Validation of ADNEX and IOTA two-step strategy and estimation of risk of complications during follow-up of adnexal masses in low-risk population.

OBJECTIVES: The aim is to evaluate the ability of the Assessment of Different NEoplasias in the adneXa model (ADNEX) and the International Ovarian Tumour Analysis (IOTA) two-step strategy to predict malignancy in adnexal masses detected in an outpatient low-risk setting, and to estimate the risk of complications in masses with benign ultrasound morphology managed with clinical and ultrasound follow-up. METHODS: This single center (Hospital Universitari Dexeus Barcelona) study was performed using interim data of the ongoing prospective observational IOTA phase 5 study. The primary aim of the IOTA 5 study is to describe the cumulative incidence of complications during follow-up of adnexal masses classified as benign on ultrasound. Consecutive patients with adnexal masses detected between June 2012 and September 2016 in a private center offering screening for gynecological cancers were included and followed-up until February 2020. Tumors were classified as benign or malignant based on histology (if patients underwent surgery) or outcome of clinical and ultrasound follow-up at 12 (±2) months. Multiple imputation was used when follow-up information was uncertain. The ability of the ADNEX model without CA125 and of the IOTA two-step strategy to distinguish benign from malignant masses was evaluated retrospectively using the prospectively collected data. We describe performance as discrimination (area under the receiver operating characteristic curve, AUC), calibration, classification (sensitivity and specificity) and clinical utility (Net Benefit). In the group of patients with a benign looking mass selected for conservative management we evaluated the occurrence of spontaneous resolution or any mass complication during the first 5 years of follow-up by assessing the cumulative incidence for malignancy, torsion, cyst rupture, or minor mass complications (inflammation, infection, or adhesions) and the time to occurrence of an event. RESULTS: A total of 2654 patients were recruited to the study. After application of exclusion criteria, 2039 patients with a newly detected mass were included for the model validation. 1684 (82.6%) masses were benign, 49 (2.4%) masses were malignant and for 306 (15.0%) masses the outcome was uncertain and imputed. The AUC was 0.95 (95% CI 0.89-0.98) for ADNEX and 0.94 (95% CI 0.88-0.97) for the two-step strategy. Calibration performance could not be meaningfully interpreted due to few malignancies resulting in very wide confidence intervals. The two-step strategy had better clinical utility than ADNEX at malignancy risk thresholds < 3%. 1472 (72%) patients had a mass judged to be benign based on pattern recognition by an experienced ultrasound examiner and were managed with clinical and ultrasound follow-up. In this group, the 5-year cumulative incidence was 66% for spontaneous resolution of the mass (95% CI 63-69), 0% for torsion (95%CI 0-0.002), 0.1% for cyst rupture (<0.1-0.6), 0.2% for a borderline tumor (<0.1-0.6), and 0.2% (0.1-0.6) for invasive malignancy. CONCLUSIONS: The ADNEX model and IOTA two-step strategy performed well to distinguish benign from malignant adnexal masses detected in a low-risk population. Conservative management is safe for masses with benign ultrasound appearance in such a population. This article is protected by copyright. All rights reserved.

Updating M6 pregnancy of unknown location risk-prediction model including evaluation of clinical factors.

OBJECTIVES: Ectopic pregnancy (EP) is a major high-risk outcome following a pregnancy of unknown location (PUL) classification. Biochemical markers are used to triage PUL as high vs low risk to guide appropriate follow-up. The M6 model is currently the best risk-prediction model. We aimed to update the M6 model and evaluate whether performance can be improved by including clinical factors. METHODS: This prospective cohort study recruited consecutive PUL between January 2015 and January 2017 at eight units (Phase 1), with two centers continuing recruitment between January 2017 and March 2021 (Phase 2). Serum samples were collected routinely and sent for ß-human chorionic gonadotropin (ß-hCG) and progesterone measurement. Clinical factors recorded were maternal age, pain score, bleeding score and history of EP. Based on transvaginal ultrasonography and/or biochemical confirmation during follow-up, PUL were classified subsequently as failed PUL (FPUL), intrauterine pregnancy (IUP) or EP (including persistent PUL (PPUL)). The M6 models with (M6P ) and without (M6NP ) progesterone were refitted and extended with clinical factors. Model validation was performed using internal-external cross-validation (IECV) (Phase 1) and temporal external validation (EV) (Phase 2). Missing values were handled using multiple imputation. RESULTS: Overall, 5473 PUL were recruited over both phases. A total of 709 PUL were excluded because maternal age was < 16 years or initial ß-hCG was ≤ 25 IU/L, leaving 4764 (87%) PUL for analysis (2894 in Phase 1 and 1870 in Phase 2). For the refitted M6P model, the area under the receiver-operating-characteristics curve (AUC) for EP/PPUL vs IUP/FPUL was 0.89 for IECV and 0.84-0.88 for EV, with respective sensitivities of 94% and 92-93%. For the refitted M6NP model, the AUCs were 0.85 for IECV and 0.82-0.86 for EV, with respective sensitivities of 92% and 93-94%. Calibration performance was good overall, but with heterogeneity between centers. Net Benefit confirmed clinical utility. The change in AUC when M6P was extended to include maternal age, bleeding score and history of EP was between -0.02 and 0.01, depending on center and phase. The corresponding change in AUC when M6NP was extended was between -0.01 and 0.03. At the 5% threshold to define high risk of EP/PPUL, extending M6P altered sensitivity by -0.02 to -0.01, specificity by 0.03 to 0.04 and Net Benefit by -0.005 to 0.006. Extending M6NP altered sensitivity by -0.03 to -0.01, specificity by 0.05 to 0.07 and Net Benefit by -0.005 to 0.006. CONCLUSIONS: The updated M6 model offers accurate diagnostic performance, with excellent sensitivity for EP. Adding clinical factors to the model improved performance in some centers, especially when progesterone levels were not suitable or unavailable. © 2023 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.

Benign descriptors and ADNEX in two-step strategy to estimate risk of malignancy in ovarian tumors: retrospective validation in IOTA5 multicenter cohort.

OBJECTIVE: Previous work has suggested that the ultrasound-based benign simple descriptors (BDs) can reliably exclude malignancy in a large proportion of women presenting with an adnexal mass. This study aimed to validate a modified version of the BDs and to validate a two-step strategy to estimate the risk of malignancy, in which the modified BDs are followed by the Assessment of Different NEoplasias in the adneXa (ADNEX) model if modified BDs do not apply. METHODS: This was a retrospective analysis using data from the 2-year interim analysis of the International Ovarian Tumor Analysis (IOTA) Phase-5 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 1 year of follow-up. Multiple imputation was used when outcome based on follow-up was uncertain according to predefined criteria. RESULTS: A total of 8519 patients were recruited at 36 centers between 2012 and 2015. We excluded patients who were already in follow-up at recruitment and all patients from 19 centers that did not fulfil our criteria for good-quality surgical and follow-up data, leaving 4905 patients across 17 centers for statistical analysis. Overall, 3441 (70%) tumors were benign, 978 (20%) malignant and 486 (10%) uncertain. The modified BDs were applicable in 1798/4905 (37%) tumors, of which 1786 (99.3%) were benign. The two-step strategy based on ADNEX without CA125 had an area under the receiver-operating-characteristics curve (AUC) of 0.94 (95% CI, 0.92-0.96). 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 modified 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. © 2022 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.

External validation of models to predict the outcome of pregnancies of unknown location: a multicentre cohort study.

OBJECTIVE: To validate externally five approaches to predict ectopic pregnancy (EP) in pregnancies of unknown location (PUL): the M6P and M6NP risk models, the two-step triage strategy (2ST, which incorporates M6P), the M4 risk model, and beta human chorionic gonadotropin ratio cut-offs (BhCG-RC). DESIGN: Secondary analysis of a prospective cohort study. SETTING: Eight UK early pregnancy assessment units. POPULATION: Women presenting with a PUL and BhCG >25 IU/l. METHODS: Women were managed using the 2ST protocol: PUL were classified as low risk of EP if presenting progesterone ≤2 nmol/l; the remaining cases returned 2 days later for triage based on M6P. EP risk ≥5% was used to classify PUL as high risk. Missing values were imputed, and predictions for the five approaches were calculated post hoc. We meta-analysed centre-specific results. MAIN OUTCOME MEASURES: Discrimination, calibration and clinical utility (decision curve analysis) for predicting EP. RESULTS: Of 2899 eligible women, the primary analysis excluded 297 (10%) women who were lost to follow up. The area under the ROC curve for EP was 0.89 (95% CI 0.86-0.91) for M6P, 0.88 (0.86-0.90) for 2ST, 0.86 (0.83-0.88) for M6NP and 0.82 (0.78-0.85) for M4. Sensitivities for EP were 96% (M6P), 94% (2ST), 92% (N6NP), 80% (M4) and 58% (BhCG-RC); false-positive rates were 35%, 33%, 39%, 24% and 13%. M6P and 2ST had the best clinical utility and good overall calibration, with modest variability between centres. CONCLUSIONS: 2ST and M6P performed best for prediction and triage in PUL. TWEETABLE ABSTRACT: The M6 model, as part of a two-step triage strategy, is the best approach to characterise and triage PULs.

Differences in post-traumatic stress, anxiety and depression following miscarriage or ectopic pregnancy between women and their partners: multicenter prospective cohort study.

OBJECTIVES: To investigate and compare post-traumatic stress (PTS), depression and anxiety in women and their partners over a 9-month period following miscarriage or ectopic pregnancy. METHODS: This was a prospective cohort study. Consecutive women and their partners were approached in the early pregnancy units of three hospitals in central London. At 1, 3 and 9 months after early pregnancy loss, recruits were e-mailed links to surveys containing the Hospital Anxiety and Depression Scale and the Post-traumatic Stress Diagnostic Scale. The proportion of participants meeting the screening criteria for moderate or severe anxiety or depression and PTS was assessed. Mixed-effects logistic regression was used to analyze differences between women and their partners and their evolution over time. RESULTS: In total, 386 partners were approached after the woman in whom the early pregnancy loss had been diagnosed consented to participate, and 192 couples were recruited. All partners were male. Response rates were 60%, 48% and 39% for partners and 78%, 70% and 59% for women, at 1, 3 and 9 months, respectively. Of the partners, 7% met the criteria for PTS at 1 month, 8% at 3 months and 4% at 9 months, compared with 34%, 26% and 21% of women, respectively. Partners also experienced lower rates of moderate/severe anxiety (6% vs 30% at 1 month, 9% vs 25% at 3 months and 6% vs 22% at 9 months) and moderate/severe depression (2% vs 10% at 1 month, 5% vs 8% at 3 months and 1% vs 7% at 9 months). The odds ratios for psychological morbidity in partners vs women after 1 month were 0.02 (95% CI, 0.004-0.12) for PTS, 0.05 (95% CI, 0.01-0.19) for moderate/severe anxiety and 0.15 (95% CI, 0.02-0.96) for moderate/severe depression. Morbidity for each outcome decreased modestly over time, without strong evidence of a different evolution between women and their partners. CONCLUSIONS: Some partners report clinically relevant levels of PTS, anxiety and depression after pregnancy loss, though to a far lesser extent than women physically experiencing the loss. © 2020 International Society of Ultrasound in Obstetrics and Gynecology.

Typical ultrasound features of various endometrial pathologies described using International Endometrial Tumor Analysis (IETA) terminology in women with abnormal uterine bleeding.

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. Copyright © 2020 ISUOG. Published by John Wiley & Sons Ltd.

Assessment of protein biomarkers for preoperative differential diagnosis between benign and malignant ovarian tumors.

OBJECTIVE: To estimate the diagnostic value of tumor and immune related proteins in the discrimination between benign and malignant adnexal masses, and between different subgroups of tumors. METHODS: In this exploratory diagnostic study, 254 patients with an adnexal mass scheduled for surgery were consecutively enrolled at the University Hospitals Leuven (128 benign, 42 borderline, 22 stage I, 55 stage II-IV, and 7 secondary metastatic tumors). The quantification of 33 serum proteins was done preoperatively, using multiplex high throughput immunoassays (Luminex) and electrochemiluminescence immuno-assay (ECLIA). We calculated univariable areas under the Receiver Operating Characteristic Curves (AUCs). To discriminate malignant from benign tumors, multivariable ridge logistic regression with backward elimination was performed, using bootstrapping to validate the resulting AUCs. RESULTS: CA125 had the highest univariable AUC to discriminate malignant from benign tumors (0.85, 95% confidence interval 0.79-0.89). Combining CA125 with CA72.4 and HE4 increased the AUC to 0.87. For benign vs borderline tumors, CA125 had the highest univariable AUC (0.74). For borderline vs stage I malignancy, no proteins were promising. For stage I vs II-IV malignancy, CA125, HE4, CA72.4, CA15.3 and LAP had univariable AUCs ≥0.80. CONCLUSIONS: The results confirm the dominant role of CA125 for identifying malignancy, and suggest that other markers (HE4, CA72.4, CA15.3 and LAP) may help to distinguish between stage I and stage II-IV malignancies. However, further research is needed, also to investigate the added value over clinical and ultrasound predictors of malignancy, focusing on the differentiation between subtypes of malignancy.

Triaging women with pregnancy of unknown location using two-step protocol including M6 model: clinical implementation study.

OBJECTIVE: The M6 risk-prediction model was published as part of a two-step protocol using an initial progesterone level of ≤ 2 nmol/L to identify probable failing pregnancies (Step 1) followed by the M6 model (Step 2). The M6 model has been shown to have good triage performance for stratifying women with a pregnancy of unknown location (PUL) as being at low or high risk of harboring an ectopic pregnancy (EP). This study validated the triage performance of the two-step protocol in clinical practice by evaluating the number of protocol-related adverse events and how effectively patients were triaged. METHODS: This was a prospective multicenter interventional study of 3272 women with a PUL, carried out between January 2015 and January 2017 in four district general hospitals and four university teaching hospitals in the UK. The final pregnancy outcome was defined as: a failed PUL (FPUL), an intrauterine pregnancy (IUP) or an EP (including persistent PUL (PPUL)). FPUL and IUP were grouped as low-risk and EP/PPUL as high-risk PUL. Serum progesterone and human chorionic gonadotropin (hCG) levels were measured at presentation in all patients. If the initial progesterone level was ≤ 2 nmol/L, patients were discharged and were asked to have a follow-up urine pregnancy test in 2 weeks to confirm a negative result. If the progesterone level was > 2 nmol/L or a measurement had not been taken, hCG level was measured again at 48 h and results were entered into the M6 model. Patients were managed according to the outcome predicted by the protocol. Those classified as 'low risk, probable FPUL' were advised to perform a urine pregnancy test in 2 weeks and those classified as 'low risk, probable IUP' were invited for a scan a week later. When a woman with a PUL was classified as high risk (i.e. risk of EP ≥ 5%) she was reviewed clinically within 48 h. One center used a progesterone cut-off of ≤ 10 nmol/L and its data were analyzed separately. If the recommended management protocol was not adhered to, this was recorded as a protocol deviation and classified as: unscheduled visit for clinician reason, unscheduled visit for patient reason or incorrect timing of blood test or ultrasound scan. The classifications outlined in the UK Good Clinical Practice (GCP) guidelines were used to evaluate the incidence of adverse events. Data were analyzed using descriptive statistics. RESULTS: Of the 3272 women with a PUL, 2625 were included in the final analysis (317 met the exclusion criteria or were lost to follow-up, while 330 were evaluated using a progesterone cut-off of ≤ 10 nmol/L). Initial progesterone results were available for 2392 (91.1%) patients. In Step 1, 407 (15.5%) patients were classified as low risk (progesterone ≤ 2 nmol/L), of whom seven (1.7%) were ultimately diagnosed with an EP. In 279 of the remaining 2218 women with a PUL, the M6 model was not applied owing to protocol deviation or because the outcome was already known (usually on the basis of an ultrasound scan) before a second hCG reading was taken; of these patients, 30 were diagnosed with an EP. In Step 2, 1038 women with a PUL were classified as low risk, of whom eight (0.8%) had a final outcome of EP. Of 901 women classified as high risk at Step 2, 275 (30.5%) had an EP. Therefore, 275/320 (85.9%) EPs were correctly classified as high risk. Overall, 1445/2625 PUL (55.0%) were classified as low risk, of which 15 (1.0%) were EP. None of these cases resulted in a ruptured EP or significant clinical harm. Sixty-two women participating in the study had an adverse event, but no woman had a serious adverse event as defined in the UK GCP guidelines. CONCLUSIONS: This study has shown that the two-step protocol incorporating the M6 model effectively triaged the majority of women with a PUL as being at low risk of an EP, minimizing the follow-up required for these patients after just two visits. There were few misclassified EPs and none of these women came to significant clinical harm or suffered a serious adverse clinical event. The two-step protocol incorporating the M6 model is an effective and clinically safe way of rationalizing the management of women with a PUL. Copyright © 2019 ISUOG. Published by John Wiley & Sons Ltd.

Ultrasound-based risk model for preoperative prediction of lymph-node metastases in women with endometrial cancer: model-development study.

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. Copyright © 2019 ISUOG. Published by John Wiley & Sons Ltd.

Impact of predictor measurement heterogeneity across settings on the performance of prediction models: A measurement error perspective.

It is widely acknowledged that the predictive performance of clinical prediction models should be studied in patients that were not part of the data in which the model was derived. Out-of-sample performance can be hampered when predictors are measured differently at derivation and external validation. This may occur, for instance, when predictors are measured using different measurement protocols or when tests are produced by different manufacturers. Although such heterogeneity in predictor measurement between derivation and validation data is common, the impact on the out-of-sample performance is not well studied. Using analytical and simulation approaches, we examined out-of-sample performance of prediction models under various scenarios of heterogeneous predictor measurement. These scenarios were defined and clarified using an established taxonomy of measurement error models. The results of our simulations indicate that predictor measurement heterogeneity can induce miscalibration of prediction and affects discrimination and overall predictive accuracy, to extents that the prediction model may no longer be considered clinically useful. The measurement error taxonomy was found to be helpful in identifying and predicting effects of heterogeneous predictor measurements between settings of prediction model derivation and validation. Our work indicates that homogeneity of measurement strategies across settings is of paramount importance in prediction research.

Untapped potential of multicenter studies: a review of cardiovascular risk prediction models revealed inappropriate analyses and wide variation in reporting.

BACKGROUND: Clinical prediction models are often constructed using multicenter databases. Such a data structure poses additional challenges for statistical analysis (clustered data) but offers opportunities for model generalizability to a broad range of centers. The purpose of this study was to describe properties, analysis, and reporting of multicenter studies in the Tufts PACE Clinical Prediction Model Registry and to illustrate consequences of common design and analyses choices. METHODS: Fifty randomly selected studies that are included in the Tufts registry as multicenter and published after 2000 underwent full-text screening. Simulated examples illustrate some key concepts relevant to multicenter prediction research. RESULTS: Multicenter studies differed widely in the number of participating centers (range 2 to 5473). Thirty-nine of 50 studies ignored the multicenter nature of data in the statistical analysis. In the others, clustering was resolved by developing the model on only one center, using mixed effects or stratified regression, or by using center-level characteristics as predictors. Twenty-three of 50 studies did not describe the clinical settings or type of centers from which data was obtained. Four of 50 studies discussed neither generalizability nor external validity of the developed model. CONCLUSIONS: Regression methods and validation strategies tailored to multicenter studies are underutilized. Reporting on generalizability and potential external validity of the model lacks transparency. Hence, multicenter prediction research has untapped potential. REGISTRATION: This review was not registered.

Early-pregnancy events and subsequent antenatal, delivery and neonatal outcomes: prospective cohort study.

OBJECTIVE: To assess prospectively the association between pelvic pain, vaginal bleeding, and nausea and vomiting occurring in the first trimester of pregnancy and the incidence of later adverse pregnancy outcomes. METHODS: This was a prospective observational cohort study of consecutive women with confirmed intrauterine singleton pregnancy between 5 and 14 weeks' gestation recruited at Queen Charlotte's & Chelsea Hospital, London, UK, from March 2014 to March 2016. Serial ultrasound scans were performed in the first trimester. Participants completed validated symptom scores for vaginal bleeding, pelvic pain, and nausea and vomiting. The key symptom of interest was any pelvic pain and/or vaginal bleeding during the first trimester. Pregnancies were followed up until the final outcome was known. Antenatal, delivery and neonatal outcomes were obtained from hospital records. Logistic regression analysis was used to assess the association between first-trimester symptoms and pregnancy complications by calculating adjusted odds ratios (aOR) with correction for maternal age. RESULTS: Of 1003 women recruited, 847 pregnancies were included in the final analysis following exclusion of cases due to first-trimester miscarriage (n = 99), termination of pregnancy (n = 20), loss to follow-up (n = 32) or withdrawal from the study (n = 5). Adverse antenatal complications were observed in 166/645 (26%) women with pelvic pain and/or vaginal bleeding in the first trimester (aOR = 1.79; 95% CI, 1.17-2.76) and in 30/181 (17%) women with no symptoms. Neonatal complications were observed in 66/634 (10%) women with and 11/176 (6%) without pelvic pain and/or vaginal bleeding (aOR = 1.73; 95% CI, 0.89-3.36). Delivery complications were observed in 402/615 (65%) women with and 110/174 (63%) without pelvic pain and/or vaginal bleeding during the first trimester (aOR = 1.16; 95% CI, 0.81-1.65). For 18 of 20 individual antenatal complications evaluated, incidence was higher among women with pelvic pain and/or vaginal bleeding, despite the overall incidences being low. Nausea and vomiting in pregnancy showed little association with adverse pregnancy outcomes. CONCLUSIONS: Our study suggests that there is an increased incidence of antenatal complications in women experiencing pelvic pain and/or vaginal bleeding in the first trimester. This should be considered when advising women attending early-pregnancy units. Copyright © 2019 ISUOG. Published by John Wiley & Sons Ltd.

Diagnostic protocols for the management of pregnancy of unknown location: a systematic review and meta-analysis.

BACKGROUND: There is no international consensus on how to manage women with a pregnancy of unknown location (PUL). OBJECTIVES: To present a systematic quantitative review summarising the evidence related to management protocols for PUL. SEARCH STRATEGY: MEDLINE, COCHRANE and DARE databases were searched from 1 January 1984 to 31 January 2017. The primary outcome was accurate risk prediction of women initially diagnosed with a PUL having an ectopic pregnancy (high risk) as opposed to either a failed PUL or intrauterine pregnancy (low risk). SELECTION CRITERIA: All studies written in the English language, which were not case reports or series that assessed women classified as having a PUL at initial ultrasound. DATA COLLECTION AND ANALYSIS: Forty-three studies were included. QUADAS-2 criteria were used to assess the risk of bias. We used a novel, linear mixed-effects model and constructed summary receiver operating characteristic curves for the thresholds of interest. MAIN RESULTS: There was a high risk of differential verification bias in most studies. Meta-analyses of accuracy were performed on (i) single human chorionic gonadotrophin (hCG) cut-off levels, (ii) hCG ratio (hCG at 48 hours/initial hCG), (iii) single progesterone cut-off levels and (iv) the 'M4 model' (a logistic regression model based on the initial hCG and hCG ratio). For predicting an ectopic pregnancy, the areas under the curves (95% CI) for these four management protocols were as follows: (i) 0.42 (0.00-0.99), (ii) 0.69 (0.57-0.78), (iii) 0.69 (0.54-0.81) and (iv) 0.87 (0.83-0.91), respectively. CONCLUSIONS: The M4 model was the best available method for predicting a final outcome of ectopic pregnancy. Developing and validating risk prediction models may optimise the management of PUL. TWEETABLE ABSTRACT: Pregnancy of unknown location meta-analysis: M4 model has best test performance to predict ectopic pregnancy.

Random-effects meta-analysis of the clinical utility of tests and prediction models.

The use of data from multiple studies or centers for the validation of a clinical test or a multivariable prediction model allows researchers to investigate the test's/model's performance in multiple settings and populations. Recently, meta-analytic techniques have been proposed to summarize discrimination and calibration across study populations. Here, we rather consider performance in terms of net benefit, which is a measure of clinical utility that weighs the benefits of true positive classifications against the harms of false positives. We posit that it is important to examine clinical utility across multiple settings of interest. This requires a suitable meta-analysis method, and we propose a Bayesian trivariate random-effects meta-analysis of sensitivity, specificity, and prevalence. Across a range of chosen harm-to-benefit ratios, this provides a summary measure of net benefit, a prediction interval, and an estimate of the probability that the test/model is clinically useful in a new setting. In addition, the prediction interval and probability of usefulness can be calculated conditional on the known prevalence in a new setting. The proposed methods are illustrated by 2 case studies: one on the meta-analysis of published studies on ear thermometry to diagnose fever in children and one on the validation of a multivariable clinical risk prediction model for the diagnosis of ovarian cancer in a multicenter dataset. Crucially, in both case studies the clinical utility of the test/model was heterogeneous across settings, limiting its usefulness in practice. This emphasizes that heterogeneity in clinical utility should be assessed before a test/model is routinely implemented.

Does ignoring clustering in multicenter data influence the performance of prediction models? A simulation study.

Clinical risk prediction models are increasingly being developed and validated on multicenter datasets. In this article, we present a comprehensive framework for the evaluation of the predictive performance of prediction models at the center level and the population level, considering population-averaged predictions, center-specific predictions, and predictions assuming an average random center effect. We demonstrated in a simulation study that calibration slopes do not only deviate from one because of over- or underfitting of patterns in the development dataset, but also as a result of the choice of the model (standard versus mixed effects logistic regression), the type of predictions (marginal versus conditional versus assuming an average random effect), and the level of model validation (center versus population). In particular, when data is heavily clustered (ICC 20%), center-specific predictions offer the best predictive performance at the population level and the center level. We recommend that models should reflect the data structure, while the level of model validation should reflect the research question.

Ultrasound characteristics of endometrial cancer as defined by International Endometrial Tumor Analysis (IETA) consensus nomenclature: prospective multicenter study.

OBJECTIVE: To describe the sonographic features of endometrial cancer in relation to tumor stage, grade and histological type, using the International Endometrial Tumor Analysis (IETA) terminology. METHODS: This was a prospective multicenter study of 1714 women with biopsy-confirmed endometrial cancer undergoing standardized transvaginal grayscale and Doppler ultrasound examination according to the IETA study protocol, by experienced ultrasound examiners using high-end ultrasound equipment. Clinical and sonographic data were entered into a web-based database. We assessed how strongly sonographic characteristics, according to IETA, were associated with outcome at hysterectomy, i.e. tumor stage, grade and histological type, using univariable logistic regression and the c-statistic. RESULTS: In total, 1538 women were included in the final analysis. Median age was 65 (range, 27-98) years, median body mass index was 28.4 (range 16-67) kg/m2 , 1377 (89.5%) women were postmenopausal and 1296 (84.3%) reported abnormal vaginal bleeding. Grayscale and color Doppler features varied according to grade and stage of tumor. High-risk tumors, compared with low-risk tumors, were less likely to have regular endometrial-myometrial junction (difference of -23%; 95% CI, -27 to -18%), were larger (mean endometrial thickness; difference of +9%; 95% CI, +8 to +11%), and were more likely to have non-uniform echogenicity (difference of +7%; 95% CI, +1 to +13%), a multiple, multifocal vessel pattern (difference of +21%; 95% CI, +16 to +26%) and a moderate or high color score (difference of +22%; 95% CI, +18 to +27%). CONCLUSION: Grayscale and color Doppler sonographic features are associated with grade and stage of tumor, and differ between high- and low-risk endometrial cancer. Copyright © 2017 ISUOG. Published by John Wiley & Sons Ltd.

International Endometrial Tumor Analysis (IETA) terminology in women with postmenopausal bleeding and sonographic endometrial thickness ≥ 4.5 mm: agreement and reliability study.

OBJECTIVE: To estimate intra- and interrater agreement and reliability with regard to describing ultrasound images of the endometrium using the International Endometrial Tumor Analysis (IETA) terminology. METHODS: Four expert and four non-expert raters assessed videoclips of transvaginal ultrasound examinations of the endometrium obtained from 99 women with postmenopausal bleeding and sonographic endometrial thickness ≥ 4.5 mm but without fluid in the uterine cavity. The following features were rated: endometrial echogenicity, endometrial midline, bright edge, endometrial-myometrial junction, color score, vascular pattern, irregularly branching vessels and color splashes. The color content of the endometrial scan was estimated using a visual analog scale graded from 0 to 100. To estimate intrarater agreement and reliability, the same videoclips were assessed twice with a minimum of 2 months' interval. The raters were blinded to their own results and to those of the other raters. RESULTS: Interrater differences in the described prevalence of most IETA variables were substantial, and some variable categories were observed rarely. Specific agreement was poor for variables with many categories. For binary variables, specific agreement was better for absence than for presence of a category. For variables with more than two outcome categories, specific agreement for expert and non-expert raters was best for not-defined endometrial midline (93% and 96%), regular endometrial-myometrial junction (72% and 70%) and three-layer endometrial pattern (67% and 56%). The grayscale ultrasound variable with the best reliability was uniform vs non-uniform echogenicity (multirater kappa (κ), 0.55 for expert and 0.52 for non-expert raters), and the variables with the lowest reliability were appearance of the endometrial-myometrial junction (κ, 0.25 and 0.16) and the nine-category endometrial echogenicity variable (κ, 0.29 and 0.28). The most reliable color Doppler variable was color score (mean weighted κ, 0.77 and 0.69). Intra- and interrater agreement and reliability were similar for experts and non-experts. CONCLUSIONS: Inter- and intrarater agreement and reliability when using IETA terminology were limited. This may have implications when assessing the association between a particular ultrasound feature and a specific histological diagnosis, because lack of reproducibility reduces the reliability of the association between a feature and the outcome. Future studies should investigate whether using fewer categories of variable or offering practical training could improve agreement and reliability. Copyright © 2017 ISUOG. Published by John Wiley & Sons Ltd.

Key steps and common pitfalls in developing and validating risk models.

Models for estimating an individual's risk of having or developing a disease are abundant in the medical literature, yet many do not meet the methodological standards that have been set to maximise generalisability and utility. This paper presents an overview of ten steps from the conception of the study to the implementation of the risk model and discusses common pitfalls. We discuss crucial aspects of study design, data collection, model development and performance evaluation, and discuss how to bring the model to clinical practice. TWEETABLE ABSTRACT: We present an overview of ten key steps for the development of risk models and discuss common pitfalls.