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Early detection of ovarian cancer has the potential to impact mortality. A multimodal screening strategy where rising CA125 values over time, analyzed with the risk of ovarian cancer algorithm (ROCA), triggers transvaginal sonography and possible surgery has high sensitivity and specificity, but still fails to detect the 20% of early-stage cases that do not express CA125. Use of multiple biomarkers could detect cases missed by CA125. We have studied the sensitivity and lead time of a multi-marker panel (CA125, HE4, MMP-7, and CA 72-4) compared with CA125 alone. We used PRoBE design principles to select preclinical longitudinal specimens from 75 women (50 screen-positive, 25 screen-negative) who developed invasive epithelial ovarian cancer (3–5 serial specimens each) and 547 corresponding healthy controls (1–10 serial specimens each) from the ovarian cancer screening trial, UKCTOCS, in a blinded fashion. We measured the multi-marker concentrations in ultra-low serum volumes (16 μL) utilizing multiplexed bead-based immunoassays with low detection limits, high inter- and intra-assay precision, negligible cross-reactivity, and good correlation with standard immunoassays. While, at least one of the complementary biomarkers rose with CA125 in 44% (22/50) of screen-positive cases, there was no advantage in lead time over CA125. Therefore, we developed single-marker longitudinal algorithms (ROCA-like) to determine the presence of a change point to distinguish between the cases and controls. Using these algorithms, at 98% specificity, HE4 and CA72-4 identified 16% (4/25) of screen-negative cases, while MMP-7 identified none. Taken together, HE4 and CA72-4 show promise as complementary biomarkers to CA125 for longitudinal screening.

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Related Articles from The Sine Qua Non of Discovering Novel Biomarkers for Early Detection of Ovarian Cancer: Carefully Selected Preclinical Samples

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Supplementary figures, tables and materials & methods Supplementary Figure 1. Schematic presentation of steps in immunoassay development, validation and studies for screening TP53 autoantibody in human serum samples. Supplementary Figure 2. Identifying a common cut-off value for TP53 autoantibody immunoassay. Supplementary Table 1. Characteristics of patients with invasive epithelial ovarian/tubal/peritoneal cancer in MDACC-NROSS set Supplementary Table 2. Characteristics of patients with invasive epithelial ovarian/tubal/peritoneal cancer in AOCS set Supplementary Table 3. Characteristics of patients with invasive epithelial ovarian/tubal/peritoneal cancer by stage and primary site in the UKCTOCS study Supplementary Figure 3. Examples of longitudinal analysis of CA125 and TP53 autoantibody titers in pre-diagnostic serial serum samples from ovarian cancer patients in the UKCTOCS Study. Supplementary Figure 4. ROC curve analysis for TP53 autoantibody and CA125 biomarkers in UKCTOCS trial. Supplementary Figure 5. Comparison of TP53 autoantibody titers between cancer cases with TP53 wild-type and mutant genes in the AOCS biobanking study. Supplementary Figure 6. The list of TP53 mutant protein candidates for preliminary screening of autoantibody against specific TP53 mutant proteins. Supplementary Table 4. Summary of specific TP53 mutant autoantibody titers of individual cancer patients with corresponding TP53 protein mutations in the AOCS biobanking study Supplementary Table 5. Summary of multiplex immunoassay results for screening TP53 mutant-specific autoantibody using samples from the AOCS biobanking study.

Purpose: In the United Kingdom Collaborative Trial of Ovarian Cancer Screening (UKCTOCS), women in the multimodal (MMS) arm had a serum CA125 test (first-line), with those at increased risk, having repeat CA125/ultrasound (second-line test). CA125 was interpreted using the “Risk of Ovarian Cancer Algorithm” (ROCA). We report on performance of other serial algorithms and a single CA125 threshold as a first-line screen in the UKCTOCS dataset.Experimental Design: 50,083 post-menopausal women who attended 346,806 MMS screens were randomly split into training and validation sets, following stratification into cases (ovarian/tubal/peritoneal cancers) and controls. The two longitudinal algorithms, a new serial algorithm, method of mean trends (MMT) and the parametric empirical Bayes (PEB) were trained in the training set and tested in the blinded validation set and the performance characteristics, including that of a single CA125 threshold, were compared.Results: The area under receiver operator curve (AUC) was significantly higher (P = 0.01) for MMT (0.921) compared with CA125 single threshold (0.884). At a specificity of 89.5%, sensitivities for MMT [86.5%; 95% confidence interval (CI), 78.4–91.9] and PEB (88.5%; 95% CI, 80.6–93.4) were similar to that reported for ROCA (sensitivity 87.1%; specificity 87.6%; AUC 0.915) and significantly higher than the single CA125 threshold (73.1%; 95% CI, 63.6–80.8).Conclusions: These findings from the largest available serial CA125 dataset in the general population provide definitive evidence that longitudinal algorithms are significantly superior to simple cutoff values for ovarian cancer screening. Use of these newer algorithms requires incorporation into a multimodal strategy. The results highlight the importance of incorporating serial change in biomarker levels in cancer screening/early detection strategies. Clin Cancer Res; 24(19); 4726–33. ©2018 AACR.

MMT / PEB values in training and validation of the algorithms based on the primary analysis

Purpose: The TP53 tumor-suppressor gene is mutated in >95% of high-grade serous ovarian cancers. Detecting an autologous antibody response to TP53 that might improve early detection.Experimental Design: An immunoassay was developed to measure TP53 autoantibody in sera from 378 cases of invasive epithelial ovarian cancer and 944 age-matched healthy controls from the United States, Australia, and the United Kingdom. Serial preclinical samples from cases and controls were also assayed from the UK Collaborative Trial of Ovarian Cancer Screening (UKCTOCS).Results: Using a cutoff value of 78 U/mL to achieve a specificity of 97.4%, TP53 autoantibody was elevated in 30% of 50 cases from MD Anderson, 21.3% of 108 cases from the Australian Ovarian Cancer Study, and 21% of 220 cases from the UKCTOCS. Among 164 cases with rising CA125 detected with the UKCTOCS risk of ovarian cancer algorithm (ROCA), 20.7% had elevated TP53 autoantibody. In cases missed by the ROCA, 16% of cases had elevated TP53 autoantibody. Of the 34 ovarian cancer cases detected with the ROCA, TP53 autoantibody titers were elevated 11.0 months before CA125. In the 9 cases missed by the ROCA, TP53 autoantibody was elevated 22.9 months before cancer diagnosis. Similar sensitivity was obtained using assays with specific mutant and wild-type TP53.Conclusions: TP53 autoantibody levels provide a biomarker with clinically significant lead time over elevation of CA125 or an elevated ROCA value. Quantitative assessment of autoantibodies in combination with CA125 holds promise for earlier detection of invasive epithelial ovarian cancer. Clin Cancer Res; 23(19); 5912–22. ©2017 AACR.

The p53 protein is critical for multiple cellular functions including cell growth and DNA repair. We assessed whether polymorphisms in the region encoding TP53 were associated with risk of invasive ovarian cancer. The study population includes a total of 5,206 invasive ovarian cancer cases (2,829 of which were serous) and 8,790 controls from 13 case-control or nested case-control studies participating in the Ovarian Cancer Association Consortium (OCAC). Three of the studies performed independent discovery investigations involving genotyping of up to 23 single nucleotide polymorphisms (SNP) in the TP53 region. Significant findings from this discovery phase were followed up for replication in the other OCAC studies. Mixed effects logistic regression was used to generate posterior median per allele odds ratios (OR), 95% probability intervals (PI), and Bayes factors (BF) for genotype associations. Five SNPs showed significant associations with risk in one or more of the discovery investigations and were followed up by OCAC. Mixed effects analysis confirmed associations with serous invasive cancers for two correlated (r2 = 0.62) SNPs: rs2287498 (median per allele OR, 1.30; 95% PI, 1.07–1.57) and rs12951053 (median per allele OR, 1.19; 95% PI, 1.01–1.38). Analyses of other histologic subtypes suggested similar associations with endometrioid but not with mucinous or clear cell cancers. This large study provides statistical evidence for a small increase in risk of ovarian cancer associated with common variants in the TP53 region. [Cancer Res 2009;69(6):2349–57]

Supplementary Table 1 from Single Nucleotide Polymorphisms in the TP53 Region and Susceptibility to Invasive Epithelial Ovarian Cancer

Supplementary Table 4 from Single Nucleotide Polymorphisms in the TP53 Region and Susceptibility to Invasive Epithelial Ovarian Cancer

High-risk susceptibility genes explain CCND1, CCND2, CCND3, CCNE1, CDK2, CDK4, CDK6, CDKN1A, CDKN1B, CDKN2A, CDKN2B, CDKN2C, and CDKN2D—and risk of invasive epithelial ovarian cancer. We used a two-stage, multicenter, case-control study. In stage 1, 88 SNPs that tag common variation in these genes were genotyped in three studies from the United Kingdom, United States, and Denmark (∼1,500 cases and 2,500 controls). Genotype frequencies in cases and controls were compared using logistic regression. In stage 2, eight other studies from Australia, Poland, and the United States (∼2,000 cases and ∼3,200 controls) were genotyped for the five most significant SNPs from stage 1. No SNP was significant in the stage 2 data alone. Using the combined stages 1 and 2 data set, CDKN2A rs3731257 and CDKN1B rs2066827 were associated with disease risk (unadjusted P trend = 0.008 and 0.036, respectively), but these were not significant after adjusting for multiple testing. Carrying the minor allele of these SNPs was found to be associated with reduced risk [OR, 0.91 (0.85–0.98) for rs3731257; and OR, 0.93 (0.87–0.995) for rs2066827]. In conclusion, we have found evidence that a single tagged SNP in both the CDKN2A and CDKN1B genes may be associated with reduced ovarian cancer risk. This study highlights the need for multicenter collaborations for genetic association studies. [Cancer Res 2007;67(7):3027–35]

Supplementary Figure 1 from Single Nucleotide Polymorphisms in the TP53 Region and Susceptibility to Invasive Epithelial Ovarian Cancer

Supplementary Tables 1-4 from Tagging Single Nucleotide Polymorphisms in Cell Cycle Control Genes and Susceptibility to Invasive Epithelial Ovarian Cancer

Supplementary Table 2 from Single Nucleotide Polymorphisms in the TP53 Region and Susceptibility to Invasive Epithelial Ovarian Cancer

Supplementary Table 3 from Single Nucleotide Polymorphisms in the TP53 Region and Susceptibility to Invasive Epithelial Ovarian Cancer

Supplementary Figure 2 from Single Nucleotide Polymorphisms in the TP53 Region and Susceptibility to Invasive Epithelial Ovarian Cancer

Charge modulation microscopy (CMM) is an electro-optical method that is capable of mapping the spatial distribution of induced charges in an organic field-effect transistor (OFET). Here, we report a new (and simple) implementation of CMM in transmission geometry with camera-based imaging. A significant improvement in data acquisition speed (by at least an order of magnitude) has been achieved while preserving the spatial and spectral resolution. To demonstrate the capability of the system, we measured the spatial distribution of the induced charges in an OFET with a polymer blend of indacenodithiophene-co-benzothiadiazole and poly-vinylcarbazole that shows micrometer-scale phase separation. We were able to resolve spatial variations in the accumulated charge density on a length scale of 500 nm. We demonstrated through a careful spectral analysis that the measured signal is a genuine charge accumulation signal that is not dominated by optical artifacts.

Ashkenazi-Jewish (AJ) population-based BRCA testing is acceptable, cost-effective and amplifies primary prevention for breastovarian cancer. However, data describing lifestyle impact are lacking. We report long-term results of population-based BRCA testing on lifestyle behaviour and cancer risk perception.Two-arm randomised controlled trials (ISRCTN73338115, GCaPPS): (a) population-screening (PS); (b) family history (FH)/clinical criteria testing.North London AJ-population.AJ women/men18 years.prior BRCA testing or first-degree relatives of BRCA-carriers.Participants were recruited through self-referral. All participants received informed pre-test genetic counselling. The intervention included genetic testing for three AJ BRCA-mutations: 185delAG(c.68_69delAG), 5382insC(c.5266dupC) and 6174delT(c.5946delT). This was undertaken for all participants in the PS arm and participants fulfilling FH/clinical criteria in the FH arm. Patients filled out customised/validated questionnaires at baseline/1-year/2-year/3-year follow-ups. Generalised linear-mixed models adjusted for covariates and appropriate contrast tests were used for between-group/within-group analysis of lifestyle and behavioural outcomes along with evaluating factors associated with these outcomes. Outcomes are adjusted for multiple testing (Bonferroni method), with P 0.0039 considered significant.Lifestyle/behavioural outcomes at baseline/1-year/2-year/3-year follow-ups.1034 participants were randomised to PS (n = 530) or FH (n = 504) arms. No significant difference was identified between PS- and FH-based BRCA testing approaches in terms of dietary fruit/vegetable/meat consumption, vitamin intake, alcohol quantity/ frequency, smoking behaviour (frequency/cessation), physical activity/exercise or routine breast mammogram screening behaviour, with outcomes not affected by BRCA test result. Cancer risk perception decreased with time following BRCA testing, with no difference between FH/PS approaches, and the perception of risk was lowest in BRCA-negative participants. Men consumed fewer fruits/vegetables/vitamins and more meat/alcohol than women (P 0.001).Population-based and FH-based AJ BRCA testing have similar long-term lifestyle impacts on smoking, alcohol, dietary fruit/vegetable/meat/vitamin, exercise, breast screening participation and reduced cancer risk perception.

Objective Estrogen is a well‐established risk factor for various cancers. It causes endometrial proliferation, which is assessed routinely as endometrial thickness (ET) using transvaginal ultrasound (TVS). Only one previous study, restricted to endometrial and breast cancer, has considered ET and the risk of non‐endometrial cancer. The aim of this study was to explore the association between baseline and serial ET measurements and nine non‐endometrial hormone‐sensitive cancers, in postmenopausal women, using contemporary statistical methodology that attempts to minimize the biases typical of endogenous serial data. Methods This was a cohort study nested within the UK Collaborative Trial of Ovarian Cancer Screening (UKCTOCS). In the ultrasound arm of UKCTOCS, 50639 postmenopausal women, aged 50–74, underwent annual TVS examination, of whom 38 105 had a valid ET measurement, no prior hysterectomy and complete covariate data, and were included in this study. All women were followed up through linkage to national cancer registries. The effect of ET on the risk of six estrogen‐dependent cancers (breast, ovarian, colorectal, bladder, lung and pancreatic) was assessed using joint models for longitudinal biomarker and time‐to‐event data, and Cox models were used to assess the association between baseline ET measurement and these six cancers in addition to liver cancer, gastric cancer and non‐Hodgkin's lymphoma (NHL). All models were adjusted for current hormone‐replacement therapy (HRT) use, body mass index, age at last menstrual period, parity and oral contraceptive pill use. Results The 38 105 included women had a combined total of 267 567 (median, 8; interquartile range, 5–9) valid ET measurements. During a combined total of 407 838 (median, 10.9) years of follow‐up, 1398 breast, 351 endometrial, 381 lung, 495 colorectal, 222 ovarian, 94 pancreatic, 79 bladder, 62 gastric, 38 liver cancers and 52 NHLs were registered. Using joint models, a doubling of ET increased significantly the risk of breast (hazard ratio (HR), 1.21; 95% CI, 1.09–1.36; P = 0.001), ovarian (HR, 1.39; 95% CI, 1.06–1.82; P = 0.018) and lung (HR, 1.25; 95% CI, 1.02–1.54; P = 0.036) cancers. There were no statistically significant associations between ET and the remaining six cancers. Conclusion Postmenopausal women with high/increasing ET on TVS are at increased risk of breast, ovarian and lung cancer. It is important that clinicians are aware of these risks, as TVS is a common investigation. © 2019 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of the International Society of Ultrasound in Obstetrics and Gynecology.

Objective There are widespread efforts to increase symptom awareness of ‘pelvic/abdominal pain, increased abdominal size/bloating, difficulty eating/feeling full and urinary frequency/urgency’ in an attempt to diagnose ovarian cancer earlier. Long-term survival of women with these symptoms adjusted for known prognostic factors is yet to be determined. This study explored the association of symptoms, routes and interval to diagnosis and long-term survival in a population-based cohort of postmenopausal women diagnosed with invasive epithelial tubo-ovarian cancer (iEOC) in the ‘no screen’ (control) UKCTOCS arm. Methods Of 101,299 women in the control arm, 574 were confirmed on outcome review to have iEOC between randomisation (2001–2005) and 31 December 2014. Data was extracted from medical notes and electronic records. A multivariable model was fitted for individual symptoms, time interval from symptom onset to diagnosis, route to diagnosis, speciality, morphological Type, age at diagnosis, year of diagnosis (period effect), stage, primary treatment, and residual disease. Results Women presenting with symptoms listed in the NICE guidelines (HR1.48, 95%CI1.16–1.89, p = 0.001) or the modified Goff Index (HR1·68, 95%CI1·32–2.13, p, Highlights • This study explored the association of symptoms of ovarian cancer, interval and route to diagnosis with survival. • Focus on ‘high alert’ symptoms: pelvic/abdominal pain, increase abdominal size/bloating and difficulty eating/feeling full • The ovarian cancer ‘high alert’ symptom complexes identify postmenopausal women with a significantly poorer prognosis. • The study could not however exclude the possibility of better outcomes in those who are aware and acted on these symptoms.

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.

Funder: White Rock Foundation, Funder: Jardine Foundation, Funder: Cambridge Commonwealth European and International Trust, Coordination nanosheets are an emerging class of 2D, bottom-up materials having fully π-conjugated, planar, graphite-like structures with high electrical conductivities. Since their discovery, great effort has been devoted to expand the variety of coordination nanosheets; however, in most cases, their low crystallinity in thick films hampers practical device applications. In this study, mixtures of nickel and copper ions are employed to fabricate benzenehexathiolato (BHT)-based coordination nanosheet films, and serendipitously, it is found that this heterometallicity preferentially forms a structural phase with improved film crystallinity. Spectroscopic and scattering measurements provide evidence for a bilayer structure with in-plane periodic arrangement of copper and nickel ions with the NiCu2 BHT formula. Compared with homometallic films, heterometallic films exhibit more crystalline microstructures with larger and more oriented grains, achieving higher electrical conductivities reaching metallic behaviors. Low dependency of Seebeck coefficient on the mixing ratio of nickel and copper ions supports that the large variation in the conductivity data is not caused by change in the intrinsic properties of the films. The findings open new pathways to improve crystallinity and to tune functional properties of 2D coordination nanosheets.

Earlier detection of pancreatic ductal adenocarcinoma (PDAC) is key to improving patient outcomes, as it is mostly detected at advanced stages which are associated with poor survival. Developing non-invasive blood tests for early detection would be an important breakthrough. The primary objective of the work presented here was to use a unique dataset, that is both large and prospectively collected, to quantify a set of 96 cancer-associated proteins and construct multi-marker models with the capacity to accurately predict PDAC years before diagnosis. The data is part of a nested case control study within UK Collaborative Trial of Ovarian Cancer Screening and is comprised of 219 samples, collected from a total of 143 post-menopausal women who were diagnosed with pancreatic cancer within 70 months after sample collection, and 248 matched non-cancer controls. We developed a stacked ensemble modelling technique to achieve robustness in predictions and, therefore, improve performance in newly collected datasets. With a pool of 10 base-learners and a Bayesian averaging meta-learner, we can predict PDAC status with an AUC of 0.91 (95% CI 0.75 - 1.0), sensitivity of 92% (95% CI 0.54 - 1.0) at 90% specificity, up to 1 year to diagnosis, and at an AUC of 0.85 (95% CI 0.74 - 0.93) up to 2 years to diagnosis (sensitivity of 61%, 95 % CI 0.17 - 0.83, at 90% specificity). These models also use clinical covariates such as hormone replacement therapy use (at randomization), oral contraceptive pill use (ever) and diabetes and outperform biomarker combinations cited in the literature.

Funder: Department of Health; FundRef: http://dx.doi.org/10.13039/501100000276, Funder: Ontario Research Fund, Funder: CHU de Quebec Foundation, Funder: Fondation du cancer du sein du Qu��bec; FundRef: http://dx.doi.org/10.13039/100016328, Funder: The Eve Appeal, Background: Epithelial tubo-ovarian cancer (EOC) has high mortality partly due to late diagnosis. Prevention is available but may be associated with adverse effects. A multifactorial risk model based on known genetic and epidemiological risk factors (RFs) for EOC can help identify women at higher risk who could benefit from targeted screening and prevention. Methods: We developed a multifactorial EOC risk model for women of European ancestry incorporating the effects of pathogenic variants (PVs) in BRCA1, BRCA2, RAD51C, RAD51D and BRIP1, a Polygenic Risk Score (PRS) of arbitrary size, the effects of RFs and explicit family history (FH) using a synthetic model approach. The PRS, PV and RFs were assumed to act multiplicatively. Results: Based on a currently available PRS for EOC that explains 5% of the EOC polygenic variance, the estimated lifetime risks under the multifactorial model in the general population vary from 0.5% to 4.6% for the first to 99th percentiles of the EOC risk distribution. The corresponding range for women with an affected first-degree relative is 1.9%���10.3%. Based on the combined risk distribution, 33% of RAD51D PV carriers are expected to have a lifetime EOC risk of less than 10%. RFs provided the widest distribution, followed by the PRS. In an independent partial model validation, absolute and relative 5-year risks were well calibrated in quintiles of predicted risk. Conclusion: This multifactorial risk model can facilitate stratification, in particular among women with FH of cancer and/or moderate-risk and high-risk PVs. The model is available via the CanRisk Tool (www.canrisk.org).

Introduction/Background* Population-based BRCA-testing in the Ashkenazi Jewish (AJ) population is feasible, acceptable, reduces anxiety, identifies more BRCA-carriers and is cost-effective. The Jewish population is the first population for whom unselected population testing is now being implemented with Israel recently adopted this into national policy. Guideline change is being advocated in the UK and by others too. It is unknown whether BRCA-testing differs across Jewish denominational affiliations and religious or cultural outlook. We evaluate the association of Jewish cultural and religious identity and denominational affiliation with interest-in, intention-to undertake and uptake-of population-based BRCA-testing Methodology Design Cohort-study set within recruitment to GCaPPS-trial (ISRCTN73338115). AJ men and women, >18years, from London, self-referred, and attended recruitment clinics(clusters) for pre-test counselling. Subsequently consenting individuals underwent BRCA-testing. Mina oucome measures were: Interest, intention, uptake-of BRCA-testing. Participants self-identified to one Jewish denomination: Conservative/Liberal/Reform/Traditional/Orthodox/Unaffiliated. Validated scales measured Jewish Cultural-Identity (JI) and Jewish Religious-identity (JR). 4-item Likert-scales analysed initial ‘interest’ and ‘intention-to-test’ pre-counselling. Item-Response-Theory and graded-response-models, modelled responses to JI and JR scales. Ordered/multinomial logistic regression modelling evaluated association of JI-scale, JR-scale and Jewish Denominational affiliation on interest, intention and uptake-of BRCA-testing. Result(s)* 935 AJ women/men of mean-age=53.8 (S.D=15.02) years, received pre-test education and counselling through 256 recruitment clinic clusters (mean cluster size=3.64). Denominational affiliations included Conservative/Masorti=91(10.2%); Liberal=82(9.2%), Reform=135(15.1%), Traditional=212(23.7%), Orthodox=239(26.7%); and Unaffiliated/Non-practising=135(15.1%). Overall BRCA-testing uptake was 88%. Pre-counselling 96% expressed interest and 60% intention-to test. JI and JR scores were highest for Orthodox, followed by Conservative/Masorti, Traditional, Reform, Liberal and Unaffiliated Jewish denominations. Regression modelling showed no significant association between overall Jewish Cultural or Religious Identity with either interest, intention or uptake-of BRCA-testing. Interest, intention and uptake of BRCA-testing was not significantly associated with denominational affiliation. Conclusion* Jewish religious/cultural identity and denominational affiliation do not appear to influence interest, intention or uptake of population-based BRCA-testing. BRCA-testing was robust across all Jewish denominations.

OBJECTIVE To evaluate the association of Jewish cultural and religious identity and denominational affiliation with interest in, intention to undertake and uptake of population-based BRCA (Breast Cancer Gene)-testing. DESIGN Cohort-study set within recruitment to GCaPPS-trial (ISRCTN73338115). SETTING London Ashkenazi-Jewish (AJ) population. POPULATION OR SAMPLE AJ men and women, >18 years. METHODS Participants were self-referred, and attended recruitment clinics (clusters) for pre-test counselling. Subsequently consenting individuals underwent BRCA testing. Participants self-identified to one Jewish denomination: Conservative/Liberal/Reform/Traditional/Orthodox/Unaffiliated. Validated scales measured Jewish Cultural-Identity (JI) and Jewish Religious-identity (JR). Four-item Likert-scales analysed initial 'interest' and 'intention to test' pre-counselling. Item-Response-Theory and graded-response models, modelled responses to JI and JR scales. Ordered/multinomial logistic regression modelling evaluated association of JI-scale, JR-scale and Jewish Denominational affiliation on interest, intention and uptake of BRCA testing. MAIN OUTCOME MEASURES Interest, intention, uptake of BRCA testing. RESULTS In all, 935 AJ women/men of mean age = 53.8 (S.D = 15.02) years, received pre-test education and counselling through 256 recruitment clinic clusters (median cluster size = 3). Denominational affiliations included Conservative/Masorti = 91 (10.2%); Liberal = 82 (9.2%), Reform = 135 (15.1%), Traditional = 212 (23.7%), Orthodox = 239 (26.7%); and Unaffiliated/Non-practising = 135 (15.1%). Overall BRCA testing uptake was 88%. Pre-counselling, 96% expressed interest and 60% intention to test. JI and JR scores were highest for Orthodox, followed by Conservative/Masorti, Traditional, Reform, Liberal and Unaffiliated Jewish denominations. Regression modelling showed no significant association between overall Jewish Cultural or Religious Identity with either interest, intention or uptake of BRCA testing. Interest, intention and uptake of BRCA testing was not significantly associated with denominational affiliation. CONCLUSIONS Jewish religious/cultural identity and denominational affiliation do not appear to influence interest, intention or uptake of population-based BRCA testing. BRCA testing was robust across all Jewish denominations. TWEETABLE ABSTRACT Jewish cultural/religious factors do not affect BRCA testing, with robust uptake seen across all denominational affiliations.

Ovarian cancer is most commonly diagnosed at an advanced stage (3 or 4) and remains the deadliest gynecologic malignancy. When diagnosed at stage 1, a survival rate of greater than 90% has been demonstrated, compared with a 5-year survival rate of 27% and 13% for stage 3 and stage 4 disease, respectively. Despite international efforts to identify robust screening methods and increase early-stage detection, to date no evidence that screening saves lives has been presented. The UK Collaborative Trial of Ovarian Cancer Screening (UKCTOCS) is a randomized controlled trial that demonstrated no evidence associated with screening for ovarian cancer and reduction in ovarian cancer-related deaths at primary analysis but requires further follow-up. This secondary analysis of the UKCTOCS randomized controlled trial aimed to provide a follow-up and report on the long-term mortality effects of ovarian cancer screening. The UKCTOCS is a multicenter randomized trial of 202,638 women aged 50 to 74 years assigned to 2 annual screening groups (multimodal screening [MMS] vs ultrasound screening [USS]). Women in the United Kingdom were recruited from 13 National Health Service (NHS) centers and randomized to MMS, USS, or no screening in a 1:1:2 ratio. Annual screening in the MMS group involved serum CA125 measurements used in conjunction with the risk of ovarian cancer (ROCA) calculation to guide follow-up involving either no additional screening, repeat CA125 ROCA in 3 months, or transvaginal USS as a second test. Annual screening in the USS group involved transvaginal ultrasound with follow-up involving either continuation of annual screening, repeat in 3 months, or requiring a scan with a senior ultrasonographer within 6 weeks. The primary study outcome was death due to ovarian cancer or tubal cancer. A total of 202,638 women were randomized between April 2001 and September 2005, with screening concluding in December 2011 and follow-up continuing until June 2020. The final analysis cohort consisted of 202,562 women, 50,625 in the MMS group, 50,623 in the USS group, and 101,314 in the no screening group. Compliance with screening was 81% in the MMS group versus 78% in the USS group, with a median of 8 annual screens per participant. The median follow-up was 16.3 years (interquartile range, 15.1–17.3). A total of 2055 participants were diagnosed with ovarian or tubal cancer. At 9.5 years after screening, there was a 47.2% (95% confidence interval, 19.7–81.1) greater incidence of stage 1 disease and a 24.5% (-41.8 to -2.0) lower incidence of stage IV disease in the MMS group compared with the no screening group. Overall, a 39.2% (95% confidence interval, 16.1–66.9) greater incidence of stage I or II disease and a 10.2% (-21.3 to 2.4) lower incidence of stage III or IV disease was observed in the MMS group compared with the no screening group. At follow-up conclusion, 1206 women had died of ovarian cancer (296/50,625 [0.6%] in the MMS group, 291/50,623 [0.6%] in the USS group, 619/101,314 [0.6%] in the no screening group) with no significant difference between the MMS (P = 0.58) and USS (P = 0.36) groups compared with the no screening group. The results of this large-scale ovarian cancer screening trial demonstrate that, on long-term follow-up, while the screening strategies defined here resulted in a greater likelihood of diagnosing early stage disease, neither MMS nor USS resulted in a significant reduction in deaths from ovarian or tubal cancer.

Artificial Intelligence methods can be very effective in classification tasks that involve the processing of ordered sequences of data. Here we explore two different approaches to tackle the problem of ovarian cancer detection from a sequence of longitudinal measurements of several biomarkers. The first approach relies on a Bayesian hierarchical model whose fundamental assumption is that measurements taken from case subjects exhibit a changepoint in one or several biomarkers. The second approach is a purely discriminative machine learning algorithm based on the use of recurrent neural networks, a kind of artificial neural network specially suited to the processing of inputs of different lengths.