Purpose Breast cancer (BC) risk prediction allows systematic identification of individuals at highest and lowest risk. We extend the Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA) risk model to incorporate the effects of polygenic risk scores (PRS) and other risk factors (RFs). Methods BOADICEA incorporates the effects of truncating variants in BRCA1 , BRCA2 , PALB2 , CHEK2 , and ATM ; a PRS based on 313 single-nucleotide polymorphisms (SNPs) explaining 20% of BC polygenic variance; a residual polygenic component accounting for other genetic/familial effects; known lifestyle/hormonal/reproductive RFs; and mammographic density, while allowing for missing information. Results Among all factors considered, the predicted UK BC risk distribution is widest for the PRS, followed by mammographic density. The highest BC risk stratification is achieved when all genetic and lifestyle/hormonal/reproductive/anthropomorphic factors are considered jointly. With all factors, the predicted lifetime risks for women in the UK population vary from 2.8% for the 1st percentile to 30.6% for the 99th percentile, with 14.7% of women predicted to have a lifetime risk of ≥17–<30% (moderate risk according to National Institute for Health and Care Excellence [NICE] guidelines) and 1.1% a lifetime risk of ≥30% (high risk). Conclusion This comprehensive model should enable high levels of BC risk stratification in the general population and women with family history, and facilitate individualized, informed decision-making on prevention therapies and screening.

Background: The CanRisk Tool (https://canrisk.org) is the next-generation web interface for the latest version of the BOADICEA (Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm) state-of-the-art risk model and a forthcoming ovarian cancer risk model. Methods: The tool captures information on family history, rare pathogenic variants in cancer susceptibility genes, polygenic risk scores, lifestyle/hormonal/clinical features, and imaging risk factors to predict breast and ovarian cancer risks and estimate the probabilities of carrying pathogenic variants in certain genes. It was implemented using modern web frameworks, technologies, and web services to make it extensible and increase accessibility to researchers and third-party applications. The design of the graphical user interface was informed by feedback from health care professionals and a formal evaluation. Results: This freely accessible tool was designed to be user friendly for clinicians and to boost acceptability in clinical settings. The tool incorporates a novel graphical pedigree builder to facilitate collection of the family history data required by risk calculations. Conclusions: The CanRisk Tool provides health care professionals and researchers with a user-friendly interface to carry out multifactorial breast and ovarian cancer risk predictions. It is the first freely accessible cancer risk prediction program to carry the CE marking. Impact: There have been over 3,100 account registrations, and 98,000 breast and ovarian cancer risk calculations have been run within the first 9 months of the CanRisk Tool launch.

Background There is a growing focus on the development of multi-factorial cancer risk prediction algorithms alongside tools that operationalise them for clinical use. BOADICEA is a breast and ovarian cancer risk prediction model incorporating genetic and other risk factors. A new user-friendly Web-based tool (CanRisk.org) has been developed to apply BOADICEA. This study aimed to explore the acceptability of the prototype CanRisk tool among two healthcare professional groups to inform further development, evaluation and implementation. Method A multi-methods approach was used. Clinicians from primary care and specialist genetics clinics in England, France and Germany were invited to use the CanRisk prototype with two test cases (either face-to-face with a simulated patient or via a written vignette). Their views about the tool were examined via a semi-structured interview or equivalent open-ended questionnaire. Qualitative data were subjected to thematic analysis and organised around Sekhon's Theoretical Framework of Acceptability. Results Seventy-five clinicians participated, 21 from primary care and 54 from specialist genetics clinics. Participants were from England (n = 37), France (n = 23) and Germany (n = 15). The prototype CanRisk tool was generally acceptable to most participants due to its intuitive design. Primary care clinicians were concerned about the amount of time needed to complete, interpret and communicate risk information. Clinicians from both settings were

ObjectiveThe aims of this study were to determine the prevalence of risk factors associated with hepatocellular carcinoma (HCC) in black adult South Africans and to estimate the size of the associated risks.MethodsA case-control analysis of 150 black South African patients (aged 18–75 years) with HCC—who were a subset of patients recruited for the Johannesburg Cancer Case Control Study 2000 to 2012—was undertaken. The association between this tumour and hepatitis B/C virus infections, and human immunodeficiency virus (HIV) mono- and co-infections was investigated. Odds ratios (ORs) and 95% confidence intervals (CI) adjusted for age, year of diagnosis, marital status, place of birth and selected modifiable risk factors were calculated.ResultsHCC was significantly associated with a rural birthplace (p<0.05), being male and living in an urban area for 14 years or less. The Odds Ratio (OR) for HCC increased significantly with HBV DNA+/HBsAg+ (OR 34.5; CI:16.26–73.13), HBV DNA+/HBsAg- (OR 3.76; CI:1.79–7.92), HBV DNA level >2000 IU/ml (OR 8.55; CI:3.00–24.54) to ≥200,000 (OR 16.93; CI:8.65–33.13), anti-HCV (OR 8.98; CI:3.59–22.46), HBV DNA+/HIV+ co-infection (OR 5.36; CI:2.59–11.11), but not with HBV DNA-/HIV+ (OR 0.34; CI:0.14–0.85). We did not find a synergistic interaction between HBV and HIV. Modifiable risk factors (alcohol consumption, tobacco smoking, number of sexual partners, diabetes and hormonal contraceptive use) were nonsignificant.DiscussionA considerable portion of the HCC burden in Johannesburg and surrounding provinces falls on rural migrants to urban areas, most of whom are men. The HBV will continue to contribute to HCC incidence in older age-groups and in others who missed vaccination. Although we did not find an increased risk for HCC in HIV positive individuals this may change as life expectancy increases due to greater access to antiretroviral therapies, necessitating the addition of hepatitis virus screening to preventive medical care.