sábado, 2 de septiembre de 2017

Best practices for multidisciplinary integration of a DCIS genomic assay into clinical practice. - PubMed - NCBI

Best practices for multidisciplinary integration of a DCIS genomic assay into clinical practice. - PubMed - NCBI

 2017 Aug 22. doi: 10.1002/jso.24754. [Epub ahead of print]

Best practices for multidisciplinary integration of a DCIS genomic assay into clinical practice.

Abstract

Most newly diagnosed ductal carcinoma in situ (DCIS) is treated with breast-conserving surgery (BCS) ± radiation therapy (RT). A key challenge is deciding whether or not to include RT with BCS. This decision is often determined by the degree of risk associated with disease recurrence. However, methods for risk assessment have not kept pace with diagnostic advances. The DCIS Score is an independent predictor and quantifier of individualized recurrence risk in patients with DCIS. Although the test is the only available genomic classifier for DCIS, the degree of adoption is varied, and it has not yet been fully accepted as standard practice. Recognizing the importance of individualizing recurrence assessment in patients with DCIS, the authors convened to review relevant clinical data, share best practices, and establish recommendations regarding how the assay should be incorporated into the decision-making process. Based on their clinical experiences, the authors concluded that effective integration of the DCIS Score should involve shared decision-making between surgeons and other specialties (radiation oncologists, pathologists, patient navigators, and physician assistants), with the patient's preference being a primary consideration. This manuscript aims to provide easy-to-use, clear-cut, and practical guidance to help physicians utilize the DCIS Score to improve risk assessment and inform treatment decisions for their patients with DCIS, including how to understand, run, interpret, and communicate the actionable results to patients.

KEYWORDS:

DCIS; DCIS score; clinical practice integration; genomic assay

PMID:
 
28833159
 
DOI:
 
10.1002/jso.24754

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