BACKGROUND: We describe a multistep model of cancer genetic counselling designed to promote awareness, and disease surveillance and preventive measures for hereditary and familial breast and ovarian cancer. PATIENTS AND METHODS: Step T0 of the model entails information giving; this is followed by pedigree analysis and risk estimation (T1), risk communication and genetic testing (T2), and genetic test result communication (T3). User consent was required to proceed from one step to the next. Surveillance and preventive measures are proposed to at-risk users. Of the 311 subjects who requested cancer genetic counselling, consent data to each counselling step were available for 295: 93 were disease-free, 187 had breast cancer, 12 had ovarian cancer and three had breast plus ovarian cancer. RESULTS: Consent was high at T0 (98.39%), T1 (96.40%) and T2 (99.65%). Consent decreased at the crucial points of counselling: T2 (87.71%) and T3 [genetic test result communication (85.08%), and extension of counselling to and testing of relatives (65.36%)]. CONCLUSIONS: The model fosters the user's knowledge about cancer and favours identification of at-risk subjects. Furthermore, by promoting awareness about genetic testing and surveillance measures, the algorithm enables users to make a fully informed choice of action in case of predisposing or familial cancer risk.
BACKGROUND: We describe a multistep model of cancer genetic counselling designed to promote awareness, and disease surveillance and preventive measures for hereditary and familial breast and ovarian cancer. PATIENTS AND METHODS: Step T0 of the model entails information giving; this is followed by pedigree analysis and risk estimation (T1), risk communication and genetic testing (T2), and genetic test result communication (T3). User consent was required to proceed from one step to the next. Surveillance and preventive measures are proposed to at-risk users. Of the 311 subjects who requested cancer genetic counselling, consent data to each counselling step were available for 295: 93 were disease-free, 187 had breast cancer, 12 had ovarian cancer and three had breast plus ovarian cancer. RESULTS: Consent was high at T0 (98.39%), T1 (96.40%) and T2 (99.65%). Consent decreased at the crucial points of counselling: T2 (87.71%) and T3 [genetic test result communication (85.08%), and extension of counselling to and testing of relatives (65.36%)]. CONCLUSIONS: The model fosters the user's knowledge about cancer and favours identification of at-risk subjects. Furthermore, by promoting awareness about genetic testing and surveillance measures, the algorithm enables users to make a fully informed choice of action in case of predisposing or familial cancer risk.
Authors: G Cicero; R De Luca; P Dorangricchia; G Lo Coco; C Guarnaccia; D Fanale; V Calò; A Russo Journal: J Genet Couns Date: 2017-03-10 Impact factor: 2.537
Authors: C Condello; R Gesuita; M Pensabene; I Spagnoletti; I Capuano; C Baldi; F Carle; A Contegiacomo Journal: J Genet Couns Date: 2007-08-15 Impact factor: 2.537
Authors: Susanne B Haga; Rachel Mills; Kathryn I Pollak; Catherine Rehder; Adam H Buchanan; Isaac M Lipkus; Jennifer H Crow; Michael Datto Journal: Genome Med Date: 2014-07-31 Impact factor: 11.117
Authors: G Arpino; M Pensabene; C Condello; R Ruocco; I Cerillo; R Lauria; V Forestieri; M Giuliano; C De Angelis; M Montella; A Crispo; S De Placido Journal: BMC Cancer Date: 2016-11-29 Impact factor: 4.430