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1.
  • Schwartz, K. L., et al. (author)
  • Best practice guidance for antibiotic audit and feedback interventions in primary care: a modified Delphi study from the Joint Programming Initiative on Antimicrobial resistance: Primary Care Antibiotic Audit and Feedback Network (JPIAMR-PAAN)
  • 2023
  • In: Antimicrobial Resistance and Infection Control. - 2047-2994. ; 12:1
  • Journal article (peer-reviewed)abstract
    • BackgroundPrimary care is a critical partner for antimicrobial stewardship efforts given its high human antibiotic usage. Peer comparison audit and feedback (A & F) is often used to reduce inappropriate antibiotic prescribing. The design and implementation of A & F may impact its effectiveness. There are no best practice guidelines for peer comparison A & F in antibiotic prescribing in primary care.ObjectiveTo develop best practice guidelines for peer comparison A & F for antibiotic prescribing in primary care in high income countries by leveraging international expertise via the Joint Programming Initiative on Antimicrobial Resistance-Primary Care Antibiotic Audit and Feedback Network.MethodsWe used a modified Delphi process to achieve convergence of expert opinions on best practice statements for peer comparison A & F based on existing evidence and theory. Three rounds were performed, each with online surveys and virtual meetings to enable discussion and rating of each best practice statement. A five-point Likert scale was used to rate consensus with a median threshold score of 4 to indicate a consensus statement.ResultsThe final set of guidelines include 13 best practice statements in four categories: general considerations (n = 3), selecting feedback recipients (n = 1), data and indicator selection (n = 4), and feedback delivery (n = 5).ConclusionWe report an expert-derived best practice recommendations for designing and evaluating peer comparison A & F for antibiotic prescribing in primary care. These 13 statements can be used by A & F designers to optimize the impact of their quality improvement interventions, and improve antibiotic prescribing in primary care.
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2.
  • Verbakel, J. Y., et al. (author)
  • Validation of ultrasound strategies to assess tumor extension and to predict high-risk endometrial cancer in women from the prospective IETA (International Endometrial Tumor Analysis)-4 cohort
  • 2020
  • In: Ultrasound in Obstetrics and Gynecology. - : Wiley. - 0960-7692 .- 1469-0705. ; 55:1, s. 115-124
  • Journal article (peer-reviewed)abstract
    • Objectives: To compare the performance of ultrasound measurements and subjective ultrasound assessment (SA) in detecting deep myometrial invasion (MI) and cervical stromal invasion (CSI) in women with endometrial cancer, overall and according to whether they had low- or high-grade disease separately, and to validate published measurement cut-offs and prediction models to identify MI, CSI and high-risk disease (Grade-3 endometrioid or non-endometrioid cancer and/or deep MI and/or CSI). Methods: The study comprised 1538 patients with endometrial cancer from the International Endometrial Tumor Analysis (IETA)-4 prospective multicenter study, who underwent standardized expert transvaginal ultrasound examination. SA and ultrasound measurements were used to predict deep MI and CSI. We assessed the diagnostic accuracy of the tumor/uterine anteroposterior (AP) diameter ratio for detecting deep MI and that of the distance from the lower margin of the tumor to the outer cervical os (Dist-OCO) for detecting CSI. We also validated two two-step strategies for the prediction of high-risk cancer; in the first step, biopsy-confirmed Grade-3 endometrioid or mucinous or non-endometrioid cancers were classified as high-risk cancer, while the second step encompassed the application of a mathematical model to classify the remaining tumors. The ‘subjective prediction model’ included biopsy grade (Grade 1 vs Grade 2) and subjective assessment of deep MI or CSI (presence or absence) as variables, while the ‘objective prediction model’ included biopsy grade (Grade 1 vs Grade 2) and minimal tumor-free margin. The predictive performance of the two two-step strategies was compared with that of simply classifying patients as high risk if either deep MI or CSI was suspected based on SA or if biopsy showed Grade-3 endometrioid or mucinous or non-endometrioid histotype (i.e. combining SA with biopsy grade). Histological assessment from hysterectomy was considered the reference standard. Results: In 1275 patients with measurable lesions, the sensitivity and specificity of SA for detecting deep MI was 70% and 80%, respectively, in patients with a Grade-1 or -2 endometrioid or mucinous tumor vs 76% and 64% in patients with a Grade-3 endometrioid or mucinous or a non-endometrioid tumor. The corresponding values for the detection of CSI were 51% and 94% vs 50% and 91%. Tumor AP diameter and tumor/uterine AP diameter ratio showed the best performance for predicting deep MI (area under the receiver–operating characteristics curve (AUC) of 0.76 and 0.77, respectively), and Dist-OCO had the best performance for predicting CSI (AUC, 0.72). The proportion of patients classified correctly as having high-risk cancer was 80% when simply combining SA with biopsy grade vs 80% and 74% when using the subjective and objective two-step strategies, respectively. The subjective and objective models had an AUC of 0.76 and 0.75, respectively, when applied to Grade-1 and -2 endometrioid tumors. Conclusions: In the hands of experienced ultrasound examiners, SA was superior to ultrasound measurements for the prediction of deep MI and CSI of endometrial cancer, especially in patients with a Grade-1 or -2 tumor. The mathematical models for the prediction of high-risk cancer performed as expected. The best strategies for predicting high-risk endometrial cancer were combining SA with biopsy grade and the subjective two-step strategy, both having an accuracy of 80%.
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3.
  • Eriksson, L. S.E., et al. (author)
  • Ultrasound-based risk model for preoperative prediction of lymph-node metastases in women with endometrial cancer : model-development study
  • 2020
  • In: Ultrasound in Obstetrics and Gynecology. - : Wiley. - 0960-7692 .- 1469-0705. ; 56:3, s. 443-452
  • Journal article (peer-reviewed)abstract
    • Objective: To develop a preoperative risk model, using endometrial biopsy results and clinical and ultrasound variables, to predict the individual risk of lymph-node metastases in women with endometrial cancer. Methods: A mixed-effects logistic regression model for prediction of lymph-node metastases was developed in 1501 prospectively included women with endometrial cancer undergoing transvaginal ultrasound examination before surgery, from 16 European centers. Missing data, including missing lymph-node status, were imputed. Discrimination, calibration and clinical utility of the model were evaluated using leave-center-out cross validation. The predictive performance of the model was compared with that of risk classification from endometrial biopsy alone (high-risk defined as endometrioid cancer Grade 3/non-endometrioid cancer) or combined endometrial biopsy and ultrasound (high-risk defined as endometrioid cancer Grade 3/non-endometrioid cancer/deep myometrial invasion/cervical stromal invasion/extrauterine spread). Results: Lymphadenectomy was performed in 691 women, of whom 127 had lymph-node metastases. The model for prediction of lymph-node metastases included the predictors age, duration of abnormal bleeding, endometrial biopsy result, tumor extension and tumor size according to ultrasound and undefined tumor with an unmeasurable endometrium. The model's area under the curve was 0.73 (95% CI, 0.68–0.78), the calibration slope was 1.06 (95% CI, 0.79–1.34) and the calibration intercept was 0.06 (95% CI, –0.15 to 0.27). Using a risk threshold for lymph-node metastases of 5% compared with 20%, the model had, respectively, a sensitivity of 98% vs 48% and specificity of 11% vs 80%. The model had higher sensitivity and specificity than did classification as high-risk, according to endometrial biopsy alone (50% vs 35% and 80% vs 77%, respectively) or combined endometrial biopsy and ultrasound (80% vs 75% and 53% vs 52%, respectively). The model's clinical utility was higher than that of endometrial biopsy alone or combined endometrial biopsy and ultrasound at any given risk threshold. Conclusions: Based on endometrial biopsy results and clinical and ultrasound characteristics, the individual risk of lymph-node metastases in women with endometrial cancer can be estimated reliably before surgery. The model is superior to risk classification by endometrial biopsy alone or in combination with ultrasound.
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4.
  • Van Den Bosch, T., et al. (author)
  • Typical ultrasound features of various endometrial pathologies described using International Endometrial Tumor Analysis (IETA) terminology in women with abnormal uterine bleeding
  • 2021
  • In: Ultrasound in Obstetrics and Gynecology. - : Wiley. - 0960-7692 .- 1469-0705. ; 57:1, s. 164-172
  • Journal article (peer-reviewed)abstract
    • Objective: To describe the ultrasound features of different endometrial and other intracavitary pathologies inpre- and postmenopausal women presenting with abnormal uterine bleeding, using the International Endometrial Tumor Analysis (IETA) terminology. Methods: This was a prospective observational multicenter study of consecutive women presenting with abnormal uterine bleeding. Unenhanced sonography with color Doppler and fluid-instillation sonography were performed. Endometrial sampling was performed according to each center's local protocol. The histological endpoints were cancer, atypical endometrial hyperplasia/endometrioid intraepithelial neoplasia (EIN), endometrial atrophy, proliferative or secretory endometrium, endometrial hyperplasia without atypia, endometrial polyp, intracavitary leiomyoma and other. For fluid-instillation sonography, the histological endpoints were endometrial polyp, intracavitary leiomyoma and cancer. For each histological endpoint, we report typical ultrasound features using the IETA terminology. Results: The database consisted of 2856 consecutive women presenting with abnormal uterine bleeding. Unenhanced sonography with color Doppler was performed in all cases and fluid-instillation sonography in 1857. In 2216 women, endometrial histology was available, and these comprised the study population. Median age was 49 years (range, 19–92 years), median parity was 2 (range, 0–10) and median body mass index was 24.9 kg/m2 (range, 16.0–72.1 kg/m2). Of the study population, 843 (38.0%) women were postmenopausal. Endometrial polyps were diagnosed in 751 (33.9%) women, intracavitary leiomyomas in 223 (10.1%) and endometrial cancer in 137 (6.2%). None (0% (95% CI, 0.0–5.5%)) of the 66 women with endometrial thickness < 3 mm had endometrial cancer or atypical hyperplasia/EIN. Endometrial cancer or atypical hyperplasia/EIN was found in three of 283 (1.1% (95% CI, 0.4–3.1%)) endometria with a three-layer pattern, in three of 459 (0.7% (95% CI, 0.2–1.9%)) endometria with a linear endometrial midline and in five of 337 (1.5% (95% CI, 0.6–3.4%)) cases with a single vessel without branching on unenhanced ultrasound. Conclusions: The typical ultrasound features of endometrial cancer, polyps, hyperplasia and atrophy and intracavitary leiomyomas, are described using the IETA terminology. The detection of some easy-to-assess IETA features (i.e. endometrial thickness < 3 mm, three-layer pattern, linear midline and single vessel without branching) makes endometrial cancer unlikely.
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