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: To determine whether long-term oncological follow-up is required following fertility-sparing surgery (FSS) for mucinous borderline ovarian tumours (MBOTs). : A retrospective cohort study set in the tertiary gynaecology oncology centre at Imperial College Healthcare NHS Trust. Patients included were those under follow-up post-surgery for an MBOT in the ovarian clinic from 2007 to 2025. Rate of recurrence was compared amongst patients who underwent ovarian cystectomy, unilateral salpingo-oophorectomy (USO) or bilateral salpingo-oophorectomy (BSO) +/- hysterectomy. : From 74 patients diagnosed with MBOT, 36.5% (27/74) underwent BSO +/- hysterectomy and 63.5% (47/74) had FSS. Of the patients who underwent FSS, 59.6% (28/47) had an initial USO and 40.4% (19/47) underwent ovarian cystectomy. Subsequently, 63.2% (12/19) of patients who initially had ovarian cystectomy proceeded with completion USO, leading to a total of 40 USOs performed. There were no recurrences following BSO +/- hysterectomy, primary USO or completion USO after a median follow-up of 49.0, 65.5 and 48.0 months, respectively. Of the patients who underwent ovarian cystectomy, 15.8% (3/19) were found to have residual MBOT (n = 1) two months post-cystectomy or MBOT recurrence (n = 2) at 10- and 66-months post-cystectomy, all diagnosed at USO. There is a significant association between ovarian cystectomy and disease recurrence (Fisher's exact test = 0.015). : Patients of reproductive age who undergo USO for a MBOT can be offered a reduced follow-up schedule as the risk of recurrence is very low. In contrast, patients who are managed by ovarian cystectomy have a higher risk of recurrence and require long-term surveillance monitoring.

Fragmentation patterns of plasma cell-free DNA (cfDNA) are known to reflect nucleosome positions of cell types contributing to cfDNA. Based on cfDNA fragmentation patterns, the deviation in nucleosome footprints was quantified between diagnosed ovarian cancer patients and healthy individuals. Multinomial modeling was subsequently applied to capture these deviations in a per sample nucleosome footprint score. Validation was performed in 271 cfDNAs pre-surgically collected from women with an adnexal mass. We confirmed that nucleosome scores were elevated in invasive carcinoma patients, but not in patients with benign or borderline disease. Combining nucleosome scores with chromosomal instability scores assessed in the same cfDNA improved prediction of malignancy. Nucleosome scores were, however, more reliable to predict non-high-grade serous ovarian tumors, which are characterized by low chromosomal instability. These data highlight that compared to chromosomal instability, nucleosome footprinting provides a complementary and more generic read-out for pre-surgical diagnosis of invasive disease in women with adnexal masses.

ObjectiveAssess experience of healthcare professionals (HCPs) working with ultrasound in obstetrics and gynaecology during the evolving SARS-CoV-2 pandemic, given the new and unprecedented challenges involving viral exposure, personal protective equipment (PPE) and well-being.DesignProspective cross-sectional survey study.SettingOnline international survey. Single-best, open box and Hospital Anxiety and Depression Scale (HADS) questions.ParticipantsThe survey was sent to 35 509 HCPs in 124 countries and was open from 7 to 21 May 2020. 2237/3237 (69.1%) HCPs from 115 countries who consented to participate completed the survey. 1058 (47.3%) completed the HADS.Primary outcome measuresOverall prevalence of SARS-CoV-2, depression and anxiety among HCPs in relation to country and PPE availability.AnalysesUnivariate analyses were used to investigate associations without generating erroneous causal conclusions.ResultsConfirmed/suspected SARS-CoV-2 prevalence was 13.0%. PPE provision concerns were raised by 74.1% of participants; highest among trainees/resident physicians (83.9%) and among HCPs in Spain (89.7%). Most participants worked in self-perceived high-risk areas with SARS-CoV-2 (67.5%–87.0%), with proportionately more trainees interacting with suspected/confirmed infected patients (57.1% vs 24.2%–40.6%) and sonographers seeing more patients who did not wear a mask (33.3% vs 13.9%–7.9%). The most frequent PPE combination used was gloves and a surgical mask (22.3%). UK and US respondents reported spending less time self-isolating (8.8 days) and lower satisfaction with their national pandemic response (37.0%–43.0%). 19.8% and 8.8% of respondents met the criteria for moderate to severe anxiety and depression, respectively.ConclusionsReported prevalence of SARS-CoV-2 in HCPs is consistent with literature findings. Most respondents used gloves and a surgical mask, with a greater SARS-CoV-2 prevalence compared with those using ‘full’ PPE. HCPs with the least agency (trainees and sonographers) were not only more likely to see high-risk patients but also less likely to be protected. A fifth of respondents reported moderate to severe anxiety.

BackgroundTumors can influence peripheral immune macroenvironment, thereby creating opportunities for non-invasive serum/plasma immunobiomarkers for immunostratification and immunotherapy designing. However, current approaches for immunobiomarkers’ detection are largely quantitative, which is unreliable for assessing functional peripheral immunodynamics of patients with cancer. Hence, we aimed to design a functional biomarker modality for capturing peripheral immune signaling in patients with cancer for reliable immunostratification.MethodsWe used a data-driven in silico framework, integrating existing tumor/blood bulk-RNAseq or single-cell (sc)RNAseq datasets of patients with cancer, to inform the design of an innovative serum-screening modality, that is, serum-functional immunodynamic status (sFIS) assay. Next, we pursued proof-of-concept analyses via multiparametric serum profiling of patients with ovarian cancer (OV) with sFIS assay combined with Luminex (cytokines/soluble immune checkpoints), CA125-antigen detection, and whole-blood immune cell counts. Here, sFIS assay’s ability to determine survival benefit or malignancy risk was validated in a discovery (n=32) and/or validation (n=699) patient cohorts. Lastly, we used an orthotopic murine metastatic OV model, with anti-OV therapy selection via in silico drug–target screening and murine serum screening via sFIS assay, to assess suitable in vivo immunotherapy options.ResultsIn silico data-driven framework predicted that peripheral immunodynamics of patients with cancer might be best captured via analyzing myeloid nuclear factor kappa-light-chain enhancer of activated B cells (NFκB) signaling and interferon-stimulated genes' (ISG) responses. This helped in conceptualization of an ‘in sitro’ (in vitro+in situ) sFIS assay, where human myeloid cells were exposed to patients’ serum in vitro, to assess serum-induced (si)-NFκB or interferon (IFN)/ISG responses (as active signaling reporter activity) within them, thereby ‘mimicking’ patients’ in situ immunodynamic status. Multiparametric serum profiling of patients with OV established that sFIS assay can: decode peripheral immunology (by indicating higher enrichment of si-NFκB over si-IFN/ISG responses), estimate survival trends (si-NFκB or si-IFN/ISG responses associating with negative or positive prognosis, respectively), and coestimate malignancy risk (relative to benign/borderline ovarian lesions). Biologically, we documented dominance of pro-tumorigenic, myeloid si-NFκB responseHIGHsi-IFN/ISG responseLOW inflammation in periphery of patients with OV. Finally, in an orthotopic murine metastatic OV model, sFIS assay predicted the higher capacity of chemo-immunotherapy (paclitaxel–carboplatin plus anti-TNF antibody combination) in achieving a pro-immunogenic peripheral milieu (si-IFN/ISG responseHIGHsi-NFκB responseLOW), which aligned with high antitumor efficacy.ConclusionsWe established sFIS assay as a novel biomarker resource for serum screening in patients with OV to evaluate peripheral immunodynamics, patient survival trends and malignancy risk, and to design preclinical chemo-immunotherapy strategies.

Endometrial carcinoma is the most frequent cancer of the reproductive female organs. Most endometrial cancers are diagnosed at early stage (75%). Treatment options depend on pathogenetic, histopathologic and clinical characteristic at the diagnosis. To improve patient management in the near future, recent research has focused on new molecular features; evidence has shown that these give a better definition of patient prognosis and can help in tailoring adjuvant treatments by identifying specific subgroups of patients whose tumors may benefit from specific therapeutic approaches. In this review, we will focus on current knowledge of adjuvant treatment of endometrial carcinoma, using a prognostic-risk group stratification based on pathogenetic, clinical and molecular features, and will take a look at the ongoing trials that will further change the therapeutic approach in coming years.

Ultrasound-based models exist to support the classification of adnexal masses but are subjective and rely upon ultrasound expertise. We aimed to develop an end-to-end machine learning (ML) model capable of automating the classification of adnexal masses. In this retrospective study, transvaginal ultrasound scan images with linked diagnoses (ultrasound subjective assessment or histology) were extracted and segmented from Imperial College Healthcare, UK (ICH development dataset; n  = 577 masses; 1444 images) and Morgagni-Pierantoni Hospital, Italy (MPH external dataset; n  = 184 masses; 476 images). A segmentation and classification model was developed using convolutional neural networks and traditional radiomics features. Dice surface coefficient (DICE) was used to measure segmentation performance and area under the ROC curve (AUC), F1-score and recall for classification performance. The ICH and MPH datasets had a median age of 45 (IQR 35–60) and 48 (IQR 38–57) years old and consisted of 23.1% and 31.5% malignant cases, respectively. The best segmentation model achieved a DICE score of 0.85 ± 0.01, 0.88 ± 0.01 and 0.85 ± 0.01 in the ICH training, ICH validation and MPH test sets. The best classification model achieved a recall of 1.00 and F1-score of 0.88 (AUC:0.93), 0.94 (AUC:0.89) and 0.83 (AUC:0.90) in the ICH training, ICH validation and MPH test sets, respectively. We have developed an end-to-end radiomics-based model capable of adnexal mass segmentation and classification, with a comparable predictive performance (AUC 0.90) to the published performance of expert subjective assessment (gold standard), and current risk models. Further prospective evaluation of the classification performance of this ML model against existing methods is required.

Even if the benign nature of a mass is stated with a high level of diagnostic confidence or if several reassuring ultrasound features are present, the risk of malignancy exceeds the 0·3% risk of morcellating an unsuspected uterine sarcoma reported by the FDA. Characteristic present Characteristic absent Postmenopausal 9/123 (7%) 4/58 (7%) Increased CA125 (>=35 U/mL) 5/33 (15%) 4/86 (5%) Largest diameter of lesion (>=55 mm)* 8/92 (9%) 5/89 (6%) Lesion volume (>=58·4 mL)* 7/91 (8%) 6/90 (7%) Pain during examination[dagger] 2/29 (7%) 11/152 (7%) Bilateral lesions 2/16 (13%) 11/165(7%) Irregular walls 1/8 (13%) 12/173 (7%) Acoustic shadows 4/105 (4%) 9/76 (12%) Ascites 2/11 (18%) 11/170 (7%) Free fluid in the Pouch of Douglas 5/69 (7%) 8/112 (7%) Colour score 3-4 (moderate to abundant vascularisation) 3/49 (6%) 10/132 (8%) Typical appearance (colour score 1 or 2 plus acoustic shadows plus regular walls) 2/78 (3%) 11/103 (11%) Table 1 Number of malignant cases depending on the presence or absence of certain ultrasound features and clinical characteristics in solid tumours judged to be fibro(theco)mas

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.

To evaluate the performance of diagnostic prediction models for ovarian malignancy in all patients with an ovarian mass managed surgically or conservatively.OBJECTIVETo evaluate the performance of diagnostic prediction models for ovarian malignancy in all patients with an ovarian mass managed surgically or conservatively.Multicentre cohort study.DESIGNMulticentre cohort study.36 oncology referral centres (tertiary centres with a specific gynaecological oncology unit) or other types of centre.SETTING36 oncology referral centres (tertiary centres with a specific gynaecological oncology unit) or other types of centre.Consecutive adult patients presenting with an adnexal mass between January 2012 and March 2015 and managed by surgery or follow-up.PARTICIPANTSConsecutive adult patients presenting with an adnexal mass between January 2012 and March 2015 and managed by surgery or follow-up.Overall and centre specific discrimination, calibration, and clinical utility of six prediction models for ovarian malignancy (risk of malignancy index (RMI), logistic regression model 2 (LR2), simple rules, simple rules risk model (SRRisk), assessment of different neoplasias in the adnexa (ADNEX) with or without CA125). ADNEX allows the risk of malignancy to be subdivided into risks of a borderline, stage I primary, stage II-IV primary, or secondary metastatic malignancy. The outcome was based on histology if patients underwent surgery, or on results of clinical and ultrasound follow-up at 12 (±2) months. Multiple imputation was used when outcome based on follow-up was uncertain.MAIN OUTCOME MEASURESOverall and centre specific discrimination, calibration, and clinical utility of six prediction models for ovarian malignancy (risk of malignancy index (RMI), logistic regression model 2 (LR2), simple rules, simple rules risk model (SRRisk), assessment of different neoplasias in the adnexa (ADNEX) with or without CA125). ADNEX allows the risk of malignancy to be subdivided into risks of a borderline, stage I primary, stage II-IV primary, or secondary metastatic malignancy. The outcome was based on histology if patients underwent surgery, or on results of clinical and ultrasound follow-up at 12 (±2) months. Multiple imputation was used when outcome based on follow-up was uncertain.The primary analysis included 17 centres that met strict quality criteria for surgical and follow-up data (5717 of all 8519 patients). 812 patients (14%) had a mass that was already in follow-up at study recruitment, therefore 4905 patients were included in the statistical analysis. The outcome was benign in 3441 (70%) patients and malignant in 978 (20%). Uncertain outcomes (486, 10%) were most often explained by limited follow-up information. The overall area under the receiver operating characteristic curve was highest for ADNEX with CA125 (0.94, 95% confidence interval 0.92 to 0.96), ADNEX without CA125 (0.94, 0.91 to 0.95) and SRRisk (0.94, 0.91 to 0.95), and lowest for RMI (0.89, 0.85 to 0.92). Calibration varied among centres for all models, however the ADNEX models and SRRisk were the best calibrated. Calibration of the estimated risks for the tumour subtypes was good for ADNEX irrespective of whether or not CA125 was included as a predictor. Overall clinical utility (net benefit) was highest for the ADNEX models and SRRisk, and lowest for RMI. For patients who received at least one follow-up scan (n=1958), overall area under the receiver operating characteristic curve ranged from 0.76 (95% confidence interval 0.66 to 0.84) for RMI to 0.89 (0.81 to 0.94) for ADNEX with CA125.RESULTSThe primary analysis included 17 centres that met strict quality criteria for surgical and follow-up data (5717 of all 8519 patients). 812 patients (14%) had a mass that was already in follow-up at study recruitment, therefore 4905 patients were included in the statistical analysis. The outcome was benign in 3441 (70%) patients and malignant in 978 (20%). Uncertain outcomes (486, 10%) were most often explained by limited follow-up information. The overall area under the receiver operating characteristic curve was highest for ADNEX with CA125 (0.94, 95% confidence interval 0.92 to 0.96), ADNEX without CA125 (0.94, 0.91 to 0.95) and SRRisk (0.94, 0.91 to 0.95), and lowest for RMI (0.89, 0.85 to 0.92). Calibration varied among centres for all models, however the ADNEX models and SRRisk were the best calibrated. Calibration of the estimated risks for the tumour subtypes was good for ADNEX irrespective of whether or not CA125 was included as a predictor. Overall clinical utility (net benefit) was highest for the ADNEX models and SRRisk, and lowest for RMI. For patients who received at least one follow-up scan (n=1958), overall area under the receiver operating characteristic curve ranged from 0.76 (95% confidence interval 0.66 to 0.84) for RMI to 0.89 (0.81 to 0.94) for ADNEX with CA125.Our study found the ADNEX models and SRRisk are the best models to distinguish between benign and malignant masses in all patients presenting with an adnexal mass, including those managed conservatively.CONCLUSIONSOur study found the ADNEX models and SRRisk are the best models to distinguish between benign and malignant masses in all patients presenting with an adnexal mass, including those managed conservatively.ClinicalTrials.gov NCT01698632.TRIAL REGISTRATIONClinicalTrials.gov NCT01698632.