sensitivity and specificity. These were calculated for the total study population of 1938 patients with an adnexal mass as well as for sub-populations defined by the certainty with which the diagnosis of benignity or malignancy was made. The effect of applying a second-stage test to the tumors where risk estimation was uncertain was determined. Results The best mathematical model (LR1) had an AUC of 0.95, sensitivity of 92% and specificity of 84% when applied to all tumors. When model LR1 was applied to the 10% of tumors in which the calculated risk fell closest to the risk cut-off of the model, the AUC was 0.59, sensitivity 90% and specificity 21%. A strategy where subjective evaluation was used to classify these 10% of tumors for which LR1 performed poorly and where LR1 was used in the other 90% of tumors resulted in a sensitivity of 91% and specificity of 90%. Applying subjective evaluation to all tumors yielded an AUC of 0.95, sensitivity of 90% and specificity of 93%. Sensitivity was 81% and specificity 47% for those patients where the ultrasound examiner was uncertain about the diagnosis (n = 115; 5.9%). No mathematical model performed better than did subjective evaluation among the 115 tumors where the ultrasound examiner was uncertain. Conclusion When model LR1 is used as a primary test for discriminating between benign and malignant adnexal masses, the use of subjective evaluation of ultrasound findings by an experienced examiner as a second-stage test in the 10% of cases for which the model yields a risk of malignancy closest to its risk cut-off will improve specificity without substantially decreasing sensitivity. However, none of the models tested proved suitable as a second-stage test in tumors where subjective evaluation yielded an uncertain result. Copyright (C) 2010 ISUOG. Published by John Wiley & Sons, Ltd.
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  • Kaijser, J., et al. (författare)
  • Improving strategies for diagnosing ovarian cancer: a summary of the International Ovarian Tumor Analysis (IOTA) studies
  • 2013
  • Ingår i: Ultrasound in Obstetrics & Gynecology. - : Wiley. - 1469-0705 .- 0960-7692. ; 41:1, s. 9-20
  • Forskningsöversikt (refereegranskat)abstract
    • In order to ensure that ovarian cancer patients access appropriate treatment to improve the outcome of this disease, accurate characterization before any surgery on ovarian pathology is essential. The International Ovarian Tumor Analysis (IOTA) collaboration has standardized the approach to the ultrasound description of adnexal pathology. A prospectively collected large database enabled previously developed prediction models like the risk of malignancy index (RMI) to be tested and novel prediction models to be developed and externally validated in order to determine the optimal approach to characterize adnexal pathology preoperatively. The main IOTA prediction models (logistic regression model 1 (LR1) and logistic regression model 2 (LR2)) have both shown excellent diagnostic performance (area under the curve (AUC) values of 0.96 and 0.95, respectively) and outperform previous diagnostic algorithms. Their test performance almost matches subjective assessment by experienced examiners, which is accepted to be the best way to classify adnexal masses before surgery. A two-step strategy using the IOTA simple rules supplemented with subjective assessment of ultrasound findings when the rules do not apply, also reached excellent diagnostic performance (sensitivity 90%, specificity 93%) and misclassified fewer malignancies than did the RMI. An evidence-based approach to the preoperative characterization of ovarian and other adnexal masses should include the use of LR1, LR2 or IOTA simple rules and subjective assessment by an experienced examiner. Copyright (c) 2012 ISUOG. Published by John Wiley & Sons, Ltd.
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5.
  • Landolfo, C., et al. (författare)
  • Benign descriptors and ADNEX in two-step strategy to estimate risk of malignancy in ovarian tumors : retrospective validation on IOTA 5 multicenter cohort
  • 2023
  • Ingår i: Ultrasound in Obstetrics and Gynecology. - : Wiley. - 0960-7692 .- 1469-0705. ; 61:2, s. 231-242
  • Tidskriftsartikel (refereegranskat)abstract
    • Objective: Previous work suggested that the ultrasound-based benign Simple Descriptors can reliably exclude malignancy in a large proportion of women presenting with an adnexal mass. We aim to validate a modified version of the Benign Simple Descriptors (BD), and we introduce a two-step strategy to estimate the risk of malignancy: if the BDs do not apply, the ADNEX model is used to estimate the risk of malignancy. Methods: This is a retrospective analysis using the data from the 2-year interim analysis of the IOTA5 study, in which consecutive patients with at least one adnexal mass were recruited irrespective of subsequent management (conservative or surgery). The main outcome was classification of tumors as benign or malignant, based on histology or on clinical and ultrasound information during one year of follow-up. Multiple imputation was used when outcome based on follow-up was uncertain according to predefined criteria. Results: 8519 patients were recruited at 36 centers between 2012 and 2015. We included all masses that were not already in follow-up at recruitment from 17 centers with good quality surgical and follow-up data, leaving 4905 patients for statistical analysis. 3441 (70%) tumors were benign, 978 (20%) malignant, and 486 (10%) uncertain. The BDs were applicable in 1798/4905 (37%) tumors, and 1786 (99.3%) of these were benign. The two-step strategy based on ADNEX without CA125 had an area under the receiver operating characteristic curve (AUC) of 0.94 (95% CI, 0.91-0.95). The risk of malignancy was slightly underestimated, but calibration varied between centers. A sensitivity analysis in which we expanded the definition of uncertain outcome resulted in 1419 (29%) tumors with uncertain outcome and an AUC of the two-step strategy without CA125 of 0.93 (95% CI, 0.91-0.95). Conclusion: A large proportion of adnexal masses can be classified as benign by the BDs. For the remaining masses the ADNEX model can be used to estimate the risk of malignancy. This two-step strategy is convenient for clinical use.
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6.
  • Testa, A, et al. (författare)
  • Strategies to diagnose ovarian cancer: new evidence from phase 3 of the multicentre international IOTA study.
  • 2014
  • Ingår i: British Journal of Cancer. - : Springer Science and Business Media LLC. - 1532-1827 .- 0007-0920. ; 111:4, s. 680-688
  • Tidskriftsartikel (refereegranskat)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.British Journal of Cancer advance online publication 17 June 2014; doi:10.1038/bjc.2014.333 www.bjcancer.com.
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7.
  • Timmerman, D, et al. (författare)
  • Logistic regression model to distinguish between the benign and malignant adnexal mass before surgery: A multicenter study by the International Ovarian Tumor Analysis Group
  • 2005
  • Ingår i: Journal of Clinical Oncology. - 1527-7755. ; 23:34, s. 8794-8801
  • Tidskriftsartikel (refereegranskat)abstract
    • Purpose To collect data for the development of a more universally useful logistic regression model to distinguish between a malignant and benign adnexal tumor before surgery. Patients and Methods Patients had at least one persistent mass. More than 50 clinical and sonographic end points were defined and recorded for analysis. The outcome measure was the histologic classification of excised tissues as malignant or benign. Results Data from 1,066 patients recruited from nine European centers were included in the analysis; 800 patients (75%) had benign tumors and 266 (25%) had malignant tumors. The most useful independent prognostic variables for the logistic regression model were as follows: (1) personal history of ovarian cancer, (2) hormonal therapy, (3) age, (4) maximum diameter of lesion, (5) pain, (6) ascites, (7) blood flow within a solid papillary projection, (8) presence of an entirely solid tumor, (9) maximal diameter of solid component, (10) irregular internal cyst walls, (11) acoustic shadows, and (12) a color score of intratumoral blood flow. The model containing all 12 variables (M1) gave an area under the receiver operating characteristic curve of 0.95 for the development data set (n = 754 patients). The corresponding value for the test data set (n = 312 patients) was 0.94; and a probability cutoff value of .10 gave a sensitivity of 93% and a specificity of 76%. Conclusion Because the model was constructed from multicenter data, it is more likely to be generally applicable. The effectiveness of the model will be tested prospectively at different centers.
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8.
  • Timmerman, D., et al. (författare)
  • Ovarian cancer prediction in adnexal masses using ultrasound-based logistic regression models: a temporal and external validation study by the IOTA group
  • 2010
  • Ingår i: Ultrasound in Obstetrics & Gynecology. - : Wiley. - 1469-0705 .- 0960-7692. ; 36:2, s. 226-234
  • Tidskriftsartikel (refereegranskat)abstract
    • Objectives The aims of the study were to temporally and externally validate the diagnostic performance of two logistic regression models containing clinical and ultrasound variables in order to estimate the risk of malignancy in adnexal masses, and to compare the results with the subjective interpretation of ultrasound findings carried out by an experienced ultrasound examiner ('subjective assessment'). Methods Patients with adnexal masses, who were put forward by the 19 centers participating in the study, underwent a standardized transvaginal ultrasound examination by a gynecologist or a radiologist specialized in ultrasonography. The examiner prospectively collected information on clinical and ultrasound variables, and classified each mass as benign or malignant on the basis of subjective evaluation of ultrasound findings. The gold standard was the histology of the mass with local clinicians deciding whether to operate on the basis of ultrasound results and the clinical picture. The models' ability to discriminate between malignant and benign masses was assessed, together with the accuracy of the risk estimates. Results Of the 1938 patients included in the study, 1396 had benign, 373 had primary invasive, 111 had borderline malignant and 58 had metastatic tumors. On external validation (997 patients from 12 centers), the area under the receiver operating characteristics curve (AUC) for a model containing 12 predictors (LR1) was 0.956, for a reduced model with six predictors (LR2) was 0.949 and for subjective assessment was 0.949. Subjective assessment gave a positive likelihood ratio of 11.0 and a negative likelihood ratio of 0.14. The corresponding likelihood ratios for a previously derived probability threshold (0.1) were 6.84 and 0.09 for LR1, and 6.36 and 0.10 for LR2. On temporal validation (941 patients from seven centers), the AUCs were 0.945 (LR1), 0.918 (LR2) and 0.959 (subjective assessment). Conclusions Both models provide excellent discrimination between benign and malignant masses. Because the models provide an objective and reasonably accurate risk estimation, they may improve the management of women with suspected ovarian pathology. Copyright (C) 2010 ISUOG. Published by John Wiley & Sons, Ltd.
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9.
  • Timmerman, D., et al. (författare)
  • Simple ultrasound-based rules for the diagnosis of ovarian cancer
  • 2008
  • Ingår i: Ultrasound in Obstetrics & Gynecology. - : Wiley. - 1469-0705 .- 0960-7692. ; 31:6, s. 681-690
  • Tidskriftsartikel (refereegranskat)abstract
    • Objective To derive simple and clinically useful ultrasound-based rules for discriminating between benign and malignant adnexal masses. Methods In a multicenter study involving nine centers consecutive patients with persistent adnexal tumors underwent transvaginal gray-scale and Doppler ultrasound examination using a standardized examination technique and standardized terms and definitions. Information on 42 gray-scale ultrasound variables and six Doppler variables was collected and entered into a research protocol. When developing simple ultrasound-based rules to predict malignancy (M-rules) we chose the ultrasound variable or the combination of ultrasound variables that bad the highest positive predictive value (PPV) with regard to malignancy; when developing simple rules to predict a benign tumor (B-rules) we chose the ultrasound variable or the combination of ultrasound variables that had the lowest PPV with regard to malignancy. We selected ten rules that were in agreement with our clinical experience and were applicable to at least 30 tumors and then tested them prospectively on 507 tumors examined in three of the nine centers. Results 1066 patients with 1233 adnexal tumors were included. There were 903 benign tumors (73%) and 330 malignant tumors (27%). In 167 patients the tumors were bilateral. We selected five simple rules to predict malignancy (M-rules): (1) irregular solid tumor; (2) ascites; (3) at least four papillary structures; (4) irregular multilocular-solid tumor with a largest diameter of at least 100 mm; and (5) very high color content on color Doppler examination. We chose five simple rules to suggest a benign tumor (B-rules): (1) unilocular cyst; (2) presence of solid components where the largest solid component is < 7 mm in largest diameter; (3) acoustic shadows; (4) smooth multilocular tumor less than 100 mm in largest diameter; and (S) no detectable blood flow on Doppler examination. These ten rules were applicable to 76% of all tumors, where they resulted in a sensitivity of 93%, specificity of 90%, positive likelihood ratio (LR+) of 9.45 and negative likelihood ratio (LR-) of 0.08. When prospectively tested the rules were applicable in 76% (386/507) of the tumors, where they had a sensitivity of 95% (106/112), a specificity of 91% (249/274), LR+ of 10.37, and LR- of 0.06. Conclusion Most adnexal tumors in an ordinary tumor population can be correctly classified as benign or malignant using simple ultrasound-based rules. For tumors that cannot be classified using simple rules, ultrasound examination by an expert examiner might be useful. Copyright (C) 2008 ISUOG. Published by John Wiley & Sons, Ltd.
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