C. E. Desantis, F. Bray, J. Ferlay, J. Lortet-tieulent, B. O. Anderson et al., International variation in female breast cancer incidence and mortality rates, Cancer Epidemiol Biomark Prev, vol.24, pp.1495-1506, 2015.

F. J. Couch, K. L. Nathanson, and K. Offit, Two decades after BRCA: setting paradigms in personalized cancer care and prevention, Science, vol.343, pp.1466-1470, 2014.

A. W. Kurian, A. C. Antoniou, and S. M. Domchek, Refining breast cancer risk stratification: additional genes, additional information, Am Soc Clin Oncol Educ Book, vol.35, pp.44-56, 2016.

J. Doherty, D. C. Bonadies, and E. T. Matloff, Testing for hereditary breast cancer: panel or targeted testing? Experience from a clinical cancer genetics practice, J Genet Couns, vol.24, pp.683-687, 2014.

T. P. Slavin, M. Niell-swiller, I. Solomon, B. Nehoray, C. Rybak et al., Clinical application of multigene panels: challenges of next-generation counseling and cancer risk management, Front Oncol, vol.5, p.208, 2015.

A. W. Kurian, E. E. Hare, M. A. Mills, K. E. Kingham, L. Mcpherson et al., Clinical evaluation of a multiplegene sequencing panel for hereditary cancer risk assessment, J Clin Oncol, vol.32, pp.2001-2009, 2014.

D. F. Easton, P. D. Pharoah, A. C. Antoniou, M. Tischkowitz, S. V. Tavtigian et al., Gene-panel sequencing and the prediction of breast-cancer risk, N Engl J Med, vol.372, pp.2243-2257, 2015.

, Devilee P Breast Cancer Risk after Diagnostic Gene Sequencing (BRIDGES), 2020.

A. C. Antoniou, R. Hardy, L. Walker, D. G. Evans, A. Shenton et al., Predicting the likelihood of carrying a BRCA1 or BRCA2 mutation: validation of BOADICEA, BRCAPRO, IBIS, Myriad and the Manchester scoring system using data from UK genetics clinics, J Med Genet, vol.45, pp.425-431, 2008.

A. P. Cunningham, A. C. Antoniou, and D. F. Easton, Clinical software development for the Web: lessons learned from the BOADI-CEA project, BMC Med Inform Decis Mak, vol.12, p.30, 2012.

R. J. Macinnis, A. Bickerstaffe, C. Apicella, G. S. Dite, J. G. Dowty et al., Prospective validation of the breast cancer risk prediction model BOADI-CEA and a batch-mode version BOADICEACentre, Br J Cancer, vol.109, pp.1296-1301, 2013.

A. J. Lee, A. P. Cunningham, K. B. Kuchenbaecker, N. Mavaddat, D. F. Easton et al., BOADICEA breast cancer risk prediction model: updates to cancer incidences, tumour pathology and web interface, Br J Cancer, vol.110, pp.535-545, 2014.

A. J. Lee, A. P. Cunningham, M. Tischkowitz, J. Simard, P. D. Pharoah et al., Incorporating truncating variants in PALB2, CHEK2, and ATM into the BOADICEA breast cancer risk model, Genet Med, vol.18, pp.1190-1198, 2016.

H. Yi, T. Xiao, P. S. Thomas, A. N. Aguirre, C. Smalletz et al., Barriers and facilitators to patient-provider communication when discussing breast cancer risk to aid in the development of decision support tools, AMIA Annu Symp Proc, pp.1352-1360, 2015.

P. P. Chiang, D. Glance, J. Walker, F. M. Walter, and J. D. Emery, Implementing a QCancer risk tool into general practice consultations: an exploratory study using simulated consultations with Australian general practitioners, Br J Cancer, vol.112, issue.1, pp.77-83, 2015.

J. Jbilou, N. Halilem, J. Blouin-bougie, A. N. Landry, R. Simard et al., Medical genetic counseling for breast cancer in primary care: a synthesis of major determinants of physicians' practices in primary care settings, Public Health Genom, vol.17, pp.190-208, 2014.

F. Husson, S. Lê, and J. Pagès, Exploratory multivariate analysis by example using R, Jolliffe IT. Principal component analysis, 2002.
URL : https://hal.archives-ouvertes.fr/hal-00566638

E. G. Engelhardt, A. H. Pieterse, N. Van-duijn-bakker, J. R. Kroep, H. C. De-haes et al., Breast cancer specialists' views on and use of risk prediction models in clinical practice: a mixed methods approach, Acta Oncol, vol.54, pp.361-367, 2015.

E. A. Schackmann, D. F. Munoz, M. A. Mills, S. K. Plevritis, and A. W. Kurian, Feasibility evaluation of an online tool to guide decisions for BRCA1/2 mutation carriers, Fam Cancer, vol.12, pp.65-73, 2013.

P. J. Edwards, I. Roberts, M. J. Clarke, C. Diguiseppi, R. Wentz et al., Methods to increase response to postal and electronic questionnaires, Cochrane Database Syst, 2009.

E. Cottrell, E. Roddy, T. Rathod, E. Thomas, M. Porcheret et al., Maximising response from GPs to questionnaire surveys: do length or incentives make a difference, BMC Med Res Methodol, vol.15, p.3, 2015.

. Limesurvey-project-team and C. Schmitz, LimeSurvey: an open source survey tool, 2015.

B. G. Tabachnick and L. S. Fidell, Using multivariate statistics, 6th edn, 2013.

. R-core-team, R: a language and environment for statistical computing. R Foundation for Statistical Computing, 2016.

G. Parmigiani, D. Berry, and O. Aguilar, Determining carrier probabilities for breast cancer-susceptibility genes BRCA1 and BRCA2, Am J Hum Genet, vol.62, pp.145-158, 1998.

E. Mazzola, A. Blackford, G. Parmigiani, and S. Biswas, Recent enhancements to the genetic risk prediction model BRCAPRO, Cancer Inform, vol.14, pp.147-157, 2015.

J. Tyrer, S. W. Duffy, and J. Cuzick, A breast cancer prediction model incorporating familial and personal risk factors, Stat Med, vol.23, pp.1111-1130, 2004.

I. M. Collins, A. Bickerstaffe, T. Ranaweera, S. Maddumarachchi, L. Keogh et al., iPrevent(R): a tailored, web-based, decision support tool for breast cancer risk assessment and management, Breast Cancer Res Treat, vol.156, pp.171-182, 2016.

C. Fischer, K. Kuchenbacker, C. Engel, S. Zachariae, K. Rhiem et al., Evaluating the performance of the breast cancer genetic risk models BOADICEA, IBIS, BRCAPRO and Claus for predicting BRCA1/2 mutation carrier probabilities: a study based on 7352 families from the german hereditary breast and ovarian cancer consortium, J Med Genet, vol.50, pp.360-367, 2014.

A. S. Quante, A. S. Whittemore, T. Shriver, J. L. Hopper, K. Strauch et al., Practical problems with clinical guidelines for breast cancer prevention based on remaining lifetime risk, J Natl Cancer Inst, vol.107, p.124, 2015.

C. Julian-reynier, A. D. Bouhnik, D. G. Evans, H. Harris, C. J. Van-asperen et al., General practitioners and breast surgeons in France, Germany, Netherlands and the UK show variable breast cancer risk communication profiles, BMC Cancer, vol.15, p.243, 2015.
URL : https://hal.archives-ouvertes.fr/hal-01216078

E. Amir, O. C. Freedman, B. Seruga, and D. G. Evans, Assessing women at high risk of breast cancer: a review of risk assessment models, J Natl Cancer Inst, vol.102, pp.680-691, 2010.

L. J. Trevena, B. J. Zikmund-fisher, A. Edwards, W. Gaissmaier, M. Galesic et al., Presenting quantitative information about decision outcomes: a risk communication primer for patient decision aid developers, BMC Med Inform Decis Mak, vol.13, issue.2, p.7, 2013.

A. W. Kurian, D. F. Munoz, P. Rust, E. A. Schackmann, M. Smith et al., Online tool to guide decisions for BRCA1/2 mutation carriers, J Clin Oncol, vol.30, pp.497-506, 2012.

K. F. Douma, E. M. Smets, and D. C. Allain, Non-genetic health professionals' attitude towards, knowledge of and skills in discussing and ordering genetic testing for hereditary cancer, Fam Cancer, vol.15, pp.341-350, 2015.

S. A. Cohen and D. M. Nixon, A collaborative approach to cancer risk assessment services using genetic counselor extenders in a multi-system community hospital, Breast Cancer Res Treat, vol.159, pp.527-534, 2016.