Risk-prediction models in postmenopausal patients with symptoms of suspected ovarian cancer in the UK (ROCkeTS): a multicentre, prospective diagnostic accuracy study.

BACKGROUND: Multiple risk-prediction models are used in clinical practice to triage patients as being at low risk or high risk of ovarian cancer. In the ROCkeTS study, we aimed to identify the best diagnostic test for ovarian cancer in symptomatic patients, through head-to-head comparisons of risk-prediction models, in a real-world setting. Here, we report the results for the postmenopausal cohort. METHODS: In this multicentre, prospective diagnostic accuracy study, we recruited newly presenting female patients aged 16-90 years with non-specific symptoms and raised CA125 or abnormal ultrasound results (or both) who had been referred via rapid access, elective clinics, or emergency presentations from 23 hospitals in the UK. Patients with normal CA125 and simple ovarian cysts of smaller than 5 cm in diameter, active non-ovarian malignancy, or previous ovarian malignancy, or those who were pregnant or declined a transvaginal scan, were ineligible. In this analysis, only postmenopausal participants were included. Participants completed a symptom questionnaire, gave a blood sample, and had transabdominal and transvaginal ultrasounds performed by International Ovarian Tumour Analysis consortium (IOTA)-certified sonographers. Index tests were Risk of Malignancy 1 (RMI1) at a threshold of 200, Risk of Malignancy Algorithm (ROMA) at multiple thresholds, IOTA Assessment of Different Neoplasias in the Adnexa (ADNEX) at thresholds of 3% and 10%, IOTA SRRisk model at thresholds of 3% and 10%, IOTA Simple Rules (malignant vs benign, or inconclusive), and CA125 at 35 IU/mL. In a post-hoc analysis, the Ovarian Adnexal and Reporting Data System (ORADS) at 10% was derived from IOTA ultrasound variables using established methods since ORADS was described after completion of recruitment. Index tests were conducted by study staff masked to the results of the reference standard. The comparator was RMI1 at the 250 threshold (the current UK National Health Service standard of care). The reference standard was surgical or biopsy tissue histology or cytology within 3 months, or a self-reported diagnosis of ovarian cancer at 12 month follow-up. The primary outcome was diagnostic accuracy at predicting primary invasive ovarian cancer versus benign or normal histology, assessed by analysing the sensitivity, specificity, C-index, area under receiver operating characteristic curve, positive and negative predictive values, and calibration plots in participants with conclusive reference standard results and available index test data. This study is registered with the International Standard Randomised Controlled Trial Number registry (ISRCTN17160843). FINDINGS: Between July 13, 2015, and Nov 30, 2018, 1242 postmenopausal patients were recruited, of whom 215 (17%) had primary ovarian cancer. 166 participants had missing, inconclusive, or other reference standard results; therefore, data from a maximum of 1076 participants were used to assess the index tests for the primary outcome. Compared with RMI1 at 250 (sensitivity 82·9% [95% CI 76·7 to 88·0], specificity 87·4% [84·9 to 89·6]), IOTA ADNEX at 10% was more sensitive (difference of -13·9% [-20·2 to -7·6], p<0·0001) but less specific (difference of 28·5% [24·7 to 32·3], p<0·0001). ROMA at 29·9 had similar sensitivity (difference of -3·6% [-9·1 to 1·9], p=0·24) but lower specificity (difference of 5·2% [2·5 to 8·0], p=0·0001). RMI1 at 200 had similar sensitivity (difference of -2·1% [-4·7 to 0·5], p=0·13) but lower specificity (difference of 3·0% [1·7 to 4·3], p<0·0001). IOTA SRRisk model at 10% had similar sensitivity (difference of -4·3% [-11·0 to -2·3], p=0·23) but lower specificity (difference of 16·2% [12·6 to 19·8], p<0·0001). IOTA Simple Rules had similar sensitivity (difference of -1·6% [-9·3 to 6·2], p=0·82) and specificity (difference of -2·2% [-5·1 to 0·6], p=0·14). CA125 at 35 IU/mL had similar sensitivity (difference of -2·1% [-6·6 to 2·3], p=0·42) but higher specificity (difference of 6·7% [4·3 to 9·1], p<0·0001). In a post-hoc analysis, when compared with RMI1 at 250, ORADS achieved similar sensitivity (difference of -2·1%, 95% CI -8·6 to 4·3, p=0·60) and lower specificity (difference of 10·2%, 95% CI 6·8 to 13·6, p<0·0001). INTERPRETATION: In view of its higher sensitivity than RMI1 at 250, despite some loss in specificity, we recommend that IOTA ADNEX at 10% should be considered as the new standard-of-care diagnostic in ovarian cancer for postmenopausal patients. FUNDING: UK National Institute of Heath Research.

Imaging fetal anatomy.

Due to advancements in ultrasound techniques, the focus of antenatal ultrasound screening is moving towards the first trimester of pregnancy. The early first trimester however remains in part, a 'black box', due to the size of the developing embryo and the limitations of contemporary scanning techniques. Therefore there is a need for images of early anatomical developmental to improve our understanding of this area. By using new imaging techniques, we can not only obtain better images to further our knowledge of early embryonic development, but clear images of embryonic and fetal development can also be used in training for e.g. sonographers and fetal surgeons, or to educate parents expecting a child with a fetal anomaly. The aim of this review is to provide an overview of the past, present and future techniques used to capture images of the developing human embryo and fetus and provide the reader newest insights in upcoming and promising imaging techniques. The reader is taken from the earliest drawings of da Vinci, along the advancements in the fields of in utero ultrasound and MR imaging techniques towards high-resolution ex utero imaging using Micro-CT and ultra-high field MRI. Finally, a future perspective is given about the use of artificial intelligence in ultrasound and new potential imaging techniques such as synchrotron radiation-based CT to increase our knowledge regarding human development.

Comparison of the ADNEX and ROMA risk prediction models for the diagnosis of ovarian cancer: a multicentre external validation in patients who underwent surgery.

BACKGROUND: Several diagnostic prediction models to help clinicians discriminate between benign and malignant adnexal masses are available. This study is a head-to-head comparison of the performance of the Assessment of Different NEoplasias in the adneXa (ADNEX) model with that of the Risk of Ovarian Malignancy Algorithm (ROMA). METHODS: This is a retrospective study based on prospectively included consecutive women with an adnexal tumour scheduled for surgery at five oncology centres and one non-oncology centre in four countries between 2015 and 2019. The reference standard was histology. Model performance for ADNEX and ROMA was evaluated regarding discrimination, calibration, and clinical utility. RESULTS: The primary analysis included 894 patients, of whom 434 (49%) had a malignant tumour. The area under the receiver operating characteristic curve (AUC) was 0.92 (95% CI 0.88-0.95) for ADNEX with CA125, 0.90 (0.84-0.94) for ADNEX without CA125, and 0.85 (0.80-0.89) for ROMA. ROMA, and to a lesser extent ADNEX, underestimated the risk of malignancy. Clinical utility was highest for ADNEX. ROMA had no clinical utility at decision thresholds <27%. CONCLUSIONS: ADNEX had better ability to discriminate between benign and malignant adnexal tumours and higher clinical utility than ROMA. CLINICAL TRIAL REGISTRATION: clinicaltrials.gov NCT01698632 and NCT02847832.

Beta-human chorionic gonadotrophin point of care testing for the management of pregnancy of unknown location.

RESEARCH QUESTION: Does a commercially available quantitative beta-human chorionic gonadotrophin (BHCG) point of care testing (POCT) device improve workflow management in early pregnancy by performing comparably to gold standard laboratory methods, and is the performance of a validated pregnancy of unknown location (PUL) triage strategy maintained using POCT BHCG results? DESIGN: Women classified with a PUL between 2018 and 2021 at three early pregnancy units were included. The linear relationship of untreated whole-blood POCT and serum laboratory BHCG values was defined using coefficients and regression. Paired serial BHCG values were then incorporated into the validated M6 multinomial logistic regression model to stratify the PUL as at high risk or at low risk of clinical complications. The sensitivity and negative predictive value were assessed. The timings required for equivocal POCT and laboratory care pathways were compared. RESULTS: A total of 462 PUL were included. The discrepancy between 571 laboratory and POCT BHCG values was -5.2% (-6.2 IU/l), with a correlation coefficient of 0.96. The 133 PUL with paired 0 and 48 h BHCG values were compared using the M6 model. The sensitivity for high-risk outcomes (96.2%) and negative predictive values (98.5%) was excellent for both. Sample receipt and laboratory processing took 135 min (421 timings), compared with 12 min (91 timings) when using POCT (P < 0.0001). CONCLUSIONS: POCT BHCG values correlated well with laboratory testing measurements. The M6 model retained its performance when using POCT BHCG values. Using the model with POCT may improve workflow and patient care without compromising on effective PUL triage.

Investigating harms of testing for ovarian cancer - psychological outcomes and cancer conversion rates in women with symptoms of ovarian cancer: A cohort study embedded in the multicentre ROCkeTS prospective diagnostic study.

OBJECTIVE: To investigate psychological correlates in women referred with suspected ovarian cancer via the fast-track pathway, explore how anxiety and distress levels change at 12 months post-testing, and report cancer conversion rates by age and referral pathway. DESIGN: Single-arm prospective cohort study. SETTING: Multicentre. Secondary care including outpatient clinics and emergency admissions. POPULATION: A cohort of 2596 newly presenting symptomatic women with a raised CA125 level, abnormal imaging or both. METHODS: Women completed anxiety and distress questionnaires at recruitment and at 12 months for those who had not undergone surgery or a biopsy within 3 months of recruitment. MAIN OUTCOME MEASURES: Anxiety and distress levels measured using a six-item short form of the State-Trait Anxiety Inventory (STAI-6) and the Impact of Event Scale - Revised (IES-r) questionnaire. Ovarian cancer (OC) conversion rates by age, menopausal status and referral pathway. RESULTS: Overall, 1355/2596 (52.1%) and 1781/2596 (68.6%) experienced moderate-to-severe distress and anxiety, respectively, at recruitment. Younger age and emergency presentations had higher distress levels. The clinical category for anxiety and distress remained unchanged/worsened in 76% of respondents at 12 months, despite a non-cancer diagnosis. The OC rates by age were 1.6% (95% CI 0.5%-5.9%) for age <40 years and 10.9% (95% CI 8.7%-13.6%) for age ≥40 years. In women referred through fast-track pathways, 3.3% (95% CI 1.9%-5.7%) of pre- and 18.5% (95% CI 16.1%-21.0%) of postmenopausal women were diagnosed with OC. CONCLUSIONS: Women undergoing diagnostic testing display severe anxiety and distress. Younger women are especially vulnerable and should be targeted for support. Women under the age of 40 years have low conversion rates and we advocate reducing testing in this group to reduce the harms of testing.

Ambulatory human chorionic gonadotrophin (hCG) testing: a verification of two hCG point of care devices.

OBJECTIVES: Quantitative human chorionic gonadotropin (hCG) measurements are used to manage women classified with a pregnancy of unknown location (PUL). Two point of care testing (POCT) devices that quantify hCG are commercially available. We verified the i-STAT 1 (Abbott) and the AQT 90 FLEX (Radiometer) prior to use in PUL triage. METHODS: Tests for precision, external quality assurance (EQA), correlation, hook effect and recovery were undertaken alongside a POCT usability assessment during this prospective multi-center verification. RESULTS: Coefficients of variation ranged between 4.0 and 5.1 % for the three i-STAT 1 internal quality control (IQC) solutions and between 6.8 and 7.3 % for the two AQT IQC solutions. Symmetric differences in POCT EQA results when compared with laboratory and EQA stock values ranged between 3.2 and 24.5 % for the i-STAT 1 and between 3.3 and 36.9 % for the AQT. Correlation coefficients (i-STAT 1: 0.96, AQT: 0.99) and goodness of fit curves (i-STAT 1: 0.92, AQT: 0.99) were excellent when using suitable whole blood samples. An hCG hook effect was noted with the i-STAT 1 between 572,194 and 799,089 IU/L, lower than the hook effect noted with the AQT, which was between 799,089 and 1,619,309 IU/L. When hematocrit concentration was considered in sample types validated for use with each device, hCG recovery was 108 % with the i-STAT 1 and 98 % with the AQT. The i-STAT 1 scored lower on usability overall (90/130) than the AQT (121/130, p<0.001, Mann-Whitney). CONCLUSIONS: Both hCG POCT devices were verified for use in clinical practice. Practical factors must also be considered when choosing which device to use in each unit.

Symptom-triggered testing detects early stage and low volume resectable advanced stage ovarian cancer.

OBJECTIVE: Symptom-triggered testing for ovarian cancer was introduced to the UK whereby symptomatic women undergo an ultrasound scan and serum CA125, and are referred to hospital within 2 weeks if these are abnormal. The potential value of symptom-triggered testing in the detection of early-stage disease or low tumor burden remains unclear in women with high grade serous ovarian cancer. In this descriptive study, we report on the International Federation of Gynecology and Obstetrics (FIGO) stage, disease distribution, and complete cytoreduction rates in women presenting via the fast-track pathway and who were diagnosed with high grade serous ovarian cancer. METHODS: We analyzed the dataset from Refining Ovarian Cancer Test accuracy Scores (ROCkeTS), a single-arm prospective diagnostic test accuracy study recruiting from 24 hospitals in the UK. The aim of ROCkeTS is to validate risk prediction models in symptomatic women. We undertook an opportunistic analysis for women recruited between June 2015 to July 2022 and who were diagnosed with high grade serous ovarian cancer via the fast-track pathway. Women presenting with symptoms suspicious for ovarian cancer receive a CA125 blood test and an ultrasound scan if the CA125 level is abnormal. If either of these is abnormal, women are referred to secondary care within 2 weeks. Histology details were available on all women who underwent surgery or biopsy within 3 months of recruitment. Women who did not undergo surgery or biopsy at 3 months were followed up for 12 months as per the national guidelines in the UK. In this descriptive study, we report on patient demographics (age and menopausal status), WHO performance status, FIGO stage at diagnosis, disease distribution (low/pelvic confined, moderate/extending to mid-abdomen, high/extending to upper abdomen) and complete cytoreduction rates in women who underwent surgery. RESULTS: Of 1741 participants recruited via the fast-track pathway, 119 (6.8%) were diagnosed with high grade serous ovarian cancer. The median age was 63 years (range 32-89). Of these, 112 (94.1%) patients had a performance status of 0 and 1, 30 (25.2%) were diagnosed with stages I/II, and the disease distribution was low-to-moderate in 77 (64.7%). Complete and optimal cytoreduction were achieved in 73 (61.3%) and 18 (15.1%). The extent of disease was low in 43 of 119 (36.1%), moderate in 34 of 119 (28.6%), high in 32 of 119 (26.9%), and not available in 10 of 119 (8.4%). Nearly two thirds, that is 78 of 119 (65.5%) women with high grade serous ovarian cancer, underwent primary debulking surgery, 36 of 119 (30.3%) received neoadjuvant chemotherapy followed by interval debulking surgery, and 5 of 119 (4.2%) women did not undergo surgery. CONCLUSION: Our results demonstrate that one in four women identified with high grade serous ovarian cancer through the fast-track pathway following symptom-triggered testing was diagnosed with early-stage disease. Symptom-triggered testing may help identify women with a low disease burden, potentially contributing to high complete cytoreduction rates.

Predictors of successful expectant and medical management of miscarriage: A systematic review.

INTRODUCTION: 15.3% of pregnancies result in miscarriage, management options include expectant, medical, or surgical. However, each patient has a range of variables, which makes navigating the available literature challenging when supporting individual patient decision-making. This systematic review aims to investigate whether there are any specific predictors for miscarriage management outcome. MATERIAL AND METHODS: The following databases were searched, from the start of each database up to April 2023: PubMed, Medline, and Google Scholar. Inclusion criteria were studies interrogating defined predictors for expectant or medical management of miscarriage success. Exclusion criteria were poor quality, review articles, trial protocols, and congress abstracts. Data collection was carried as per PRISMA guidelines. Quality assessment for each study was assessed using the QUIPS proforma. RESULTS: Relevant predictors include demographics, ultrasound features, presenting symptoms, and biochemical markers. Across the 24 studies there is heterogeneity in miscarriage definition, predictors reported, and management outcomes used. Associations with certain variables and miscarriage management outcomes are described. Ten studies assessed the impact of miscarriage type on expectant and/or medical management. The majority found that a diagnosis of incomplete miscarriage had a higher success rate following expectant or medical management compared to missed miscarriage or anembryonic pregnancy. CONCLUSIONS: We conclude that there is evidence supporting the possibility to offer personalized miscarriage management advice with case specific predictors. Further larger studies with consistent definitions of predictors, management, and outcomes are needed in order to better support women through the decision-making of miscarriage management.

Using online search activity for earlier detection of gynaecological malignancy.

BACKGROUND: Ovarian cancer is the most lethal and endometrial cancer the most common gynaecological cancer in the UK, yet neither have a screening program in place to facilitate early disease detection. The aim is to evaluate whether online search data can be used to differentiate between individuals with malignant and benign gynaecological diagnoses. METHODS: This is a prospective cohort study evaluating online search data in symptomatic individuals (Google user) referred from primary care (GP) with a suspected cancer to a London Hospital (UK) between December 2020 and June 2022. Informed written consent was obtained and online search data was extracted via Google takeout and anonymised. A health filter was applied to extract health-related terms for 24 months prior to GP referral. A predictive model (outcome: malignancy) was developed using (1) search queries (terms model) and (2) categorised search queries (categories model). Area under the ROC curve (AUC) was used to evaluate model performance. 844 women were approached, 652 were eligible to participate and 392 were recruited. Of those recruited, 108 did not complete enrollment, 12 withdrew and 37 were excluded as they did not track Google searches or had an empty search history, leaving a cohort of 235. RESULTS: The cohort had a median age of 53 years old (range 20-81) and a malignancy rate of 26.0%. There was a difference in online search data between those with a benign and malignant diagnosis, noted as early as 360 days in advance of GP referral, when search queries were used directly, but only 60 days in advance, when queries were divided into health categories. A model using online search data from patients (n = 153) who performed health-related search and corrected for sample size, achieved its highest sample-corrected AUC of 0.82, 60 days prior to GP referral. CONCLUSIONS: Online search data appears to be different between individuals with malignant and benign gynaecological conditions, with a signal observed in advance of GP referral date. Online search data needs to be evaluated in a larger dataset to determine its value as an early disease detection tool and whether its use leads to improved clinical outcomes.

Multiclass risk models for ovarian malignancy: an illustration of prediction uncertainty due to the choice of algorithm.

BACKGROUND: Assessing malignancy risk is important to choose appropriate management of ovarian tumors. We compared six algorithms to estimate the probabilities that an ovarian tumor is benign, borderline malignant, stage I primary invasive, stage II-IV primary invasive, or secondary metastatic. METHODS: This retrospective cohort study used 5909 patients recruited from 1999 to 2012 for model development, and 3199 patients recruited from 2012 to 2015 for model validation. Patients were recruited at oncology referral or general centers and underwent an ultrasound examination and surgery ≤ 120 days later. We developed models using standard multinomial logistic regression (MLR), Ridge MLR, random forest (RF), XGBoost, neural networks (NN), and support vector machines (SVM). We used nine clinical and ultrasound predictors but developed models with or without CA125. RESULTS: Most tumors were benign (3980 in development and 1688 in validation data), secondary metastatic tumors were least common (246 and 172). The c-statistic (AUROC) to discriminate benign from any type of malignant tumor ranged from 0.89 to 0.92 for models with CA125, from 0.89 to 0.91 for models without. The multiclass c-statistic ranged from 0.41 (SVM) to 0.55 (XGBoost) for models with CA125, and from 0.42 (SVM) to 0.51 (standard MLR) for models without. Multiclass calibration was best for RF and XGBoost. Estimated probabilities for a benign tumor in the same patient often differed by more than 0.2 (20% points) depending on the model. Net Benefit for diagnosing malignancy was similar for algorithms at the commonly used 10% risk threshold, but was slightly higher for RF at higher thresholds. Comparing models, between 3% (XGBoost vs. NN, with CA125) and 30% (NN vs. SVM, without CA125) of patients fell on opposite sides of the 10% threshold. CONCLUSION: Although several models had similarly good performance, individual probability estimates varied substantially.

A core outcome set for trials in miscarriage management and prevention: An international consensus development study.

OBJECTIVE: To develop core outcome sets (COS) for miscarriage management and prevention. DESIGN: Modified Delphi survey combined with a consensus development meeting. SETTING: International. POPULATION: Stakeholder groups included healthcare providers, international experts, researchers, charities and couples with lived experience of miscarriage from 15 countries: 129 stakeholders for miscarriage management and 437 for miscarriage prevention. METHODS: Modified Delphi method and modified nominal group technique. RESULTS: The final COS for miscarriage management comprises six outcomes: efficacy of treatment, heavy vaginal bleeding, pelvic infection, maternal death, treatment or procedure-related complications, and patient satisfaction. The final COS for miscarriage prevention comprises 12 outcomes: pregnancy loss <24 weeks' gestation, live birth, gestation at birth, pre-term birth, congenital abnormalities, fetal growth restriction, maternal (antenatal) complications, compliance with intervention, patient satisfaction, maternal hospitalisation, neonatal or infant hospitalisation, and neonatal or infant death. Other outcomes identified as important were mental health-related outcomes, future fertility and health economic outcomes. CONCLUSIONS: This study has developed two core outcome sets, through robust methodology, that should be implemented across future randomised trials and systematic reviews in miscarriage management and prevention. This work will help to standardise outcome selection, collection and reporting, and improve the quality and safety of future studies in miscarriage.

Sporadic miscarriage: evidence to provide effective care.

The physical and psychological effect of miscarriage is commonly underappreciated. The journey from diagnosis of miscarriage, through clinical management, to supportive aftercare can be challenging for women, their partners, and caregivers. Diagnostic challenges can lead to delayed or ineffective care and increased anxiety. Inaccurate diagnosis of a miscarriage can result in the unintended termination of a wanted pregnancy. Uncertainty about the therapeutic effects of interventions can lead to suboptimal care, with variations across facilities and countries. For this Series paper, we have developed recommendations for practice from a literature review, appraisal of guidelines, and expert group discussions. The recommendations are grouped into three categories: (1) diagnosis of miscarriage, (2) prevention of miscarriage in women with early pregnancy bleeding, and (3) management of miscarriage. We recommend that every country reports annual aggregate miscarriage data, similarly to the reporting of stillbirth. Early pregnancy services need to focus on providing an effective ultrasound service, as it is central to the diagnosis of miscarriage, and be able to provide expectant management of miscarriage, medical management with mifepristone and misoprostol, and surgical management with manual vacuum aspiration. Women with the dual risk factors of early pregnancy bleeding and a history of previous miscarriage can be recommended vaginal micronised progesterone to improve the prospects of livebirth. We urge health-care funders and providers to invest in early pregnancy care, with specific focus on training for clinical nurse specialists and doctors to provide comprehensive miscarriage care within the setting of dedicated early pregnancy units.

Miscarriage matters: the epidemiological, physical, psychological, and economic costs of early pregnancy loss.

Miscarriage is generally defined as the loss of a pregnancy before viability. An estimated 23 million miscarriages occur every year worldwide, translating to 44 pregnancy losses each minute. The pooled risk of miscarriage is 15·3% (95% CI 12·5-18·7%) of all recognised pregnancies. The population prevalence of women who have had one miscarriage is 10·8% (10·3-11·4%), two miscarriages is 1·9% (1·8-2·1%), and three or more miscarriages is 0·7% (0·5-0·8%). Risk factors for miscarriage include very young or older female age (younger than 20 years and older than 35 years), older male age (older than 40 years), very low or very high body-mass index, Black ethnicity, previous miscarriages, smoking, alcohol, stress, working night shifts, air pollution, and exposure to pesticides. The consequences of miscarriage are both physical, such as bleeding or infection, and psychological. Psychological consequences include increases in the risk of anxiety, depression, post-traumatic stress disorder, and suicide. Miscarriage, and especially recurrent miscarriage, is also a sentinel risk marker for obstetric complications, including preterm birth, fetal growth restriction, placental abruption, and stillbirth in future pregnancies, and a predictor of longer-term health problems, such as cardiovascular disease and venous thromboembolism. The costs of miscarriage affect individuals, health-care systems, and society. The short-term national economic cost of miscarriage is estimated to be £471 million per year in the UK. As recurrent miscarriage is a sentinel marker for various obstetric risks in future pregnancies, women should receive care in preconception and obstetric clinics specialising in patients at high risk. As psychological morbidity is common after pregnancy loss, effective screening instruments and treatment options for mental health consequences of miscarriage need to be available. We recommend that miscarriage data are gathered and reported to facilitate comparison of rates among countries, to accelerate research, and to improve patient care and policy development.

Recurrent miscarriage: evidence to accelerate action.

Women who have had repeated miscarriages often have uncertainties about the cause, the likelihood of recurrence, the investigations they need, and the treatments that might help. Health-care policy makers and providers have uncertainties about the optimal ways to organise and provide care. For this Series paper, we have developed recommendations for practice from literature reviews, appraisal of guidelines, and a UK-wide consensus conference that was held in December, 2019. Caregivers should individualise care according to the clinical needs and preferences of women and their partners. We define a minimum set of investigations and treatments to be offered to couples who have had recurrent miscarriages, and urge health-care policy makers and providers to make them universally available. The essential investigations include measurements of lupus anticoagulant, anticardiolipin antibodies, thyroid function, and a transvaginal pelvic ultrasound scan. The key treatments to consider are first trimester progesterone administration, levothyroxine in women with subclinical hypothyroidism, and the combination of aspirin and heparin in women with antiphospholipid antibodies. Appropriate screening and care for mental health issues and future obstetric risks, particularly preterm birth, fetal growth restriction, and stillbirth, will need to be incorporated into the care pathway for couples with a history of recurrent miscarriage. We suggest health-care services structure care using a graded model in which women are offered online health-care advice and support, care in a nurse or midwifery-led clinic, and care in a medical consultant-led clinic, according to clinical needs.

Chromosomally normal miscarriage is associated with vaginal dysbiosis and local inflammation.

BACKGROUND: Emerging evidence supports an association between vaginal microbiota composition and risk of miscarriage; however, the underlying mechanisms are poorly understood. We aim to investigate the vaginal microbial composition and the local immune response in chromosomally normal and abnormal miscarriages and compare this to uncomplicated pregnancies delivering at term. METHODS: We used 16S rRNA gene based metataxonomics to interrogate the vaginal microbiota in a cohort of 167 women, 93 miscarriages (54 euploid and 39 aneuploid using molecular cytogenetics) and 74 women who delivered at term and correlate this with the aneuploidy status of the miscarriages. We also measured the concentrations of IL-2, IL-4, IL-6, IL-8, TNF-α, IFN-γ, IL-1ß, IL-18 and IL-10 in cervical vaginal fluid. RESULTS: We show that euploid miscarriage is associated with a significantly higher prevalence of Lactobacillus spp. deplete vaginal microbial communities compared to aneuploid miscarriage (P = 0.01). Integration of matched cervicovaginal fluid immune-profiles showed that Lactobacillus spp. depleted vaginal microbiota associated with pro-inflammatory cytokine levels most strongly in euploid miscarriage compared to viable term pregnancy (IL-1ß; P < 0.001, IL-8; P = 0.01, IL-6; P < 0.001). CONCLUSIONS: Our data suggest the vaginal microbiota plays an important aetiological role in euploid miscarriage and may represent a target to modify risk of pregnancy loss.

Evaluating cut-off levels for progesterone, ß human chorionic gonadotropin and ß human chorionic gonadotropin ratio to exclude pregnancy viability in women with a pregnancy of unknown location: A prospective multicenter cohort study.

INTRODUCTION: There is no global agreement on how to best determine pregnancy of unknown location viability and location using biomarkers. Measurements of progesterone and ß human chorionic gonadotropin (ßhCG) are still used in clinical practice to exclude the possibility of a viable intrauterine pregnancy (VIUP). We evaluate the predictive value of progesterone, ßhCG, and ßhCG ratio cut-off levels to exclude a VIUP in women with a pregnancy of unknown location. MATERIAL AND METHODS: This was a secondary analysis of prospective multicenter study data of consecutive women with a pregnancy of unknown location between January 2015 and 2017 collected from dedicated early pregnancy assessment units of eight hospitals. Single progesterone and serial ßhCG measurements were taken. Women were followed up until final pregnancy outcome between 11 and 14 weeks of gestation was confirmed using transvaginal ultrasonography: (1) VIUP, (2) non-viable intrauterine pregnancy or failed pregnancy of unknown location, and (3) ectopic pregnancy or persisting pregnancy of unknown location. The predictive value of cut-off levels for ruling out VIUP were evaluated across a range of values likely to be encountered clinically for progesterone, ßhCG, and ßhCG ratio. RESULTS: Data from 2507 of 3272 (76.6%) women were suitable for analysis. All had data for ßhCG levels, 2248 (89.7%) had progesterone levels, and 1809 (72.2%) had ßhCG ratio. The likelihood of viability falls with the progesterone level. Although the median progesterone level associated with viability was 59 nmol/L, VIUP were identified with levels as low as 5 nmol/L. No single ßhCG cut-off reliably ruled out the presence of viability with certainty, even when the level was more than 3000 IU/L, there were 39/358 (11%) women who had a VIUP. The probability of viability decreases with the ßhCG ratio. Although the median ßhCG ratio associated with viability was 2.26, VIUP were identified with ratios as low as 1.02. A progesterone level below 2 nmol/L and ßhCG ratio below 0.87 were unlikely to be associated with viability but were not definitive when considering multiple imputation. CONCLUSIONS: Cut-off levels for ßhCG, ßhCG ratio, and progesterone are not safe to be used clinically to exclude viability in early pregnancy. Although ßhCG ratio and progesterone have slightly better performance in comparison, single ßhCG used in this manner is highly unreliable.

The Risk of Endometrial Malignancy and Other Endometrial Pathology in Women with Abnormal Uterine Bleeding: An Ultrasound-Based Model Development Study by the IETA Group.

OBJECTIVES: The aim of this study was to develop a model that can discriminate between different etiologies of abnormal uterine bleeding. DESIGN: The International Endometrial Tumor Analysis 1 study is a multicenter observational diagnostic study in 18 bleeding clinics in 9 countries. Consecutive women with abnormal vaginal bleeding presenting for ultrasound examination (n = 2,417) were recruited. The histology was obtained from endometrial sampling, D&C, hysteroscopic resection, hysterectomy, or ultrasound follow-up for >1 year. METHODS: A model was developed using multinomial regression based on age, body mass index, and ultrasound predictors to distinguish between: (1) endometrial atrophy, (2) endometrial polyp or intracavitary myoma, (3) endometrial malignancy or atypical hyperplasia, (4) proliferative/secretory changes, endometritis, or hyperplasia without atypia and validated using leave-center-out cross-validation and bootstrapping. The main outcomes are the model's ability to discriminate between the four outcomes and the calibration of risk estimates. RESULTS: The median age in 2,417 women was 50 (interquartile range 43-57). 414 (17%) women had endometrial atrophy; 996 (41%) had a polyp or myoma; 155 (6%) had an endometrial malignancy or atypical hyperplasia; and 852 (35%) had proliferative/secretory changes, endometritis, or hyperplasia without atypia. The model distinguished well between malignant and benign histology (c-statistic 0.88 95% CI: 0.85-0.91) and between all benign histologies. The probabilities for each of the four outcomes were over- or underestimated depending on the centers. LIMITATIONS: Not all patients had a diagnosis based on histology. The model over- or underestimated the risk for certain outcomes in some centers, indicating local recalibration is advisable. CONCLUSIONS: The proposed model reliably distinguishes between four histological outcomes. This is the first model to discriminate between several outcomes and is the only model applicable when menopausal status is uncertain. The model could be useful for patient management and counseling, and aid in the interpretation of ultrasound findings. Future research is needed to externally validate and locally recalibrate the model.

Evaluation of the Tramline Sign in the Prediction of Placenta Accreta Spectrum and Perioperative Outcomes in Anterior Placenta Previa.

PURPOSE: To evaluate perioperative outcomes and the prognostic role of the tramline sign in a cohort of women with anterior placenta previa. MATERIALS AND METHODS: Retrospective analysis of 3D ultrasound volumes from women with anterior placenta previa who underwent ultrasound examination beyond 32 weeks. 3D and 3D color volumes were obtained from a sagittal section of the uterus bisecting a partially full bladder and processed using Crystal Vue and Crystal Vue Flow rendering to look for the "tramline sign". "Partial obliteration" was defined as a loss of some or part of the uterine-serosal interface and "full obliteration" as when both interfaces were interrupted. Postnatal ascertainment of placenta accreta spectrum (PAS) was confirmed by findings recorded intraoperatively or on a pathology report. RESULTS: 65 cases were included. The tramline sign was "partially" (17) or "fully" (19) obliterated in 36 cases (55.4 %), and present in 29 (44.6 %). Obliteration was associated with earlier gestational age at delivery (35 + 1 (26 + 3-38 + 3) vs. 36 + 4 (25 + 3-38 + 0) weeks, p = 0.005), greater estimated blood loss (800 (400-11 000) vs. 600 (300-2100) mls, p = 0.003), longer operative time (155 (60-240) vs. 54 (25-80) minutes, p < 0.001), higher rate of hysterectomy (97.2 % vs. 0.0 %, p < 0.001), longer postoperative admission (7 (3-19) vs. 3 (1-5) days, p < 0.001) and a 100 % rate of postnatal diagnosis of PAS. The finding of an "obliterated" tramline sign identified all women that required hysterectomy and all cases of PAS. CONCLUSION: A "partially or fully obliterated" tramline sign is strongly associated with indicators of operative complexity, the postnatal confirmation of PAS, and the need for peripartum hysterectomy.

ESGO/ISUOG/IOTA/ESGE Consensus Statement on pre-operative diagnosis of ovarian tumors.

The European Society of Gynaecological Oncology (ESGO), the International Society of Ultrasound in Obstetrics and Gynecology (ISUOG), the International Ovarian Tumour Analysis (IOTA) group, and the European Society for Gynaecological Endoscopy (ESGE) jointly developed clinically relevant and evidence-based statements on the pre-operative diagnosis of ovarian tumors, including imaging techniques, biomarkers, and prediction models. ESGO/ISUOG/IOTA/ESGE nominated a multidisciplinary international group, including expert practising clinicians and researchers who have demonstrated leadership and expertise in the pre-operative diagnosis of ovarian tumors and management of patients with ovarian cancer (19 experts across Europe). A patient representative was also included in the group. To ensure that the statements were evidence-based, the current literature was reviewed and critically appraised. Preliminary statements were drafted based on the review of the relevant literature. During a conference call, the whole group discussed each preliminary statement and a first round of voting was carried out. Statements were removed when a consensus among group members was not obtained. The voters had the opportunity to provide comments/suggestions with their votes. The statements were then revised accordingly. Another round of voting was carried out according to the same rules to allow the whole group to evaluate the revised version of the statements. The group achieved consensus on 18 statements. This Consensus Statement presents these ESGO/ISUOG/IOTA/ESGE statements on the pre-operative diagnosis of ovarian tumors and the assessment of carcinomatosis, together with a summary of the evidence supporting each statement.

An Evaluation of the Effectiveness of Image-based Texture Features Extracted from Static B-mode Ultrasound Images in Distinguishing between Benign and Malignant Ovarian Masses.

Significant successes in machine learning approaches to image analysis for various applications have energized strong interest in automated diagnostic support systems for medical images. The evolving in-depth understanding of the way carcinogenesis changes the texture of cellular networks of a mass/tumor has been informing such diagnostics systems with use of more suitable image texture features and their extraction methods. Several texture features have been recently applied in discriminating malignant and benign ovarian masses by analysing B-mode images from ultrasound scan of the ovary with different levels of performance. However, comparative performance evaluation of these reported features using common sets of clinically approved images is lacking. This paper presents an empirical evaluation of seven commonly used texture features (histograms, moments of histogram, local binary patterns [256-bin and 59-bin], histograms of oriented gradients, fractal dimensions, and Gabor filter), using a collection of 242 ultrasound scan images of ovarian masses of various pathological characteristics. The evaluation examines not only the effectiveness of classification schemes based on the individual texture features but also the effectiveness of various combinations of these schemes using the simple majority-rule decision level fusion. Trained support vector machine classifiers on the individual texture features without any specific pre-processing, achieve levels of accuracy between 75% and 85% where the seven moments and the 256-bin LBP are at the lower end while the Gabor filter is at the upper end. Combining the classification results of the top k (k = 3, 5, 7) best performing features further improve the overall accuracy to a level between 86% and 90%. These evaluation results demonstrate that each of the investigated image-based texture features provides informative support in distinguishing benign or malignant ovarian masses.