Patient decision aids in mainstreaming genetic testing for women with ovarian cancer: A prospective cohort study.

OBJECTIVE: To evaluate patient preference for short (gist) or detailed/extensive decision aids (DA) for genetic testing at ovarian cancer (OC) diagnosis. DESIGN: Cohort study set within recruitment to the Systematic Genetic Testing for Personalised Ovarian Cancer Therapy (SIGNPOST) study (ISRCTN: 16988857). SETTING: North-East London Cancer Network (NELCN) population. POPULATION/SAMPLE: Women with high-grade non-mucinous epithelial OC. METHODS: A more detailed DA was developed using patient and stakeholder input following the principles/methodology of IPDAS (International Patients Decision Aids Standards). Unselected patients attending oncology clinics evaluated both a pre-existing short and a new long DA version and then underwent mainstreaming genetic testing by a cancer clinician. Appropriate inferential descriptive and regression analyses were undertaken. MAIN OUTCOME MEASURES: Satisfaction, readability, understanding, emotional well-being and preference for long/short DA. RESULTS: The mean age of patients was 66 years (interquartile range 11), and 85% were White British ethnicity. Of the participants, 74% found DAs helpful/useful in decision-making. Women reported higher levels of satisfaction (86% versus 58%, p < 0.001), right amount of information provided (76.79% versus49.12%, p < 0.001) and improved understanding (p < 0.001) with the long DA compared with the short DA. There was no statistically significant difference in emotional outcomes (feeling worried/concerned/reassured/upset) between 'short' and 'long' DA; 74% of patients preferred the long DA and 24% the short DA. Patients undergoing treatment (correlation coefficient (coef) = 0.603; 95% CI 0.165-1.041, p = 0.007), those with recurrence (coef = 0.493; 95% CI 0.065-0.92, p = 0.024) and older women (coef = 0.042; 95% CI 0.017-0.066, p = 0.001) preferred the short DA. Ethnicity did not affect outcomes or overall preference for long/short DA. CONCLUSIONS: A longer DA in OC patients has higher satisfaction without increasing emotional distress. Older women and those undergoing treatment/recurrence prefer less extensive information, whereas those in remission preferred a longer DA.

Urine biomarkers enable pancreatic cancer detection up to 2 years before diagnosis.

The poor prognosis of pancreatic ductal adenocarcinoma (PDAC) is mainly attributed to late diagnosis. We assessed the predictive performance of our previously reported urine biomarker panel for earlier detection of PDAC (LYVE1, REG1B and TFF1) in prediagnostic samples, alone and in combination with plasma CA19-9. This nested case-control study included 99 PDAC cases with urine samples prospectively collected up to 5 years prior to PDAC diagnosis and 198 matched controls. The samples were obtained from the Shanghai Women's Health Study (SWHS), the Shanghai Men's Health Studies (SMHS) and the Southern Community Cohort Study (SCCS). The urine biomarkers were measured by ELISA. Plasma CA19-9 was quantified by Luminex. Multiple logistic regression and Wilcoxon rank-sum and Mann-Whitney test were used for analysis. The internal validation approach was applied and the validated AUC estimators are reported on. The algorithm of urinary protein panel, urine creatinine and age named PancRISK, displayed similar AUC as CA19-9 up to 1 year before PDAC diagnosis (AUC = 0.79); however, the combination enhanced the AUCs to 0.89, and showed good discriminative ability (AUC = 0.77) up to 2 years. The combination showed sensitivity (SN) of 72% at 90% specificity (SP), and SP of 59% at 90% SN up to 1 year and 60% SN with 80% SP and 53% SP with 80% SN up to 2 years before PDAC diagnosis. Adding the clinical information on BMI value resulted in the overall improvement in performance of the PancRISK score. When combined with CA19-9, the urinary panel reached a workable model for detecting PDAC cases up to 2 years prior to diagnosis.

Time series radiomics for the prediction of prostate cancer progression in patients on active surveillance.

Serial MRI is an essential assessment tool in prostate cancer (PCa) patients enrolled on active surveillance (AS). However, it has only moderate sensitivity for predicting histopathological tumour progression at follow-up, which is in part due to the subjective nature of its clinical reporting and variation among centres and readers. In this study, we used a long short-term memory (LSTM) recurrent neural network (RNN) to develop a time series radiomics (TSR) predictive model that analysed longitudinal changes in tumour-derived radiomic features across 297 scans from 76 AS patients, 28 with histopathological PCa progression and 48 with stable disease. Using leave-one-out cross-validation (LOOCV), we found that an LSTM-based model combining TSR and serial PSA density (AUC 0.86 [95% CI: 0.78-0.94]) significantly outperformed a model combining conventional delta-radiomics and delta-PSA density (0.75 [0.64-0.87]; p = 0.048) and achieved comparable performance to expert-performed serial MRI analysis using the Prostate Cancer Radiologic Estimation of Change in Sequential Evaluation (PRECISE) scoring system (0.84 [0.76-0.93]; p = 0.710). The proposed TSR framework, therefore, offers a feasible quantitative tool for standardising serial MRI assessment in PCa AS. It also presents a novel methodological approach to serial image analysis that can be used to support clinical decision-making in multiple scenarios, from continuous disease monitoring to treatment response evaluation. KEY POINTS: •LSTM RNN can be used to predict the outcome of PCa AS using time series changes in tumour-derived radiomic features and PSA density. •Using all available TSR features and serial PSA density yields a significantly better predictive performance compared to using just two time points within the delta-radiomics framework. •The concept of TSR can be applied to other clinical scenarios involving serial imaging, setting out a new field in AI-driven radiology research.

Risk factors for post-COVID-19 condition in previously hospitalised children using the ISARIC Global follow-up protocol: a prospective cohort study.

BACKGROUND: The long-term sequelae of coronavirus disease 2019 (COVID-19) in children remain poorly characterised. This study aimed to assess long-term outcomes in children previously hospitalised with COVID-19 and associated risk factors. METHODS: This is a prospective cohort study of children (≤18 years old) admitted to hospital with confirmed COVID-19. Children admitted between 2 April 2020 and 26 August 2020 were included. Telephone interviews used the International Severe Acute Respiratory and Emerging Infection Consortium (ISARIC) COVID-19 Health and Wellbeing Follow-up Survey for Children. Persistent symptoms (>5 months) were further categorised by system(s) involved. RESULTS: 518 out of 853 (61%) eligible children were available for the follow-up assessment and included in the study. Median (interquartile range (IQR)) age was 10.4 (3-15.2) years and 270 (52.1%) were girls. Median (IQR) follow-up since hospital discharge was 256 (223-271) days. At the time of the follow-up interview 126 (24.3%) participants reported persistent symptoms, among which fatigue (53, 10.7%), sleep disturbance (36, 6.9%) and sensory problems (29, 5.6%) were the most common. Multiple symptoms were experienced by 44 (8.4%) participants. Risk factors for persistent symptoms were: older age "6-11 years" (OR 2.74, 95% CI 1.37-5.75) and "12-18 years" (OR 2.68, 95% CI 1.41-5.4), and a history of allergic diseases (OR 1.67, 95% CI 1.04-2.67). CONCLUSIONS: A quarter of children experienced persistent symptoms months after hospitalisation with acute COVID-19 infection, with almost one in 10 experiencing multisystem involvement. Older age and allergic diseases were associated with higher risk of persistent symptoms at follow-up.

Comparative performance of MRI-derived PRECISE scores and delta-radiomics models for the prediction of prostate cancer progression in patients on active surveillance.

OBJECTIVES: To compare the performance of the PRECISE scoring system against several MRI-derived delta-radiomics models for predicting histopathological prostate cancer (PCa) progression in patients on active surveillance (AS). METHODS: The study included AS patients with biopsy-proven PCa with a minimum follow-up of 2 years and at least one repeat targeted biopsy. Histopathological progression was defined as grade group progression from diagnostic biopsy. The control group included patients with both radiologically and histopathologically stable disease. PRECISE scores were applied prospectively by four uro-radiologists with 5-16 years' experience. T2WI- and ADC-derived delta-radiomics features were computed using baseline and latest available MRI scans, with the predictive modelling performed using the parenclitic networks (PN), least absolute shrinkage and selection operator (LASSO) logistic regression, and random forests (RF) algorithms. Standard measures of discrimination and areas under the ROC curve (AUCs) were calculated, with AUCs compared using DeLong's test. RESULTS: The study included 64 patients (27 progressors and 37 non-progressors) with a median follow-up of 46 months. PRECISE scores had the highest specificity (94.7%) and positive predictive value (90.9%), whilst RF had the highest sensitivity (92.6%) and negative predictive value (92.6%) for predicting disease progression. The AUC for PRECISE (84.4%) was non-significantly higher than AUCs of 81.5%, 78.0%, and 80.9% for PN, LASSO regression, and RF, respectively (p = 0.64, 0.43, and 0.57, respectively). No significant differences were observed between AUCs of the three delta-radiomics models (p-value range 0.34-0.77). CONCLUSIONS: PRECISE and delta-radiomics models achieved comparably good performance for predicting PCa progression in AS patients. KEY POINTS: • The observed high specificity and PPV of PRECISE are complemented by the high sensitivity and NPV of delta-radiomics, suggesting a possible synergy between the two image assessment approaches. • The comparable performance of delta-radiomics to PRECISE scores applied by expert readers highlights the prospective use of the former as an objective and standardisable quantitative tool for MRI-guided AS follow-up. • The marginally superior performance of parenclitic networks compared to conventional machine learning algorithms warrants its further use in radiomics research.

Patient outcomes following interval and delayed cytoreductive surgery in advanced ovarian cancer: protocol for a multicenter, international, cohort study (Global Gynaecological Oncology Surgical Outcomes Collaborative).

BACKGROUND: The Global Gynecological Oncology Surgical Outcomes Collaborative (GO SOAR) has developed a network of gynecological oncology surgeons, surgical departments, and other interested parties that have the long-term ability to collaborate on outcome studies. Presented is the protocol for the GO SOAR2 study. PRIMARY OBJECTIVES: To compare survival following interval and delayed cytoreductive surgery, between delayed cytoreductive surgery and no surgery (chemotherapy alone); and international variations in access to cytoreductive surgery for women with stage III-IV epithelial ovarian cancer. STUDY HYPOTHESES: There is no difference in survival following interval and delayed cytoreductive surgery; there is poorer survival with no surgery compared with delayed cytoreductive surgery; and there are international disparities in prevalent practice and access to cytoreductive surgery in women with stage III-IV epithelial ovarian cancer. TRIAL DESIGN: International, multicenter, mixed-methods cohort study. Participating centers, will review medical charts/electronic records of patients who had been consecutively diagnosed with stage III-IV ovarian cancer between January 1, 2006 and December 31, 2021. Qualitative interviews will be conducted to identify factors determining international variations in prevalent practice and access to cytoreductive surgery. MAJOR INCLUSION/EXCLUSION CRITERIA: Inclusion criteria include women with stage III-IV epithelial ovarian cancer, undergoing interval (after 3-4 cycles of chemotherapy) or delayed (≥5 cycles of chemotherapy) cytoreductive surgeries or no cytoreductive surgery (≥5 cycles of chemotherapy alone). PRIMARY ENDPOINTS: Overall survival (defined from date of diagnosis to date of death); progression-free survival (defined from date of diagnosis to date of first recurrence); facilitator/barriers to prevalent practice and access to cytoreductive surgery. SAMPLE SIZE: In order to determine whether there is a difference in survival following interval and delayed cytoreductive surgery and no surgery, data will be abstracted from 1000 patients. ESTIMATED DATES FOR COMPLETING ACCRUAL AND PRESENTING RESULTS: It is estimated that recruitment will be completed by 2023, and results published by 2024. TRIAL REGISTRATION: NCT05523804.

Estimated Global Proportions of Individuals With Persistent Fatigue, Cognitive, and Respiratory Symptom Clusters Following Symptomatic COVID-19 in 2020 and 2021.

Importance: Some individuals experience persistent symptoms after initial symptomatic SARS-CoV-2 infection (often referred to as Long COVID). Objective: To estimate the proportion of males and females with COVID-19, younger or older than 20 years of age, who had Long COVID symptoms in 2020 and 2021 and their Long COVID symptom duration. Design, Setting, and Participants: Bayesian meta-regression and pooling of 54 studies and 2 medical record databases with data for 1.2 million individuals (from 22 countries) who had symptomatic SARS-CoV-2 infection. Of the 54 studies, 44 were published and 10 were collaborating cohorts (conducted in Austria, the Faroe Islands, Germany, Iran, Italy, the Netherlands, Russia, Sweden, Switzerland, and the US). The participant data were derived from the 44 published studies (10 501 hospitalized individuals and 42 891 nonhospitalized individuals), the 10 collaborating cohort studies (10 526 and 1906), and the 2 US electronic medical record databases (250 928 and 846 046). Data collection spanned March 2020 to January 2022. Exposures: Symptomatic SARS-CoV-2 infection. Main Outcomes and Measures: Proportion of individuals with at least 1 of the 3 self-reported Long COVID symptom clusters (persistent fatigue with bodily pain or mood swings; cognitive problems; or ongoing respiratory problems) 3 months after SARS-CoV-2 infection in 2020 and 2021, estimated separately for hospitalized and nonhospitalized individuals aged 20 years or older by sex and for both sexes of nonhospitalized individuals younger than 20 years of age. Results: A total of 1.2 million individuals who had symptomatic SARS-CoV-2 infection were included (mean age, 4-66 years; males, 26%-88%). In the modeled estimates, 6.2% (95% uncertainty interval [UI], 2.4%-13.3%) of individuals who had symptomatic SARS-CoV-2 infection experienced at least 1 of the 3 Long COVID symptom clusters in 2020 and 2021, including 3.2% (95% UI, 0.6%-10.0%) for persistent fatigue with bodily pain or mood swings, 3.7% (95% UI, 0.9%-9.6%) for ongoing respiratory problems, and 2.2% (95% UI, 0.3%-7.6%) for cognitive problems after adjusting for health status before COVID-19, comprising an estimated 51.0% (95% UI, 16.9%-92.4%), 60.4% (95% UI, 18.9%-89.1%), and 35.4% (95% UI, 9.4%-75.1%), respectively, of Long COVID cases. The Long COVID symptom clusters were more common in women aged 20 years or older (10.6% [95% UI, 4.3%-22.2%]) 3 months after symptomatic SARS-CoV-2 infection than in men aged 20 years or older (5.4% [95% UI, 2.2%-11.7%]). Both sexes younger than 20 years of age were estimated to be affected in 2.8% (95% UI, 0.9%-7.0%) of symptomatic SARS-CoV-2 infections. The estimated mean Long COVID symptom cluster duration was 9.0 months (95% UI, 7.0-12.0 months) among hospitalized individuals and 4.0 months (95% UI, 3.6-4.6 months) among nonhospitalized individuals. Among individuals with Long COVID symptoms 3 months after symptomatic SARS-CoV-2 infection, an estimated 15.1% (95% UI, 10.3%-21.1%) continued to experience symptoms at 12 months. Conclusions and Relevance: This study presents modeled estimates of the proportion of individuals with at least 1 of 3 self-reported Long COVID symptom clusters (persistent fatigue with bodily pain or mood swings; cognitive problems; or ongoing respiratory problems) 3 months after symptomatic SARS-CoV-2 infection.

Stop COVID Cohort: An Observational Study of 3480 Patients Admitted to the Sechenov University Hospital Network in Moscow City for Suspected Coronavirus Disease 2019 (COVID-19) Infection.

BACKGROUND: The epidemiology, clinical course, and outcomes of patients with coronavirus disease 2019 (COVID-19) in the Russian population are unknown. Information on the differences between laboratory-confirmed and clinically diagnosed COVID-19 in real-life settings is lacking. METHODS: We extracted data from the medical records of adult patients who were consecutively admitted for suspected COVID-19 infection in Moscow between 8 April and 28 May 2020. RESULTS: Of the 4261 patients hospitalized for suspected COVID-19, outcomes were available for 3480 patients (median age, 56 years; interquartile range, 45-66). The most common comorbidities were hypertension, obesity, chronic cardiovascular disease, and diabetes. Half of the patients (n = 1728) had a positive reverse transcriptase-polymerase chain reaction (RT-PCR), while 1748 had a negative RT-PCR but had clinical symptoms and characteristic computed tomography signs suggestive of COVID-19. No significant differences in frequency of symptoms, laboratory test results, and risk factors for in-hospital mortality were found between those exclusively clinically diagnosed or with positive severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RT-PCR. In a multivariable logistic regression model the following were associated with in-hospital mortality: older age (per 1-year increase; odds ratio, 1.05; 95% confidence interval, 1.03-1.06), male sex (1.71; 1.24-2.37), chronic kidney disease (2.99; 1.89-4.64), diabetes (2.1; 1.46-2.99), chronic cardiovascular disease (1.78; 1.24-2.57), and dementia (2.73; 1.34-5.47). CONCLUSIONS: Age, male sex, and chronic comorbidities were risk factors for in-hospital mortality. The combination of clinical features was sufficient to diagnose COVID-19 infection, indicating that laboratory testing is not critical in real-life clinical practice.

Incidence and risk factors for persistent symptoms in adults previously hospitalized for COVID-19.

BACKGROUND: The long-term sequalae of COVID-19 remain poorly characterized. We assessed persistent symptoms in previously hospitalized patients with COVID-19 and assessed potential risk factors. METHODS: Data were collected from patients discharged from 4 hospitals in Moscow, Russia between 8 April and 10 July 2020. Participants were interviewed via telephone using an ISARIC Long-term Follow-up Study questionnaire. RESULTS: 2,649 of 4755 (56%) discharged patients were successfully evaluated, at median 218 (IQR 200, 236) days post-discharge. COVID-19 diagnosis was clinical in 1291 and molecular in 1358. Most cases were mild, but 902 (34%) required supplemental oxygen and 68 (2.6%) needed ventilatory support. Median age was 56 years (IQR 46, 66) and 1,353 (51.1%) were women. Persistent symptoms were reported by 1247 (47.1%) participants, with fatigue (21.2%), shortness of breath (14.5%) and forgetfulness (9.1%) the most common symptoms and chronic fatigue (25%) and respiratory (17.2%) the most common symptom categories. Female sex was associated with any persistent symptom category OR 1.83 (95% CI 1.55 to 2.17) with association being strongest for dermatological (3.26, 2.36 to 4.57) symptoms. Asthma and chronic pulmonary disease were not associated with persistent symptoms overall, but asthma was associated with neurological (1.95, 1.25 to 2.98) and mood and behavioural changes (2.02, 1.24 to 3.18), and chronic pulmonary disease was associated with chronic fatigue (1.68, 1.21 to 2.32). CONCLUSIONS: Almost half of adults admitted to hospital due to COVID-19 reported persistent symptoms 6 to 8 months after discharge. Fatigue and respiratory symptoms were most common, and female sex was associated with persistent symptoms.

Media Influence on Anxiety, Health Utility, and Health Beliefs Early in the SARS-CoV-2 Pandemic-a Survey Study.

BACKGROUND: The psychological effects from the COVID-19 pandemic and response are poorly understood. OBJECTIVE: To understand the effects of the pandemic and response on anxiety and health utility in a nationally representative sample of US adults. DESIGN: A de-identified, cross-sectional survey was administered at the end of April 2020. Probability weights were assigned using estimates from the 2018 American Community Survey and Integrated Public Use Microdata Series Estimates. PARTICIPANTS: US adults 18-85 years of age with landline, texting-enabled cellphone, or internet access. INTERVENTION: Seven split-half survey blocks of 30 questions, assessing demographics, COVID-19-related health attitudes, and standardized measures of generalized self-efficacy, anxiety, depression, personality, and generic health utility. MAIN MEASURES: State/Trait anxiety scores, EQ-5D-3L Visual Analog Scale (VAS) score, and demographic predictors of these scores. KEY RESULTS: Among 4855 respondents, 56.7% checked COVID-19-related news several times daily, and 84.4% at least once daily. Only 65.7% desired SARS-CoV-2 vaccination for themselves, and 70.1% for their child. Mean state anxiety (S-anxiety) score was significantly higher than mean trait anxiety (T-anxiety) score (44.9, 95%CI 43.5-46.3 vs. 41.6, 95%CI 38.7-44.5; p = 0.03), with both scores significantly higher than previously published norms. In an adjusted regression model, less frequent news viewing was associated with significantly lower S-anxiety score. Mean EQ-5D-3L VAS score for the population was significantly lower vs. established US normative data (71.4 CI 67.4-75.5, std. error 2 vs. societal mean 80, std. error 0.1; p < 0.001). EQ-5D-3L VAS score was bimodal (highest with hourly and no viewing) and significantly reduced with less media viewership in an adjusted model. CONCLUSIONS: Among a nationally representative sample, there were higher S-anxiety and lower EQ-5D-3L VAS scores compared to non-pandemic normative data, indicative of a potential detrimental acute effect of the pandemic. More frequent daily media viewership was significantly associated with higher S-anxiety but also predictive of higher health utility, as measured by EQ-5D-3L VAS scores.

Determining post-operative morbidity and mortality following gynecological oncology surgery: protocol for a multicenter, international, prospective cohort study (Global Gynaecological Oncology Surgical Outcomes Collaborative-GO SOAR).

BACKGROUND: The Global Gynaecological Oncology Surgical Outcomes Collaborative (GO SOAR) aims to develop a network of gynecological oncology surgeons, surgical departments, and other interested parties that will have the long-term ability to collaborate on outcome studies. The protocol for the first collaborative study is presented here. PRIMARY OBJECTIVE: To evaluate international variation in 30-day post-operative morbidity and mortality following gynecological oncology surgery between very high/high and medium/low human development index country settings. HYPOTHESIS: There is no variation in post-operative morbidity and mortality following gynecological oncology surgery between very high/high and medium/low human development index country settings. STUDY DESIGN: International, multicenter, prospective cohort study. Patient data will be collected over a consecutive 30-day period through gynecological oncology multidisciplinary teams/tumor boards and clinics across different human development index country groups. All data are collected on a customized, secure, password protected, central REDCap database. MAJOR INCLUSION/EXCLUSION CRITERIA: Inclusion criteria include women aged ≥18 years undergoing elective/emergency, curative/palliative surgery for primary/recurrent tubo-ovarian/peritoneal, endometrial, cervical, vulval, vaginal, gestational trophoblastic malignancies. Surgical modality may be open, minimal access (laparoscopic/robotic), or vaginal. PRIMARY ENDPOINT: 30-day post-operative morbidity and mortality defined as per Clavien-Dindo classification system. SAMPLE SIZE: 1100 (550/arm). ESTIMATED DATES FOR COMPLETING ACCRUAL AND PRESENTING RESULTS: It is estimated recruitment will be completed by 2022 and results published by 2023. TRIAL REGISTRATION: ClinicalTrials.gov registry: NCT04579861 (https://clinicaltrials.gov/ct2/show/NCT04579861).

Impact of SARS-CoV-2 on training and mental well-being of surgical gynecological oncology trainees.

INTRODUCTION: The SARS-CoV-2 global pandemic has caused a crisis disrupting health systems worldwide. While efforts are being made to determine the extent of the disruption, the impact on gynecological oncology trainees/training has not been explored. We conducted an international survey of the impact of SARS-CoV-2 on clinical practice, medical education, and mental well-being of surgical gynecological oncology trainees. METHODS: In our cross-sectional study, a customized web-based survey was circulated to surgical gynecological oncology trainees from national/international organizations from May to November 2020. Validated questionnaires assessed mental well-being. The Wilcoxon rank-sum test and Fisher's exact test were used to analyse differences in means and proportions. Multiple linear regression was used to evaluate the effect of variables on psychological/mental well-being outcomes. Outcomes included clinical practice, medical education, anxiety and depression, distress, and mental well-being. RESULTS: A total of 127 trainees from 34 countries responded. Of these, 52% (66/127) were from countries with national training programs (UK/USA/Netherlands/Canada/Australia) and 48% (61/127) from countries with no national training programs. Altogether, 28% (35/125) had suspected/confirmed COVID-19, 28% (35/125) experienced a fall in household income, 20% (18/90) were self-isolated from households, 45% (57/126) had to re-use personal protective equipment, and 22% (28/126) purchased their own. In total, 32.3% (41/127) of trainees (16.6% (11/66) from countries with a national training program vs 49.1% (30/61) from countries with no national training program, p=0.02) perceived they would require additional time to complete their training fellowship. The additional training time anticipated did not differ between trainees from countries with or without national training programs (p=0.11) or trainees at the beginning or end of their fellowship (p=0.12). Surgical exposure was reduced for 50% of trainees. Departmental teaching continued throughout the pandemic for 69% (87/126) of trainees, although at reduced frequency for 16.1% (14/87), and virtually for 88.5% (77/87). Trainees reporting adequate pastoral support (defined as allocation of a dedicated mentor/access to occupational health support services) had better mental well-being with lower levels of anxiety/depression (p=0.02) and distress (p<0.001). Trainees from countries with a national training program experienced higher levels of distress (p=0.01). Mean (SD) pre-pandemic mental well-being scores were significantly higher than post-pandemic scores (8.3 (1.6) vs 7 (1.8); p<0.01). CONCLUSION: SARS-CoV-2 has negatively impacted the surgical training, household income, and psychological/mental well-being of surgical gynecological oncology trainees. The overall clinical impact was worse for trainees in countries with no national training program than for those in countries with a national training program, although national training program trainees reported greater distress. COVID-19 sickness increased anxiety/depression. The recovery phase must focus on improving mental well-being and addressing lost training opportunities.

Effect of mammographic screening from age 40 years on breast cancer mortality (UK Age trial): final results of a randomised, controlled trial.

BACKGROUND: The appropriate age range for breast cancer screening remains a matter of debate. We aimed to estimate the effect of mammographic screening at ages 40-48 years on breast cancer mortality. METHODS: We did a randomised, controlled trial involving 23 breast screening units across Great Britain. We randomly assigned women aged 39-41 years, using individual randomisation, stratified by general practice, in a 1:2 ratio, to yearly mammographic screening from the year of inclusion in the trial up to and including the calendar year that they reached age 48 years (intervention group), or to standard care of no screening until the invitation to their first National Health Service Breast Screening Programme (NHSBSP) screen at approximately age 50 years (control group). Women in the intervention group were recruited by postal invitation. Women in the control group were unaware of the study. The primary endpoint was mortality from breast cancers (with breast cancer coded as the underlying cause of death) diagnosed during the intervention period, before the participant's first NHSBSP screen. To study the timing of the mortality effect, we analysed the results in different follow-up periods. Women were included in the primary comparison regardless of compliance with randomisation status (intention-to-treat analysis). This Article reports on long-term follow-up analysis. The trial is registered with the ISRCTN registry, ISRCTN24647151. FINDINGS: 160 921 women were recruited between Oct 14, 1990, and Sept 24, 1997. 53 883 women (33·5%) were randomly assigned to the intervention group and 106 953 (66·5%) to the control group. Between randomisation and Feb 28, 2017, women were followed up for a median of 22·8 years (IQR 21·8-24·0). We observed a significant reduction in breast cancer mortality at 10 years of follow-up, with 83 breast cancer deaths in the intervention group versus 219 in the control group (relative rate [RR] 0·75 [95% CI 0·58-0·97]; p=0·029). No significant reduction was observed thereafter, with 126 deaths versus 255 deaths occurring after more than 10 years of follow-up (RR 0·98 [0·79-1·22]; p=0·86). INTERPRETATION: Yearly mammography before age 50 years, commencing at age 40 or 41 years, was associated with a relative reduction in breast cancer mortality, which was attenuated after 10 years, although the absolute reduction remained constant. Reducing the lower age limit for screening from 50 to 40 years could potentially reduce breast cancer mortality. FUNDING: National Institute for Health Research Health Technology Assessment programme.

A combination of urinary biomarker panel and PancRISK score for earlier detection of pancreatic cancer: A case-control study.

BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) is one of the deadliest cancers, with around 9% of patients surviving >5 years. Asymptomatic in its initial stages, PDAC is mostly diagnosed late, when already a locally advanced or metastatic disease, as there are no useful biomarkers for detection in its early stages, when surgery can be curative. We have previously described a promising biomarker panel (LYVE1, REG1A, and TFF1) for earlier detection of PDAC in urine. Here, we aimed to establish the accuracy of an improved panel, including REG1B instead of REG1A, and an algorithm for data interpretation, the PancRISK score, in additional retrospectively collected urine specimens. We also assessed the complementarity of this panel with CA19-9 and explored the daily variation and stability of the biomarkers and their performance in common urinary tract cancers. METHODS AND FINDINGS: Clinical specimens were obtained from multiple centres: Barts Pancreas Tissue Bank, University College London, University of Liverpool, Spanish National Cancer Research Center, Cambridge University Hospital, and University of Belgrade. The biomarker panel was assayed on 590 urine specimens: 183 control samples, 208 benign hepatobiliary disease samples (of which 119 were chronic pancreatitis), and 199 PDAC samples (102 stage I-II and 97 stage III-IV); 50.7% were from female individuals. PDAC samples were collected from patients before treatment. The samples were assayed using commercially available ELISAs. Statistical analyses were performed using non-parametric Kruskal-Wallis tests adjusted for multiple comparisons, and multiple logistic regression. Training and validation datasets for controls and PDAC samples were obtained after random division of the whole available dataset in a 1:1 ratio. The substitution of REG1A with REG1B enhanced the performance of the panel to detect resectable PDAC. In a comparison of controls and PDAC stage I-II samples, the areas under the receiver operating characteristic curve (AUCs) increased from 0.900 (95% CI 0.843-0.957) and 0.926 (95% CI 0.843-1.000) in the training (50% of the dataset) and validation sets, respectively, to 0.936 in both the training (95% CI 0.903-0.969) and the validation (95% CI 0.888-0.984) datasets for the new panel including REG1B. This improved panel showed both sensitivity (SN) and specificity (SP) to be >85%. Plasma CA19-9 enhanced the performance of this panel in discriminating PDAC I-II patients from controls, with AUC = 0.992 (95% CI 0.983-1.000), SN = 0.963 (95% CI 0.913-1.000), and SP = 0.967 (95% CI 0.924-1.000). We demonstrate that the biomarkers do not show significant daily variation, and that they are stable for up to 5 days at room temperature. The main limitation of our study is the low number of stage I-IIA PDAC samples (n = 27) and lack of samples from individuals with hereditary predisposition to PDAC, for which specimens collected from control individuals were used as a proxy. CONCLUSIONS: We have successfully validated our urinary biomarker panel, which was improved by substituting REG1A with REG1B. At a pre-selected cutoff of >80% SN and SP for the affiliated PancRISK score, we demonstrate a clinically applicable risk stratification tool with a binary output for risk of developing PDAC ('elevated' or 'normal'). PancRISK provides a step towards precision surveillance for PDAC patients, which we will test in a prospective clinical study, UroPanc.

Development of PancRISK, a urine biomarker-based risk score for stratified screening of pancreatic cancer patients.

BACKGROUND: An accurate and simple risk prediction model that would facilitate earlier detection of pancreatic adenocarcinoma (PDAC) is not available at present. In this study, we compare different algorithms of risk prediction in order to select the best one for constructing a biomarker-based risk score, PancRISK. METHODS: Three hundred and seventy-nine patients with available measurements of three urine biomarkers, (LYVE1, REG1B and TFF1) using retrospectively collected samples, as well as creatinine and age, were randomly split into training and validation sets, following stratification into cases (PDAC) and controls (healthy patients). Several machine learning algorithms were used, and their performance characteristics were compared. The latter included AUC (area under ROC curve) and sensitivity at clinically relevant specificity. RESULTS: None of the algorithms significantly outperformed all others. A logistic regression model, the easiest to interpret, was incorporated into a PancRISK score and subsequently evaluated on the whole data set. The PancRISK performance could be even further improved when CA19-9, commonly used PDAC biomarker, is added to the model. CONCLUSION: PancRISK score enables easy interpretation of the biomarker panel data and is currently being tested to confirm that it can be used for stratification of patients at risk of developing pancreatic cancer completely non-invasively, using urine samples.

Improved early detection of ovarian cancer using longitudinal multimarker models.

BACKGROUND: Ovarian cancer has a poor survival rate due to late diagnosis and improved methods are needed for its early detection. Our primary objective was to identify and incorporate additional biomarkers into longitudinal models to improve on the performance of CA125 as a first-line screening test for ovarian cancer. METHODS: This case-control study nested within UKCTOCS used 490 serial serum samples from 49 women later diagnosed with ovarian cancer and 31 control women who were cancer-free. Proteomics-based biomarker discovery was carried out using pooled samples and selected candidates, including those from the literature, assayed in all serial samples. Multimarker longitudinal models were derived and tested against CA125 for early detection of ovarian cancer. RESULTS: The best performing models, incorporating CA125, HE4, CHI3L1, PEBP4 and/or AGR2, provided 85.7% sensitivity at 95.4% specificity up to 1 year before diagnosis, significantly improving on CA125 alone. For Type II cases (mostly high-grade serous), models achieved 95.5% sensitivity at 95.4% specificity. Predictive values were elevated earlier than CA125, showing the potential of models to improve lead time. CONCLUSIONS: We have identified candidate biomarkers and tested longitudinal multimarker models that significantly improve on CA125 for early detection of ovarian cancer. These models now warrant independent validation.

Excessive Media Consumption About COVID-19 is Associated With Increased State Anxiety: Outcomes of a Large Online Survey in Russia.

BACKGROUND: The COVID-19 pandemic has potentially had a negative impact on the mental health and well-being of individuals and families. Anxiety levels and risk factors within particular populations are poorly described. OBJECTIVE: This study aims to evaluate confidence, understanding, trust, concerns, and levels of anxiety during the COVID-19 pandemic in the general population and assess risk factors for increased anxiety. METHODS: We launched a cross-sectional online survey of a large Russian population between April 6 and 15, 2020, using multiple social media platforms. A set of questions targeted confidence, understanding, trust, and concerns in respondents. The State-Trait Anxiety Inventory was used to measure anxiety. Multiple linear regressions were used to model predictors of COVID-19-related anxiety. RESULTS: The survey was completed by 23,756 out of 53,966 (44.0% response rate) unique visitors; of which, 21,364 were residing in 62 areas of Russia. State Anxiety Scale (S-Anxiety) scores were higher than Trait Anxiety Scale scores across all regions of Russia (median S-Anxiety score 52, IQR 44-60), exceeding published norms. Time spent following news on COVID-19 was strongly associated with an increased S-Anxiety adjusted for baseline anxiety level. One to two hours spent reading COVID-19 news was associated with a 5.46 (95% CI 5.03-5.90) point difference, 2-3 hours with a 7.06 (95% CI 6.37-7.74) point difference, and more than three hours with an 8.65 (95% CI 7.82-9.47) point difference, all compared to less than 30 minutes per day. Job loss during the pandemic was another important factor associated with higher S-Anxiety scores (3.95, 95% CI 3.31-4.58). Despite survey respondents reporting high confidence in information regarding COVID-19 as well as an understanding of health care guidance, they reported low overall trust in state and local authorities, and perception of country readiness. CONCLUSIONS: Among Russian respondents from multiple social media platforms, there was evidence of higher levels of state anxiety associated with recent job loss and increased news consumption, as well as lower than expected trust in government agencies. These findings can help inform the development of key public health messages to help reduce anxiety and raise perceived trust in governmental response to this current national emergency. Using a similar methodology, comparative surveys are ongoing in other national populations.

Transforming growth factor beta in human milk and allergic outcomes in children: A systematic review.

BACKGROUND: Human milk (HM) transforming growth factor beta (TGF-ß) is critical for inflammation regulation and oral tolerance promotion. Previous reports suggested that variations in HM TGF-ß levels are associated with allergic outcomes. OBJECTIVE: We undertook a systematic review (PROSPERO 2017 CRD42017069920) to reassess the evidence on the relationships between HM TGF-ß and allergic outcomes in children. METHODS: Electronic bibliographic databases (MEDLINE, EMBASE and Cochrane Library) were systematically searched. Two independent reviewers screened reference lists, extracted the data and assessed risk of bias using the National Institute for Clinical Excellence methodological checklist. RESULTS: A total of 21 studies were identified. Sixteen studies assessed relationships between HM TGF-ß and risk of eczema; 14, allergic sensitization; nine, wheezing/asthma; six, food allergy; three, allergic rhinitis/conjunctivitis. Five cohorts (5/18, 28%) reported a protective effect of TGF-ß1, while 3 (3/10, 30%) suggested increased risk of allergic outcomes development and 1 (1/10, 10%), a protective effect of TGF-ß2 on eczema. Meta-analysis was not possible due to significant heterogeneity in methodology, age of outcome assessment and differing statistical approaches. 71% (15/21) of studies carried a high risk of bias. CONCLUSION AND CLINICAL RELEVANCE: In contrast with previous findings, we did not find strong evidence of associations between HM TGF-ß and allergic outcomes. Differences in studies' methodology and outcomes do not allow unconditional rejection or acceptance of the hypothesis that HM TGF-ß influences the risk of allergy development. Future studies on diverse populations employing standardized methods, accurate phenotyping of outcomes and evaluation of the effect of TGF-ß in combination with other HM immune markers, microbiome and oligosaccharides are required.

Discovery of non-invasive biomarkers for the diagnosis of endometriosis.

BACKGROUND: Endometriosis is a common gynaecological disorder affecting 5-10% of women of reproductive age who often experience chronic pelvic pain and infertility. Definitive diagnosis is through laparoscopy, exposing patients to potentially serious complications, and is often delayed. Non-invasive biomarkers are urgently required to accelerate diagnosis and for triaging potential patients for surgery. METHODS: This retrospective case control biomarker discovery and validation study used quantitative 2D-difference gel electrophoresis and tandem mass tagging-liquid chromatography-tandem mass spectrometry for protein expression profiling of eutopic and ectopic endometrial tissue samples collected from 28 cases of endometriosis and 18 control patients undergoing surgery for investigation of chronic pelvic pain without endometriosis or prophylactic surgery. Samples were further sub-grouped by menstrual cycle phase. Selected differentially expressed candidate markers (LUM, CPM, TNC, TPM2 and PAEP) were verified by ELISA in a set of 87 serum samples collected from the same and additional women. Previously reported biomarkers (CA125, sICAM1, FST, VEGF, MCP1, MIF and IL1R2) were also validated and diagnostic performance of markers and combinations established. RESULTS: Cycle phase and endometriosis-associated proteomic changes were identified in eutopic tissue from over 1400 identified gene products, yielding potential biomarker candidates. Bioinformatics analysis revealed enrichment of adhesion/extracellular matrix proteins and progesterone signalling. The best single marker for discriminating endometriosis from controls remained CA125 (AUC = 0.63), with the best cross-validated multimarker models improving the AUC to 0.71-0.81, depending upon menstrual cycle phase and control group. CONCLUSIONS: We have identified menstrual cycle- and endometriosis-associated protein changes linked to various cellular processes that are potential biomarkers and that provide insight into the biology of endometriosis. Our data indicate that the markers tested, whilst not useful alone, have improved diagnostic accuracy when used in combination and demonstrate menstrual cycle specificity. Tissue heterogeneity and blood contamination is likely to have hindered biomarker discovery, whilst a small sample size precludes accurate determination of performance by cycle phase. Independent validation of these biomarker panels in a larger cohort is however warranted, and if successful, they may have clinical utility in triaging patients for surgery.

Current detection rates and time-to-detection of all identifiable BRCA carriers in the Greater London population.

BACKGROUND: BRCA carrier identification offers opportunities for early diagnoses, targeted treatment and cancer prevention. We evaluate BRCA- carrier detection rates in general and Ashkenazi Jewish (AJ) populations across Greater London and estimate time-to-detection of all identifiable BRCA carriers. METHODS: BRCA carrier data from 1993 to 2014 were obtained from National Health Service genetic laboratories and compared with modelled predictions of BRCA prevalence from published literature and geographical data from UK Office for National Statistics. Proportion of BRCA carriers identified was estimated. Prediction models were developed to fit BRCA detection rate data. BRCA carrier identification rates were evaluated for an 'Angelina Jolie effect'. Maps for four Greater London regions were constructed, and their relative BRCA detection rates were compared. Models developed were used to predict future time-to-identify all detectable BRCA carriers in AJ and general populations. RESULTS: Until 2014, only 2.6% (3072/111 742 estimated) general population and 10.9% (548/4985 estimated) AJ population BRCA carriers have been identified in 16 696 608 (AJ=190 997) Greater London population. 57% general population and 54% AJ mutations were identified through cascade testing. Current detection rates mirror linear fit rather than parabolic model and will not identify all BRCA carriers. Addition of unselected ovarian/triple-negative breast cancer testing would take >250 years to identify all BRCA carriers. Doubling current detection rates can identify all 'detectable' BRCA carriers in the general population by year 2181, while parabolic and triple linear rates can identify 'detectable' BRCA carriers by 2084 and 2093, respectively. The linear fit model can identify 'detectable' AJ carriers by 2044. We did not find an Angelina Jolie effect on BRCA carrier detection rates. There was a significant difference in BRCA detection rates between geographical regions over time (P<0.001). CONCLUSIONS: The majority of BRCA carriers have not been identified, missing key opportunities for prevention/earlier diagnosis. Enhanced and new strategies/approaches are needed.