The avoiding late diagnosis of ovarian cancer (ALDO) project; a pilot national surveillance programme for women with pathogenic germline variants in BRCA1 and BRCA2.

BACKGROUND: Our study aimed to establish 'real-world' performance and cost-effectiveness of ovarian cancer (OC) surveillance in women with pathogenic germline BRCA1/2 variants who defer risk-reducing bilateral salpingo-oophorectomy (RRSO). METHODS: Our study recruited 875 female BRCA1/2-heterozygotes at 13 UK centres and via an online media campaign, with 767 undergoing at least one 4-monthly surveillance test with the Risk of Ovarian Cancer Algorithm (ROCA) test. Surveillance performance was calculated with modelling of occult cancers detected at RRSO. The incremental cost-effectiveness ratio (ICER) was calculated using Markov population cohort simulation. RESULTS: Our study identified 8 OCs during 1277 women screen years: 2 occult OCs at RRSO (both stage 1a), and 6 screen-detected; 3 of 6 (50%) were ≤stage 3a and 5 of 6 (83%) were completely surgically cytoreduced. Modelled sensitivity, specificity, Positive Predictive Value (PPV) and Negative Predictive Value (NPV) for OC were 87.5% (95% CI, 47.3 to 99.7), 99.9% (99.9-100), 75% (34.9-96.8) and 99.9% (99.9-100), respectively. The predicted number of quality-adjusted life years (QALY) gained by surveillance was 0.179 with an ICER cost-saving of -£102,496/QALY. CONCLUSION: OC surveillance for women deferring RRSO in a 'real-world' setting is feasible and demonstrates similar performance to research trials; it down-stages OC, leading to a high complete cytoreduction rate and is cost-saving in the UK National Health Service (NHS) setting. While RRSO remains recommended management, ROCA-based surveillance may be considered for female BRCA-heterozygotes who are deferring such surgery.

Changing trends in reproductive/lifestyle factors in UK women: descriptive study within the UK Collaborative Trial of Ovarian Cancer Screening (UKCTOCS).

OBJECTIVE: There has been considerable interest in the impact of reproductive factors on health but there are little data on how these have varied over time. We explore trends in reproductive/lifestyle factors of postmenopausal British women by analysing self-reported data from participants of the UK Collaborative Trial of Ovarian Cancer Screening (UKCTOCS). DESIGN: Prospective birth cohort analysis. SETTING: Population cohort invited between 2001 and 2005 from age-sex registers of 27 Primary Care Trusts in England, Wales and Northern Ireland and recruited through 13 National Health Service Trusts. PARTICIPANTS: 202 638 postmenopausal women aged 50-74 years at randomisation to UKCTOCS between April 2001 and October 2005. INTERVENTIONS: Women were stratified into the following six birth cohorts (1925-1929, 1930-1934, 1935-1939, 1940-1944, 1945-1949, 1950-1955) based on year of birth. Self-reported data on reproductive factors provided at recruitment were explored using tabular and graphical summaries to examine for differences between the birth cohorts. OUTCOME MEASURES: Trends in mean age at menarche and menopause, use of oral contraceptives, change in family size, infertility treatments, tubal ligation and hysterectomy rates. RESULTS: Women born between 1935 and 1955 made up 86% of the cohort. Median age at menarche decreased from 13.4 for women born between 1925 and 1929 to 12.8 for women born between 1950 and 1955. Increased use of the oral contraceptives, infertility treatments and smaller family size was observed in the younger birth cohorts. Tubal ligation rates increased for those born between 1925 and 1945, but this increase did not persist in subsequent cohorts. Hysterectomy rates (17-20%) did not change over time. CONCLUSIONS: The trends seen in this large cohort are likely to reflect the reproductive history of the UK female postmenopausal population of similar age. Since these are risk factors for hormone-related cancers, these trends are important in understanding the changing incidence of these cancers. TRIAL REGISTRATION NUMBER: International Standard Randomised Controlled Trial Number: 22488978.

Potential effect of the risk of ovarian cancer algorithm (ROCA) on the mortality outcome of the Prostate, Lung, Colorectal and Ovarian (PLCO) trial.

Recently, the Prostate, Lung, Colorectal and Ovarian (PLCO) Trial reported no mortality benefit for annual screening with CA-125 and transvaginal ultrasound (TVU). Currently ongoing is the UK Collaborative Trial of Ovarian Cancer Screening (UKCTOCS), which utilizes the risk of ovarian cancer algorithm (ROCA), a statistical tool that considers current and past CA125 values to determine ovarian cancer risk. In contrast, PLCO used a single cutoff for CA125, based on current levels alone. We investigated whether having had used ROCA in PLCO could have, under optimal assumptions, resulted in a significant mortality benefit by applying ROCA to PLCO CA125 screening values. A best-case scenario assumed that all cancers showing a positive screen result earlier with ROCA than under the PLCO protocol would have avoided mortality; under a stage-shift scenario, such women were assigned survival equivalent to Stage I/II screen-detected cases. Updated PLCO data show 132 intervention arm ovarian cancer deaths versus 119 in usual care (relative risk, RR = 1.11). Forty-three ovarian cancer cases, 25 fatal, would have been detected earlier with ROCA, with a median (minimum) advance time for fatal cases of 344 (147) days. Best-case and stage-shift scenarios gave 25 and 19 deaths prevented with ROCA, for RRs of 0.90 (95% CI: 0.69-1.17) and 0.95 (95% CI: 0.74-1.23), respectively. Having utilized ROCA in PLCO would not have led to a significant mortality benefit of screening. However, ROCA could still show a significant effect in other screening trials, including UKCTOCS.

Recruitment to multicentre trials--lessons from UKCTOCS: descriptive study.

OBJECTIVE: To describe the factors that contributed to successful recruitment of more than 200,000 women to the UK Collaborative Trial of Ovarian Cancer Screening, one of the largest ever randomised controlled trials. DESIGN: Descriptive study. SETTING: 13 NHS trusts in England, Wales, and Northern Ireland. PARTICIPANTS: Postmenopausal women aged 50-74; exclusion criteria included ovarian malignancy, bilateral oophorectomy, increased risk of familial ovarian cancer, active non-ovarian malignancy, and participation in other ovarian cancer screening trials. MAIN OUTCOME MEASURES: Achievement of target recruitment, acceptance rates of invitation, and recruitment rates. RESULTS: The trial was set up in 13 centres with 27 adjoining local health authorities. The coordinating centre team was led by one of the senior investigators, who was closely involved in planning and day to day trial management. Of 1 243,282 women invited, 23.2% (288 955) replied that they were eligible and would like to participate. Of those sent appointments, 73.6% (205 090) attended for recruitment. The acceptance rate varied from 19% to 33% between trial centres. Measures to ensure target recruitment included named coordinating centre staff supporting and monitoring each centre, prompt identification and resolution of logistic problems, varying the volume of invitations by centre, using local non-attendance rates to determine the size of recruitment clinics, and organising large ad hoc clinics supported by coordinating centre staff. The trial randomised 202,638 women in 4.3 years. CONCLUSIONS: Planning and trial management are as important as trial design and require equal attention from senior investigators. Successful recruitment needs constant monitoring by a committed proactive management team that is willing to explore individual solutions for different centres and use central resources to improve local recruitment. Automation of trial processes with web based trial management systems is crucial in large multicentre randomised controlled trials. Recruitment can be further enhanced by using information videos and group discussions. Trial registration Current Controlled Trials ISRCTN22488978.

Development of multimarker panel for early detection of endometrial cancer. High diagnostic power of prolactin.

OBJECTIVE: Endometrial carcinoma is the most common gynecologic cancer. Although the prognosis for endometrial cancer is generally good, cancers identified at late stages are associated with high levels of morbidity and mortality. Therefore, prevention and early detection may further reduce the burden of this challenging disease. METHODS: A panel of 64 serum biomarkers was analyzed in sera of patients with stages I-III endometrial cancer and age-matched healthy women, utilizing a multiplex xMAP bead-based immunoassay. For multivariate analysis, four different statistical classification methods were used: logistic regression (LR), separating hyperplane (SHP), k nearest neighbors (KNN), and classification tree (CART). For each of these classifiers, a diagnostic model was created based on the cross-validation set consisting of sera from 115 patients with endometrial cancer and 135 healthy women. RESULTS: Our data have demonstrated that patients with endometrial cancer have significantly different expression patterns of several serum biomarkers as compared to healthy controls. Prolactin was the strongest discriminative biomarker for endometrial cancer providing 98.3% sensitivity and 98.0% specificity alone. Our results have revealed that serum concentration of cancer antigens, including CA 125, CA 15-3, and CEA are higher in patients with Stage III endometrial cancer as compared to those with Stage I. In addition, we have shown that the expression of CA 125, AFP, and ACTH is elevated in women with tumor grade 3 vs. grade 1. Furthermore, five-biomarker panel (prolactin, GH, Eotaxin, E-selectin, and TSH) identified in this study was able to discriminate endometrial cancer from ovarian and breast cancers with high sensitivity and specificity. CONCLUSIONS: The ability of prolactin to accurately discriminate between cancer and control groups indicates that this biomarker could potentially be used for development of blood-based test for the early detection of endometrial cancer in high-risk populations. Combining the information on multiple serum markers using flexible statistical methods allows for achieving high cancer selectivity.