| 91. |
- Van Calster, Ben, et al.
(författare)
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Evaluating the risk of ovarian cancer before surgery using the ADNEX model to differentiate between benign, borderline, early and advanced stage invasive, and secondary metastatic tumours: prospective multicentre diagnostic study.
- 2014
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Ingår i: BMJ: British Medical Journal. - : BMJ. - 1756-1833. ; 349, s. 5920-5920
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Tidskriftsartikel (refereegranskat)abstract
- To develop a risk prediction model to preoperatively discriminate between benign, borderline, stage I invasive, stage II-IV invasive, and secondary metastatic ovarian tumours.
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| 92. |
- Van Calster, Ben, et al.
(författare)
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Polytomous diagnosis of ovarian tumors as benign, borderline, primary invasive or metastatic: development and validation of standard and kernel-based risk prediction models
- 2010
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Ingår i: BMC Medical Research Methodology. - : Springer Science and Business Media LLC. - 1471-2288. ; 10
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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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| 93. |
- Van Calster, Ben, et al.
(författare)
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Validation of models to diagnose ovarian cancer in patients managed surgically or conservatively : multicentre cohort study
- 2020
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Ingår i: BMJ (Clinical research ed.). - : BMJ. - 1756-1833. ; 370
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Tidskriftsartikel (refereegranskat)abstract
- OBJECTIVE: To evaluate the performance of diagnostic prediction models for ovarian malignancy in all patients with an ovarian mass managed surgically or conservatively. DESIGN: Multicentre cohort study. SETTING: 36 oncology referral centres (tertiary centres with a specific gynaecological oncology unit) or other types of centre. PARTICIPANTS: Consecutive adult patients presenting with an adnexal mass between January 2012 and March 2015 and managed by surgery or follow-up. MAIN OUTCOME MEASURES: Overall and centre specific discrimination, calibration, and clinical utility of six prediction models for ovarian malignancy (risk of malignancy index (RMI), logistic regression model 2 (LR2), simple rules, simple rules risk model (SRRisk), assessment of different neoplasias in the adnexa (ADNEX) with or without CA125). ADNEX allows the risk of malignancy to be subdivided into risks of a borderline, stage I primary, stage II-IV primary, or secondary metastatic malignancy. The outcome was based on histology if patients underwent surgery, or on results of clinical and ultrasound follow-up at 12 (±2) months. Multiple imputation was used when outcome based on follow-up was uncertain. RESULTS: The primary analysis included 17 centres that met strict quality criteria for surgical and follow-up data (5717 of all 8519 patients). 812 patients (14%) had a mass that was already in follow-up at study recruitment, therefore 4905 patients were included in the statistical analysis. The outcome was benign in 3441 (70%) patients and malignant in 978 (20%). Uncertain outcomes (486, 10%) were most often explained by limited follow-up information. The overall area under the receiver operating characteristic curve was highest for ADNEX with CA125 (0.94, 95% confidence interval 0.92 to 0.96), ADNEX without CA125 (0.94, 0.91 to 0.95) and SRRisk (0.94, 0.91 to 0.95), and lowest for RMI (0.89, 0.85 to 0.92). Calibration varied among centres for all models, however the ADNEX models and SRRisk were the best calibrated. Calibration of the estimated risks for the tumour subtypes was good for ADNEX irrespective of whether or not CA125 was included as a predictor. Overall clinical utility (net benefit) was highest for the ADNEX models and SRRisk, and lowest for RMI. For patients who received at least one follow-up scan (n=1958), overall area under the receiver operating characteristic curve ranged from 0.76 (95% confidence interval 0.66 to 0.84) for RMI to 0.89 (0.81 to 0.94) for ADNEX with CA125. CONCLUSIONS: Our study found the ADNEX models and SRRisk are the best models to distinguish between benign and malignant masses in all patients presenting with an adnexal mass, including those managed conservatively. TRIAL REGISTRATION: ClinicalTrials.gov NCT01698632.
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| 94. |
- Van den Bosch, T., et al.
(författare)
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Detection of intracavitary uterine pathology using offline analysis of three-dimensional ultrasound volumes: interobserver agreement and diagnostic accuracy
- 2012
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Ingår i: Ultrasound in Obstetrics & Gynecology. - : Wiley. - 1469-0705 .- 0960-7692. ; 40:4, s. 459-463
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Tidskriftsartikel (refereegranskat)abstract
- Objective To estimate the diagnostic accuracy and interobserver agreement in predicting intracavitary uterine pathology at offline analysis of three-dimensional (3D) ultrasound volumes of the uterus. Methods 3D volumes (unenhanced ultrasound and gel infusion sonography with and without power Doppler, i.e. four volumes per patient) of 75 women presenting with abnormal uterine bleeding at a bleeding clinic were assessed offline by six examiners. The sonologists were asked to provide a tentative diagnosis. A histological diagnosis was obtained by hysteroscopy with biopsy or operative hysteroscopy. Proliferative, secretory or atrophic endometrium was classified as normal histology; endometrial polyps, intracavitary myomas, endometrial hyperplasia and endometrial cancer were classified as abnormal histology. The diagnostic accuracy of the six sonologists with regard to normal/abnormal histology and interobserver agreement were estimated. Results Intracavitary pathology was diagnosed at histology in 39% of patients. Agreement between the ultrasound diagnosis and the histological diagnosis (normal vs abnormal) ranged from 67 to 83% for the six sonologists. In 45% of cases all six examiners agreed with regard to the presence/absence of intracavitary pathology. The percentage agreement between any two examiners ranged from 65 to 91% (Cohen's ?, 0.310.81). The Schouten ? for all six examiners was 0.51 (95% CI, 0.400.62), while the highest Schouten ? for any three examiners was 0.69. Conclusion When analyzing stored 3D ultrasound volumes, agreement between sonologists with regard to classifying the endometrium/uterine cavity as normal or abnormal as well as the diagnostic accuracy varied substantially. Possible actions to improve interobserver agreement and diagnostic accuracy include optimization of image quality and the use of a consistent technique for analyzing the 3D volumes. Copyright (c) 2012 ISUOG. Published by John Wiley & Sons, Ltd.
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| 95. |
- Van den Bosch, T., et al.
(författare)
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Effect of gel-instillation sonography on Doppler ultrasound findings in endometrial polyps
- 2011
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Ingår i: Ultrasound in Obstetrics & Gynecology. - : Wiley. - 1469-0705 .- 0960-7692. ; 38:3, s. 355-359
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Tidskriftsartikel (refereegranskat)abstract
- Objective Saline infusion sonohysterography has been reported to suppress the color signal within the endometrium at color or power Doppler evaluation. The aim of this study was to evaluate if gel-instillation sonography (GIS) affects the power Doppler signal in patients with endometrial polyps. Methods Ultrasound volumes of the uterus, obtained by three-dimensional ultrasound imaging of 25 women with histologically confirmed endometrial polyps, were assessed offline by six gynecologists with a special interest in gynecological ultrasound. Each woman contributed four volumes: one gray-scale volume and one power Doppler volume before GIS, and one gray-scale volume and one power Doppler volume at GIS. Power Doppler features before and after gel infusion were compared. Results At unenhanced ultrasound a pedicle artery was seen in 27-46% of cases, whereas, after gel infusion the examiners reported a pedicle artery in 30-46% of cases (Exact McNemar's test P-values ranged from 0.50 to 1.00). The level of agreement between unenhanced ultrasound and GIS ranged from 59 to 91% (Cohen's kappa values ranged from 0.17 to 0.79). There was no tendency for a pedicle artery to be identified less often at GIS than before gel instillation. Conclusion Gel infusion does not affect the power Doppler signal in patients with endometrial polyps. Copyright. (C) 2011 ISUOG. Published by John Wiley & Sons, Ltd.
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| 96. |
- 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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| 97. |
- Van Holsbeke, C., et al.
(författare)
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Prospective external validation of the 'ovarian crescent sign' as a single ultrasound parameter to distinguish between benign and malignant adnexal pathology
- 2010
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Ingår i: Ultrasound in Obstetrics & Gynecology. - : Wiley. - 1469-0705 .- 0960-7692. ; 36:1, s. 81-87
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Tidskriftsartikel (refereegranskat)abstract
- Objective To determine the sensitivity and specificity of the 'ovarian crescent sign' (OCS) - a rim of normal ovarian tissue seen adjacent to an ipsilateral adnexal mass as a sonographic feature to discriminate between benign and malignant adnexal masses. Methods The patients included were a subgroup of patients participating in the International Ovarian Tumor Analysis (IOTA) Phase 2 study, which is an international multicenter study. The subgroup comprised 1938 patients, with an adnexal mass, recruited from 19 ultrasound centers in different countries. All patients were scanned using the same standardized ultrasound protocol. Information on more than 40 demographic and ultrasound variables were collected, but the evaluation of the OCS was optional. Only patients from centers that had evaluated the OCS in >= 90% of their cases were included. The gold standard was the histological diagnosis of the adnexal mass. The ability of the OCS to discriminate between borderline or invasively malignant vs. benign adnexal masses, as well as between invasively malignant vs. other (benign and borderline) tumors, was determined and compared with the performance of subjective evaluation of ultrasound findings by the ultrasound examiner. Results The OCS was evaluated in 1377 adnexal masses from 12 centers, 938 (68%) masses being benign, 86 (6%) borderline, 305 (22%) primary invasive and 48 (3%) metastases. The OCS was present in 398 (42%) of 938 benign masses, in 14 (16%) of 86 borderline tumors, in 18 (6%) of 305 primary invasive tumors (one malignant struma ovarii, one uterine clear cell adenocarcinoma and 16 epithelial carcinomas, i.e. four Stage I and 12 Stage II-IV) and in two (4%) of 48 ovarian metastases. Hence, the sensitivity and specificity for absent OCS to identify a malignancy was 92% and 42%, respectively, and the positive and negative likelihood ratios (LR+ and LR-, respectively) were 1.60 and 0.18. Subjective impression performed significantly better than the OCS. Sensitivity and specificity were 90% and 92%, respectively, LR+ was 11.0 and LR- was 0.10. For discrimination between invasive vs. benign or borderline tumors, the sensitivity for absent OCS was 94%, the specificity was 40%, the LR+ was 1.58 and the LR- was 0.14. Conclusion This study confirms previous reports that the presence of the OCS decreases the likelihood of invasive malignancy in adnexal masses. However it is a poor discriminator between benign and malignant adnexal masses. Copyright (C) 2010 ISUOG. Published by John Wiley & Sons, Ltd.
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| 98. |
- Van Holsbeke, Caroline, et al.
(författare)
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Ultrasound Experience Substantially Impacts on Diagnostic Performance and Confidence when Adnexal Masses Are Classified Using Pattern Recognition
- 2010
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Ingår i: Gynecologic and Obstetric Investigation. - : S. Karger AG. - 1423-002X .- 0378-7346. ; 69:3, s. 160-168
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Tidskriftsartikel (refereegranskat)abstract
- Aim: To determine how accurately and confidently examiners with different levels of ultrasound experience can classify adnexal masses as benign or malignant and suggest a specific histological diagnosis when evaluating ultrasound images using pattern recognition. Methods: Ultrasound images of selected adnexal masses were evaluated by 3 expert sonologists, 2 senior and 4 junior trainees. They were instructed to classify the masses using pattern recognition as benign or malignant, to state the level of confidence with which this classification was made and to suggest a specific histological diagnosis. Sensitivity, specificity, accuracy and positive and negative likelihood ratios (LR+ and LR-) with regard to malignancy were calculated. The area under the receiver operating characteristic curve (AUC) of pattern recognition was calculated by using six levels of diagnostic confidence. Results: 166 masses were examined, of which 42% were malignant. Sensitivity with regard to malignancy ranged from 80 to 86% for the experts, was 70 and 84% for the 2 senior trainees and ranged from 70 to 86% for the junior trainees. The specificity of the experts ranged from 79 to 91%, was 77 and 89% for the senior trainees and ranged from 59 to 83% for the junior trainees. The experts were uncertain about their diagnosis in 4-13% of the cases, the senior trainees in 15-20% and the junior trainees in 67-100% of the cases. The AUCs ranged from 0.861 to 0.922 for the experts, were 0.842 and 0.855 for the senior trainees, and ranged from 0.726 to 0.795 for the junior trainees. The experts suggested a correct specific histological diagnosis in 69-77% of the cases. All 6 trainees did so significantly less often (22-42% of the cases). Conclusion: Expert sonologists can accurately classify adnexal masses as benign or malignant and can successfully predict the specific histological diagnosis in many cases. Whilst less experienced operators perform reasonably well when predicting the benign or malignant nature of the mass, they do so with a very low level of diagnostic confidence and are unable to state the likely histology of a mass in most cases. Copyright (C) 2009 S. Karger AG, Basel
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| 99. |
- Wilkinson, Mark D., et al.
(författare)
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Comment : The FAIR Guiding Principles for scientific data management and stewardship
- 2016
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Ingår i: Scientific Data. - : Springer Science and Business Media LLC. - 2052-4463. ; 3
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Tidskriftsartikel (refereegranskat)abstract
- There is an urgent need to improve the infrastructure supporting the reuse of scholarly data. A diverse set of stakeholders-representing academia, industry, funding agencies, and scholarly publishers-have come together to design and jointly endorse a concise and measureable set of principles that we refer to as the FAIR Data Principles. The intent is that these may act as a guideline for those wishing to enhance the reusability of their data holdings. Distinct from peer initiatives that focus on the human scholar, the FAIR Principles put specific emphasis on enhancing the ability of machines to automatically find and use the data, in addition to supporting its reuse by individuals. This Comment is the first formal publication of the FAIR Principles, and includes the rationale behind them, and some exemplar implementations in the community.
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| 100. |
- Wurzbacher, Christian, 1980, et al.
(författare)
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High habitat-specificity in fungal communities in oligo-mesotrophic, temperate Lake Stechlin (North-East Germany)
- 2016
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Ingår i: MycoKeys. - : Pensoft Publishers. - 1314-4057 .- 1314-4049. ; 16, s. 17-44
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Tidskriftsartikel (refereegranskat)abstract
- Freshwater fungi are a poorly studied ecological group that includes a high taxonomic diversity. Most studies on aquatic fungal diversity have focused on single habitats, thus the linkage between habitat heterogeneity and fungal diversity remains largely unexplored. We took 216 samples from 54 locations representing eight different habitats in the meso-oligotrophic, temperate Lake Stechlin in North-East Germany. These included the pelagic and littoral water column, sediments, and biotic substrates. We performed high throughput sequencing using the Roche 454 platform, employing a universal eukaryotic marker region within the large ribosomal subunit (LSU) to compare fungal diversity, community structure, and species turnover among habitats. Our analysis recovered 1027 fungal OTUs (97% sequence similarity). Richness estimates were highest in the sediment, biofilms, and benthic samples (189–231 OTUs), intermediate in water samples (42–85 OTUs), and lowest in plankton samples (8 OTUs). NMDS grouped the eight studied habitats into six clusters, indicating that community composition was strongly influenced by turnover among habitats. Fungal communities exhibited changes at the phylum and order levels along three different substrate categories from littoral to pelagic habitats. The large majority of OTUs (> 75%) could not be classified below the order level due to the lack of aquatic fungal entries in public sequence databases. Our study provides a first estimate of lake-wide fungal diversity and highlights the important contribution of habitat heterogeneity to overall diversity and community composition. Habitat diversity should be considered in any sampling strategy aiming to assess the fungal diversity of a water body.
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