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Sökning: WFRF:(Bourne C.)

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81.
  • 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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82.
  • Timmerman, Dirk, et al. (författare)
  • Inclusion of CA-125 does not improve mathematical models developed to distinguish between benign and malignant adnexal tumors
  • 2007
  • Ingår i: Journal of Clinical Oncology. - 1527-7755. ; 25:27, s. 4194-4200
  • Tidskriftsartikel (refereegranskat)abstract
    • Purpose To test the value of serum CA-125 measurements alone or as part of a multimodal strategy to distinguish between malignant and benign ovarian tumors before surgery based on a large prospective multicenter study (International Ovarian Tumor Analysis). Patients and Methods Patients with at least one persistent ovarian mass preoperatively underwent transvaginal ultrasonography using gray scale imaging to assess tumor morphology and color Doppler imaging to obtain indices of blood flow. Results Data from 809 patients recruited from nine centers were included in the analysis; 567 patients (70%) had benign tumors and 242 (30%) had malignant tumors - of these 152 were primary invasive (62.8%), 52 were borderline malignant (21.5%), and 38 were metastatic (15.7%). A logistic regression model including CA-125 (M2) resulted in an area under the receiver operating characteristic curve (AUC) of 0.934 and did not outperform a published (M1) without serum CA-125 information (AUC, 0.936). Specifically designed new models including CA-125 for premenopausal women (M3) and for postmenopausal women (M4) did not perform significantly better than the model without CA-125 ( M1; AUC, 0.891 v AUC, 0.911 and AUC, 0.975 v AUC, 0.949, respectively). In postmenopausal patients, serum CA-125 alone (AUC, 0.920) and the risk of malignancy index (AUC, 0.924) performed very well. Results were very similar when the models were prospectively tested on a group of 345 new patients with adnexal masses of whom 126 had malignant tumors (37%). Conclusion Adding information on CA-125 to clinical information and ultrasound information does not improve discrimination of mathematical models between benign and malignant adnexal masses.
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83.
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84.
  • Timmerman, Stefan, et al. (författare)
  • External Validation of the Ovarian-Adnexal Reporting and Data System (O-RADS) Lexicon and the International Ovarian Tumor Analysis 2-Step Strategy to Stratify Ovarian Tumors Into O-RADS Risk Groups
  • 2023
  • Ingår i: JAMA Oncology. - : American Medical Association (AMA). - 2374-2437 .- 2374-2445. ; 9:2, s. 225-233
  • Tidskriftsartikel (refereegranskat)abstract
    • IMPORTANCE: Correct diagnosis of ovarian cancer results in better prognosis. Adnexal lesions can be stratified into the Ovarian-Adnexal Reporting and Data System (O-RADS) risk of malignancy categories with either the O-RADS lexicon, proposed by the American College of Radiology, or the International Ovarian Tumor Analysis (IOTA) 2-step strategy.OBJECTIVE: To investigate the diagnostic performance of the O-RADS lexicon and the IOTA 2-step strategy.DESIGN, SETTING, AND PARTICIPANTS: Retrospective external diagnostic validation study based on interim data of IOTA5, a prospective international multicenter cohort study, in 36 oncology referral centers or other types of centers. A total of 8519 consecutive adult patients presenting with an adnexal mass between January 1, 2012, and March 1, 2015, and treated either with surgery or conservatively were included in this diagnostic study. Twenty-five patients were excluded for withdrawal of consent, 2777 were excluded from 19 centers that did not meet predefined data quality criteria, and 812 were excluded because they were already in follow-up at recruitment. The analysis included 4905 patients with a newly detected adnexal mass in 17 centers that met predefined data quality criteria. Data were analyzed from January 31 to March 1, 2022.EXPOSURES: Stratification into O-RADS categories (malignancy risk <1%, 1% to <10%, 10% to <50%, and ≥50%). For the IOTA 2-step strategy, the stratification is based on the individual risk of malignancy calculated with the IOTA 2-step strategy.MAIN OUTCOMES AND MEASURES: Observed prevalence of malignancy in each O-RADS risk category, as well as sensitivity and specificity. The reference standard was the status of the tumor at inclusion, determined by histology or clinical and ultrasonographic follow-up for 1 year. Multiple imputation was used for uncertain outcomes owing to inconclusive follow-up information.RESULTS: Median age of the 4905 patients was 48 years (IQR, 36-62 years). Data on race and ethnicity were not collected. A total of 3441 tumors (70%) were benign, 978 (20%) were malignant, and 486 (10%) had uncertain classification. Using the O-RADS lexicon resulted in 1.1% (24 of 2196) observed prevalence of malignancy in O-RADS 2, 4% (34 of 857) in O-RADS 3, 27% (246 of 904) in O-RADS 4, and 78% (732 of 939) in O-RADS 5; the corresponding results for the IOTA 2-step strategy were 0.9% (18 of 1984), 4% (58 of 1304), 30% (206 of 690), and 82% (756 of 927). At the 10% risk threshold (O-RADS 4-5), the O-RADS lexicon had 92% sensitivity (95% CI, 87%-96%) and 80% specificity (95% CI, 74%-85%), and the IOTA 2-step strategy had 91% sensitivity (95% CI, 84%-95%) and 85% specificity (95% CI, 80%-88%).CONCLUSIONS AND RELEVANCE: The findings of this external diagnostic validation study suggest that both the O-RADS lexicon and the IOTA 2-step strategy can be used to stratify patients into risk groups. However, the observed malignancy rate in O-RADS 2 was not clearly below 1%.
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85.
  • Tshuma, Piwai, et al. (författare)
  • Cyclometalation of lanthanum(iii) based MOF for catalytic hydrogenation of carbon dioxide to formate
  • 2020
  • Ingår i: RSC Advances. - : Royal Society of Chemistry (RSC). - 2046-2069. ; 10:6, s. 3593-3605
  • Tidskriftsartikel (refereegranskat)abstract
    • The hydrogenation of carbon dioxide (CO2) to formic acid is of great importance due to its useful properties in the chemical industry. In this work, we have prepared a novel metal-organic framework (MOF), JMS-1, using bipyridyl dicarboxylate linkers, with molecular formula [La2(bpdc)3(DMF)3]n. Network analysis of JMS-1 revealed a new 7-connected topology (zaz). The MOF backbone of the activated phase (JMS-1a) was functionalized by cyclometalation using [RuCl2(p-cymene)]2 to produce Ru(ii)@JMS-1a. Both JMS-1a and Ru(ii)@JMS-1a were able to convert CO2 in the presence of hydrogen to formate. Ru(ii)@JMS-1a displayed outstanding conversion evidenced by a yield of 98% of formate under optimized conditions of total pressure 50 bar (CO2/H2 = 1 : 4, temperature 110 °C, time 24 h, 5 mmol KOH, 8 mL ethanol). This work is significant in providing new strategies of incorporating active catalytic centres in MOFs for efficient and selective conversion of CO2 to formate.
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86.
  • Valentin, Lil, et al. (författare)
  • Adding a single CA 125 measurement to ultrasound imaging performed by an experienced examiner does not improve preoperative discrimination between benign and malignant adnexal masses.
  • 2009
  • Ingår i: Ultrasound in obstetrics & gynecology : the official journal of the International Society of Ultrasound in Obstetrics and Gynecology. - : Wiley. - 1469-0705. ; 34, s. 345-354
  • Tidskriftsartikel (refereegranskat)abstract
    • OBJECTIVES: To determine whether CA 125 measurement is superior to ultrasound imaging performed by an experienced examiner for discriminating between benign and malignant adnexal lesions, and to determine whether adding CA 125 to ultrasound examination improves diagnostic performance. METHODS: This is a prospective multicenter study (International Ovarian Tumor Analysis (IOTA) study) conducted in nine European ultrasound centers in university hospitals. Of 1149 patients with an adnexal mass examined in the IOTA study, 83 were excluded. Of the remaining 1066 patients, 809 had CA 125 results available and were included. The patients underwent preoperative serum CA 125 measurements and transvaginal ultrasound examination by an experienced ultrasound examiner blinded to CA 125 values. The examiner classified each mass as certainly or probably benign, difficult to classify, or probably or certainly malignant. The outcome measure was the sensitivity and specificity with regard to malignancy of CA 125, ultrasound imaging and their combined use, the 'gold standard' being the histological diagnosis of the adnexal mass removed surgically within 120 days after the ultrasound examination. RESULTS: There were 242 (30%) malignancies. For 534 tumors judged to be certainly benign or certainly malignant by the ultrasound examiner the sensitivity and specificity of ultrasound examination and CA 125 (>/=35 U/mL indicating malignancy) were 97% vs. 86% (95% CI of difference, 4.7-17.2) and 99% vs. 79% (95% CI of difference, 15.7-24.2); for 209 tumors judged probably benign or probably malignant, sensitivity and specificity were 81% vs. 57% (95% CI of difference, 12.3-36.0) and 91% vs. 74% (95% CI of difference, 8.5-25.7); for 66 tumors that were difficult to classify, sensitivity and specificity were 57% vs. 39% (95% CI of difference, -9.7 to 41.1) and 74% vs. 67% (95% CI of difference, -14.6 to 27.7). Diagnostic performance deteriorated when CA 125 was used as a second-stage test after ultrasound examination. CONCLUSIONS: Specialist ultrasound examination is superior to CA 125 for preoperative discrimination between benign and malignant adnexal masses, irrespective of the diagnostic confidence of the ultrasound examiner; adding CA 125 to ultrasound does not improve diagnostic performance. Our results indicate that greater investment in education and training in gynecological ultrasound imaging would be of value. Copyright (c) 2009 ISUOG. Published by John Wiley & Sons, Ltd.
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87.
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88.
  • Van Belle, Vanya M. C. A., et al. (författare)
  • A Mathematical Model for Interpretable Clinical Decision Support with Applications in Gynecology
  • 2012
  • Ingår i: PLoS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 7:3
  • Tidskriftsartikel (refereegranskat)abstract
    • Background: Over time, methods for the development of clinical decision support (CDS) systems have evolved from interpretable and easy-to-use scoring systems to very complex and non-interpretable mathematical models. In order to accomplish effective decision support, CDS systems should provide information on how the model arrives at a certain decision. To address the issue of incompatibility between performance, interpretability and applicability of CDS systems, this paper proposes an innovative model structure, automatically leading to interpretable and easily applicable models. The resulting models can be used to guide clinicians when deciding upon the appropriate treatment, estimating patient-specific risks and to improve communication with patients. Methods and Findings: We propose the interval coded scoring (ICS) system, which imposes that the effect of each variable on the estimated risk is constant within consecutive intervals. The number and position of the intervals are automatically obtained by solving an optimization problem, which additionally performs variable selection. The resulting model can be visualised by means of appealing scoring tables and color bars. ICS models can be used within software packages, in smartphone applications, or on paper, which is particularly useful for bedside medicine and home-monitoring. The ICS approach is illustrated on two gynecological problems: diagnosis of malignancy of ovarian tumors using a dataset containing 3,511 patients, and prediction of first trimester viability of pregnancies using a dataset of 1,435 women. Comparison of the performance of the ICS approach with a range of prediction models proposed in the literature illustrates the ability of ICS to combine optimal performance with the interpretability of simple scoring systems. Conclusions: The ICS approach can improve patient-clinician communication and will provide additional insights in the importance and influence of available variables. Future challenges include extensions of the proposed methodology towards automated detection of interaction effects, multi-class decision support systems, prognosis and high-dimensional data.
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89.
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90.
  • Van Calster, Ben, et al. (författare)
  • Polytomous diagnosis of ovarian tumors as benign, borderline, primary invasive or metastatic: development and validation of standard and kernel-based risk prediction models
  • 2010
  • Ingår i: BMC Medical Research Methodology. - : Springer Science and Business Media LLC. - 1471-2288. ; 10
  • Tidskriftsartikel (refereegranskat)abstract
    • Background: Hitherto, risk prediction models for preoperative ultrasound-based diagnosis of ovarian tumors were dichotomous (benign versus malignant). We develop and validate polytomous models (models that predict more than two events) to diagnose ovarian tumors as benign, borderline, primary invasive or metastatic invasive. The main focus is on how different types of models perform and compare. Methods: A multi-center dataset containing 1066 women was used for model development and internal validation, whilst another multi-center dataset of 1938 women was used for temporal and external validation. Models were based on standard logistic regression and on penalized kernel-based algorithms (least squares support vector machines and kernel logistic regression). We used true polytomous models as well as combinations of dichotomous models based on the 'pairwise coupling' technique to produce polytomous risk estimates. Careful variable selection was performed, based largely on cross-validated c-index estimates. Model performance was assessed with the dichotomous c-index (i.e. the area under the ROC curve) and a polytomous extension, and with calibration graphs. Results: For all models, between 9 and 11 predictors were selected. Internal validation was successful with polytomous c-indexes between 0.64 and 0.69. For the best model dichotomous c-indexes were between 0.73 (primary invasive vs metastatic) and 0.96 (borderline vs metastatic). On temporal and external validation, overall discrimination performance was good with polytomous c-indexes between 0.57 and 0.64. However, discrimination between primary and metastatic invasive tumors decreased to near random levels. Standard logistic regression performed well in comparison with advanced algorithms, and combining dichotomous models performed well in comparison with true polytomous models. The best model was a combination of dichotomous logistic regression models. This model is available online. Conclusions: We have developed models that successfully discriminate between benign, borderline, and invasive ovarian tumors. Methodologically, the combination of dichotomous models was an interesting approach to tackle the polytomous problem. Standard logistic regression models were not outperformed by regularized kernel-based alternatives, a finding to which the careful variable selection procedure will have contributed. The random discrimination between primary and metastatic invasive tumors on temporal/external validation demonstrated once more the necessity of validation studies.
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