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SAGE Publications, Tumori Journal, 1(102), p. 45-50, 2015

DOI: 10.5301/tj.5000407

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A targeted approach to genetic counseling in breast cancer patients: the experience of an Italian local project

This paper was not found in any repository, but could be made available legally by the author.
This paper was not found in any repository, but could be made available legally by the author.

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Abstract

Aims and background Patients with hereditary breast cancer (BC) may benefit from genetic counseling and testing for detection of causative mutations, definition of therapeutic and preventive strategies, and identification of at-risk relatives. Italy has few oncogenetic centers and genetic evaluation of all patients with BC is not feasible. Moreover, lack of uniformity in the selection of patients generates inappropriate referral to the geneticist. We designed a model that may represent a reproducible way to select patients at risk for hereditary BC, with the aims of rationalizing access to genetic centers and improving clinical management and surveillance. Methods The genetic unit of a Cancer Center and the Departments of Oncology from 2 public Hospitals in Milan were involved in the project. After training sessions at the genetic unit, operators from the 2 hospitals evaluated all patients with BC attending a first oncologic visit, through a specific interview. Patients considered at risk of hereditary BC attended counseling at the genetic unit. Results Of 419 patients, 61 (14.5%) were eligible for genetic counseling after the interview. Of these, 46 (10.9%) strictly met testing criteria. Overall, 52 (12.4%) patients underwent genetic counseling and 47 were tested for BRCA1/ BRCA2 mutation. After genetic test results, the available options for treatment/surveillance were discussed by a multidisciplinary team, according to the level of genetic risk. Conclusions It is possible to improve the process of referring patients with suspected hereditary BC for genetic risk assessment. The application of clinical screening reduced the genetics unit's workload and enabled optimization of time and resources.