Clinical software development for the Web: lessons learned from the BOADICEA project.

BACKGROUND: In the past 20 years, society has witnessed the following landmark scientific advances: (i) the sequencing of the human genome, (ii) the distribution of software by the open source movement, and (iii) the invention of the World Wide Web. Together, these advances have provided a new impetus for clinical software development: developers now translate the products of human genomic research into clinical software tools; they use open-source programs to build them; and they use the Web to deliver them. Whilst this open-source component-based approach has undoubtedly made clinical software development easier, clinical software projects are still hampered by problems that traditionally accompany the software process. This study describes the development of the BOADICEA Web Application, a computer program used by clinical geneticists to assess risks to patients with a family history of breast and ovarian cancer. The key challenge of the BOADICEA Web Application project was to deliver a program that was safe, secure and easy for healthcare professionals to use. We focus on the software process, problems faced, and lessons learned. Our key objectives are: (i) to highlight key clinical software development issues; (ii) to demonstrate how software engineering tools and techniques can facilitate clinical software development for the benefit of individuals who lack software engineering expertise; and (iii) to provide a clinical software development case report that can be used as a basis for discussion at the start of future projects. RESULTS: We developed the BOADICEA Web Application using an evolutionary software process. Our approach to Web implementation was conservative and we used conventional software engineering tools and techniques. The principal software development activities were: requirements, design, implementation, testing, documentation and maintenance. The BOADICEA Web Application has now been widely adopted by clinical geneticists and researchers. BOADICEA Web Application version 1 was released for general use in November 2007. By May 2010, we had > 1200 registered users based in the UK, USA, Canada, South America, Europe, Africa, Middle East, SE Asia, Australia and New Zealand. CONCLUSIONS: We found that an evolutionary software process was effective when we developed the BOADICEA Web Application. The key clinical software development issues identified during the BOADICEA Web Application project were: software reliability, Web security, clinical data protection and user feedback.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

Risk threshold for surgical prevention of ovarian cancer

BACKGROUND: Risk-reducing salpingo-oophorectomy (RRSO) is the most effective intervention to prevent ovarian cancer (OC). It is only available to high-risk women with >10% lifetime OC risk. This threshold has not been formally tested for cost-effectiveness. OBJECTIVE: To specify the OC risk thresholds for RRSO being cost-effective for preventing OC in premenopausal women. METHODS: The costs as well as effects of surgical prevention ('RRSO') were compared over a lifetime with 'no RRSO' using a decision analysis model. RRSO was undertaken in premenopausal women >40 years. The model was evaluated at lifetime OC risk levels: 2%, 4%, 5%, 6%, 8% and 10%. Costs and outcomes are discounted at 3.5%. Uncertainty in the model was assessed using both deterministic sensitivity analysis and probabilistic sensitivity analysis (PSA). Outcomes included in the analyses were OC, breast cancer (BC) and additional deaths from coronary heart disease. Total costs and effects were estimated in terms of quality-adjusted life-years (QALYs); incidence of OC and BC; as well as incremental cost-effectiveness ratio (ICER). DATA SOURCES: Published literature, Nurses Health Study, British National Formulary, Cancer Research UK, National Institute for Health and Care Excellence guidelines and National Health Service reference costs. The time horizon is lifetime and perspective: payer. RESULTS: Premenopausal RRSO is cost-effective at 4% OC risk (life expectancy gained=42.7 days, ICER=£19 536/QALY) with benefits largely driven by reduction in BC risk. RRSO remains cost-effective at >8.2% OC risk without hormone replacement therapy (ICER=£29 071/QALY, life expectancy gained=21.8 days) or 6%if BC risk reduction=0 (ICER=£27 212/QALY, life expectancy gained=35.3 days). Sensitivity analysis indicated results are not impacted much by costs of surgical prevention or treatment of OC/ BC or cardiovascular disease. However, results were sensitive to RRSO utility scores. Additionally, 37%, 61%, 74%, 84%, 96% and 99.5% simulations on PSA are cost-effective for RRSO at the 2%, 4%, 5%, 6%, 8% and 10% levels of OC risk, respectively. CONCLUSIONS: Premenopausal RRSO appears to be extremely cost-effective at ≥4% lifetime OC risk, with ≥42.7 days gain in life expectancy if compliance with hormone replacement therapy is high. Current guidelines should be re-evaluated to reduce the RRSO OC risk threshold to benefit a number of at-risk women who presently cannot access risk-reducing surgery.The study is supported by researchers at the National Institute for Health Research University College London Hospitals Biomedical Research CentreThis is the author accepted manuscript. It is currently under an indefinite embargo pending publication by BMJ Group

BRCA1 and BRCA2 mutation predictions using the BOADICEA and BRCAPRO models and penetrance estimation in high-risk French-Canadian families.

INTRODUCTION: Several genetic risk models for breast and ovarian cancer have been developed, but their applicability to specific populations has not been evaluated. We used data from French-Canadian families to evaluate the mutation predictions given by the BRCAPRO and BOADICEA models. We also used this data set to estimate the age-specific risks for breast and ovarian cancer in BRCA1 and BRCA2 mutation carriers. METHODS: A total of 195 families with multiple affected individuals with breast or ovarian cancer were recruited through the INHERIT (INterdisciplinary HEalth Research International Team on BReast CAncer susceptibility) BRCAs research program. Observed BRCA1 and BRCA2 mutation status was compared with predicted carrier probabilities under the BOADICEA and BRCAPRO models. The models were assessed using Brier scores, attributes diagrams and receiver operating characteristic curves. Log relative risks for breast and ovarian cancer in mutation carriers versus population risks were estimated by maximum likelihood, using a modified segregation analysis implemented in the computer program MENDEL. Twenty-five families were eligible for inclusion in the BRCA1 penetrance analysis and 27 families were eligible for the BRCA2 penetrance analysis. RESULTS: The BOADICEA model predicted accurately the number of BRCA1 and BRCA2 mutations for the various groups of families, and was found to discriminate well at the individual level between carriers and noncarriers. BRCAPRO over-predicted the number of mutations in almost all groups of families, in particular the number of BRCA1 mutations. It significantly overestimated the carrier frequency for high predicted probabilities. However, it discriminated well between carriers and noncarriers. Receiver operating characteristic (ROC) curves indicate similar sensitivity and specificity for BRCAPRO and BOADICEA. The estimated risks for breast and ovarian cancer in BRCA1 and BRCA2 mutation carriers were consistent with previously published estimates. CONCLUSION: The BOADICEA model predicts accurately the carrier probabilities in French-Canadian families and may be used for counselling in this population. None of the penetrance estimates was significantly different from previous estimates, suggesting that previous estimates may be appropriate for counselling in this population.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

Cost effectiveness of population based BRCA1 founder mutation testing in Sephardi Jewish women.

BACKGROUND: Population-based BRCA1/BRCA2 founder-mutation testing has been demonstrated as cost effective compared with family history based testing in Ashkenazi Jewish women. However, only 1 of the 3 Ashkenazi Jewish BRCA1/BRCA2 founder mutations (185delAG[c.68_69delAG]), 5382insC[c.5266dupC]), and 6174delT[c.5946delT]) is found in the Sephardi Jewish population (185delAG[c.68_69delAG]), and the overall prevalence of BRCA mutations in the Sephardi Jewish population is accordingly lower (0.7% compared with 2.5% in the Ashkenazi Jewish population). Cost-effectiveness analyses of BRCA testing have not previously been performed at these lower BRCA prevalence levels seen in the Sephardi Jewish population. Here we present a cost-effectiveness analysis for UK and US populations comparing population testing with clinical criteria/family history-based testing in Sephardi Jewish women. STUDY DESIGN: A Markov model was built comparing the lifetime costs and effects of population-based BRCA1 testing, with testing using family history-based clinical criteria in Sephardi Jewish women aged ≥30 years. BRCA1 carriers identified were offered magnetic resonance imaging/mammograms and risk-reducing surgery. Costs are reported at 2015 prices. Outcomes include breast cancer, ovarian cancer, and excess deaths from heart disease. All costs and outcomes are discounted at 3.5%. The time horizon is lifetime, and perspective is payer. The incremental cost-effectiveness ratio per quality-adjusted life-year was calculated. Parameter uncertainty was evaluated through 1-way and probabilistic sensitivity analysis. RESULTS: Population testing resulted in gain in life expectancy of 12 months (quality-adjusted life-year = 1.00). The baseline discounted incremental cost-effectiveness ratio for UK population-based testing was £67.04/quality-adjusted life-year and for US population was $308.42/quality-adjusted life-year. Results were robust in the 1-way sensitivity analysis. The probabilistic sensitivity analysis showed 100$100,000/quality-adjusted life-year US willingness-to-pay thresholds. Scenario analysis showed that population testing remains cost effective in UK and US populations, even if premenopausal oophorectomy does not reduce breast cancer risk or if hormone replacement therapy compliance is nil. CONCLUSION: Population-based BRCA1 testing is highly cost effective compared with clinical criteria-driven approach in Sephardi Jewish women. This supports changing the paradigm to population-based BRCA testing in the Jewish population, regardless of Ashkenazi/Sephardi ancestry

HOXB13 G84E Mutation and Prostate Cancer Risk: Kin-Cohort Analysis Using Data From the UK Genetic Prostate Cancer Study

G84E missense mutations in HOXB13 are associated with prostate cancer. However, a wide range of risk estimates has been reported. Based on case-control studies, reported OR range from 2 to 20, often with wide confidence intervals because mutations are rare in the population. To obtain more precise risk estimates, we used a kin-cohort study design and modified segregation analysis, using family data on 11,988 PCa index-cases (4509 consecutive cases, 870 and 6609 cases recruited based on family history and young age at diagnosis, respectively) enrolled in the UK Genetic Prostate Cancer Study, who had been genotyped for G84E. Among index-cases, 182 carried at least one copy of G84E. PCa incidence was assumed to follow a mixed Cox regression model of the form λ(t)=λ_0 (t)"×exp" (G+P), where G is a fixed effect which depends on G84E, P∈N(0,σ_P^2 ) a residual polygenic random effect, and λ_0 (t) is the baseline incidence for non-carriers to age t. Using maximum likelihood, after adjusting for ascertainment, we estimated the frequency and RR (i.e. penetrance) for G84E under different genetic models, and σ_P. Preliminary results suggest that under the best fitting model, the data are consistent with a multiplicative model where each copy of G84E confers RR for PCa of 2.6 (95%CI 1.7-4.2), and a significant σ_P of 1.8 (95%CI 1.7-1.9), indicating that family history increases risk above that resulting from being a mutation carrier. Ongoing work will evaluate effect-modification of RR and/or σ_P by age, birth cohort, and mutation status, and estimate absolute risks for reference family structures

Incorporating truncating variants in PALB2, CHEK2, and ATM into the BOADICEA breast cancer risk model.

PURPOSE: The proliferation of gene panel testing precipitates the need for a breast cancer (BC) risk model that incorporates the effects of mutations in several genes and family history (FH). We extended the BOADICEA model to incorporate the effects of truncating variants in PALB2, CHEK2, and ATM. METHODS: The BC incidence was modeled via the explicit effects of truncating variants in BRCA1/2, PALB2, CHEK2, and ATM and other unobserved genetic effects using segregation analysis methods. RESULTS: The predicted average BC risk by age 80 for an ATM mutation carrier is 28%, 30% for CHEK2, 50% for PALB2, and 74% for BRCA1 and BRCA2. However, the BC risks are predicted to increase with FH burden. In families with mutations, predicted risks for mutation-negative members depend on both FH and the specific mutation. The reduction in BC risk after negative predictive testing is greatest when a BRCA1 mutation is identified in the family, but for women whose relatives carry a CHEK2 or ATM mutation, the risks decrease slightly. CONCLUSIONS: The model may be a valuable tool for counseling women who have undergone gene panel testing for providing consistent risks and harmonizing their clinical management. A Web application can be used to obtain BC risks in clinical practice (http://ccge.medschl.cam.ac.uk/boadicea/).Genet Med 18 12, 1190-1198.This work was funded by Cancer Research UK Grants C12292/A11174 and C1287/A10118. ACA is a Cancer Research UK Senior Cancer Research Fellow. This work was supported by the Governement of Canada through Genome Canada and the Canadian Institutes of Health Research, and the Ministère de l'enseignement supérieur, de la recherche, de la science et de la technologie du Québec through Génome Québec.This is the author accepted manuscript. The final version is available from Nature Publishing Group via http://dx.doi.org/10.1038/gim.2016.3

Parity and breast cancer risk among BRCA1 and BRCA2 mutation carriers.

INTRODUCTION: Increasing parity and age at first full-term pregnancy are established risk factors for breast cancer in the general population. However, their effects among BRCA1 and BRCA2 mutation carriers is still under debate. We used retrospective data on BRCA1 and BRCA2 mutation carriers from the UK to assess the effects of parity-related variables on breast cancer risk. METHODS: The data set included 457 mutation carriers who developed breast cancer (cases) and 332 healthy mutation carriers (controls), ascertained through families seen in genetic clinics. Hazard ratios were estimated by using a weighted cohort approach. RESULTS: Parous BRCA1 and BRCA2 mutation carriers were at a significantly lower risk of developing breast cancer (hazard ratio 0.54, 95% confidence interval 0.37 to 0.81; p = 0.002). The protective effect was observed only among carriers who were older than 40 years. Increasing age at first live birth was associated with an increased breast cancer risk among BRCA2 mutation carriers (p trend = 0.002) but not BRCA1 carriers. However, the analysis by age at first live birth was based on small numbers. CONCLUSION: The results suggest that the relative risks of breast cancer associated with parity among BRCA1 and BRCA2 mutation carriers may be similar to those in the general population and that reproductive history may be used to improve risk prediction in carriers.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

Risk-reducing salpingo-oophorectomy, natural menopause, and breast cancer risk:an international prospective cohort of BRCA1 and BRCA2 mutation carriers

Background The effect of risk-reducing salpingo-oophorectomy (RRSO) on breast cancer risk for BRCA1 and BRCA2 mutation carriers is uncertain. Retrospective analyses have suggested a protective effect but may be substantially biased. Prospective studies have had limited power, particularly for BRCA2 mutation carriers. Further, previous studies have not considered the effect of RRSO in the context of natural menopause. Methods A multi-centre prospective cohort of 2272 BRCA1 and 1605 BRCA2 mutation carriers was followed for a mean of 5.4 and 4.9 years, respectively; 426 women developed incident breast cancer. RRSO was modelled as a time-dependent covariate in Cox regression, and its effect assessed in premenopausal and postmenopausal women. Results There was no association between RRSO and breast cancer for BRCA1 (HR = 1.23; 95% CI 0.94-1.61) or BRCA2 (HR = 0.88; 95% CI 0.62-1.24) mutation carriers. For BRCA2 mutation carriers, HRs were 0.68 (95% CI 0.40-1.15) and 1.07 (95% CI 0.69-1.64) for RRSO carried out before or after age 45 years, respectively. The HR for BRCA2 mutation carriers decreased with increasing time since RRSO (HR = 0.51; 95% CI 0.26-0.99 for 5 years or longer after RRSO). Estimates for premenopausal women were similar. Conclusion We found no evidence that RRSO reduces breast cancer risk for BRCA1 mutation carriers. A potentially beneficial effect for BRCA2 mutation carriers was observed, particularly after 5 years following RRSO. These results may inform counselling and management of carriers with respect to RRSO.</p

Letter to the editor: a response to Ming’s study on machine learning techniques for personalized breast cancer risk prediction

A recent paper [1] compared two well-known breast cancer risk prediction models (BCRAT and BOADICEA) with eight different machine learning (ML) methods. The authors found a striking improvement in cancer prediction with ML. While their comparative assessment against more classical approaches is timely, we are skeptical about the results presented

Risk Prediction Models for Colorectal Cancer Incorporating Common Genetic Variants: A Systematic Review.

Colorectal cancer screening reduces colorectal cancer incidence and mortality. Risk models based on phenotypic variables have relatively good discrimination in external validation and may improve efficiency of screening. Models incorporating genetic variables may perform better. In this review, we updated our previous review by searching Medline and EMBASE from the end date of that review (January 2014) to February 2019 to identify models incorporating at least one SNP and applicable to asymptomatic individuals in the general population. We identified 23 new models, giving a total of 29. Of those in which the SNP selection was on the basis of published genome-wide association studies, in external or split-sample validation the AUROC was 0.56 to 0.57 for models that included SNPs alone, 0.61 to 0.63 for SNPs in combination with other risk factors, and 0.56 to 0.70 when age was included. Calibration was only reported for four. The addition of SNPs to other risk factors increases discrimination by 0.01 to 0.06. Public health modeling studies suggest that, if determined by risk models, the range of starting ages for screening would be several years greater than using family history alone. Further validation and calibration studies are needed alongside modeling studies to assess the population-level impact of introducing genetic risk-based screening programs