Australian Women’s Prediagnostic Decision-Making Styles, Relating to Treatment Choices for Early Breast Cancer Treatment

2003 ◽  
Vol 17 (2) ◽  
pp. 117-136 ◽  
Author(s):  
Lea M. Budden ◽  
Penny F. Pierce ◽  
Barbara A. Hayes ◽  
Petra G. Buettner
Keyword(s):  
Breast Cancer ◽  
Decision Making ◽  
Decision Support ◽  
Medical Treatment ◽  
Early Breast Cancer ◽  
Information Seeking ◽  
Treatment Plan ◽  
Treatment Decision ◽  
Treatment Choices ◽  
Decision Styles

Women diagnosed with early breast cancer are now asked by their doctors to choose from a range of options for their preferred medical treatment plan. Little information is known about women’s treatment decision-making and therefore nurses do not have evidence to guide this decision support. The aim of this descriptive survey was to investigate the prediagnostic decision-making behavior of a sample (N= 377) of Australian women, regarding their treatment choices for early breast cancer. The data were collected using the Pre-Decision Portfolio Questionnaire (PDPQ) by Pierce (1996), which includes the Michigan Assessment of Decision Styles (MADS). Of 366 participating women, 19.9% strongly agreed to all three items of the MADS factor Deferring Responsibility; 0.3% strongly agreed to all four factors of Avoidance; 32.7% strongly agreed on all four items of Information Seeking; and 63.4% strongly agreed to all five items of Deliberation. Women showed a variety of preferred decision styles, depending on age, education, occupation and employment status. Only 36% of women indicated it was critically important to “get the treatment over as soon as possible;” 55% to “participate in selecting treatment;” and 53% to “read a lot of information.” The understanding of factors that are important to women when they are making decisions for medical treatment is a mandatory step in designing customized evidence-based decision support, which can be delivered by nurses to help women during this distressing experience.

Gene Expression Assay in the Management of Early Breast Cancer

2020 ◽  
Vol 27 (17) ◽  
pp. 2826-2839 ◽  
Author(s):  
Roberta Caputo ◽  
Daniela Cianniello ◽  
Antonio Giordano ◽  
Michela Piezzo ◽  
Maria Riemma ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Decision Making ◽  
Adjuvant Chemotherapy ◽  
Early Breast Cancer ◽  
Treatment Decision ◽  
Endocrine Treatment ◽  
Expression Ratio ◽  
Treatment Decision Making ◽  
Low Sensitivity

The addition of adjuvant chemotherapy to hormonal therapy is often considered questionable in patients with estrogen receptor-positive early breast cancer. Low risk of disease relapse after endocrine treatment alone and/or a low sensitivity to chemotherapy are reasons behind not all patients benefit from chemotherapy. Most of the patients could be exposed to unnecessary treatment- related adverse events and health care costs when treatment decision-making is based only on classical clinical histological features. Gene expression profile has been developed to refine physician’s decision-making process and to tailor personalized treatment to patients. In particular, these tests are designed to spare patients the side effects of unnecessary treatment, and ensure that adjuvant chemotherapy is correctly recommended to patients with early breast cancer. In this review, we will discuss the main diagnostic tests and their potential clinical applications (Oncotype DX, MammaPrint, PAM50/Prosigna, EndoPredict, MapQuant Dx, IHC4, and Theros-Breast Cancer Gene Expression Ratio Assay).

Size and influence of the decision support networks of women newly diagnosed with breast cancer.

2017 ◽  
Vol 35 (15_suppl) ◽  
pp. e18012-e18012
Author(s):  
Lauren P. Wallner ◽  
Yun Li ◽  
Chandler McLeod ◽  
Ann S Hamilton ◽  
Kevin C. Ward ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Decision Making ◽  
Decision Support ◽  
Treatment Decision ◽  
Treatment Decisions ◽  
Breast Cancer Treatment ◽  
Network Size ◽  
Support Networks ◽  
Newly Diagnosed ◽  
Treatment Decision Making

e18012 Background: Little is known about the size and characteristics of informal decision support networks of women diagnosed with breast cancer and whether involvement of informal decision supporters (DSP) influences breast cancer treatment decisions. Methods: A population-based sample of newly diagnosed breast cancer patients reported to the Georgia and Los Angeles SEER registries in 2014-15 were surveyed approximately 6 months after diagnosis (N = 2,502, 68% response rate). Network size was estimated by asking women to list up to 3 of the most important DSPs who helped them with locoregional therapy decisions. For each individual DSP listed, respondents reported how important each DSP’s opinion was in treatment decision making, and how satisfied they were with their involvement (5 pt. scales, “not at all” to “very”). Decision deliberation was measured using 5-items assessing degree patients thought through the decision, with higher scores reflecting more deliberative treatment decisions. We compared network size (0-3 or more) across patient-level characteristics and estimated the association between network size and deliberation using multivariable linear regression. Results: Of the 2,502 women in this analysis, 51% reported having 3 or more DSPs, 20% reported 2, 18% reported 1, and 11% reported not having any DSPs. Married/partnered women, those younger than 45 years old, and black women were all more likely to report larger networks (all p < 0.001). Partnered women most often reported their partner as their main DSP (37.9%), whereas not partnered/unmarried women most often reported children (38.4%). The majority of women were highly satisfied with their DSP being involved in their decisions (76.5%) and 68.6% felt their DSP was very important in their decision making. Larger support networks were associated with more deliberative surgical treatment decision-making (p < 0.001). Conclusions: Most women engaged multiple DSPs in their treatment decision making, including spouses, children, and friends. Involving more DSPs was associated with more deliberative treatment decisions. Future initiatives to improve breast cancer treatment decision making should acknowledge and engage informal DSPs.

Population-based evaluation of 21-gene assay in treatment decision making for early breast cancer in Ontario.

2014 ◽  
Vol 32 (15_suppl) ◽  
pp. 583-583 ◽  
Author(s):  
Mark Norman Levine ◽  
Brandy Lynn Cochrane ◽  
Jim A. Julian ◽  
Maureen E. Trudeau ◽  
Andrea Eisen ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Decision Making ◽  
Early Breast Cancer ◽  
Treatment Decision ◽  
Population Based ◽  
Treatment Decision Making ◽  
Gene Assay

Prognostic impact of the inclusion of uPA/PAI-1 tumor levels in the current adjuvant treatment decision-making for early breast cancer

2014 ◽  
Vol 10 (2) ◽  
pp. 195-209 ◽  
Author(s):  
Haïdar Saadoun ◽  
Pierre-Jean Lamy ◽  
Simon Thezenas ◽  
Stéphane Pouderoux ◽  
Frédéric Bibeau ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Decision Making ◽  
Early Breast Cancer ◽  
Adjuvant Treatment ◽  
Treatment Decision ◽  
Prognostic Impact ◽  
Treatment Decision Making ◽  
Pai 1

scholarly journals Contribution of the Prosigna® (PAM50) Gene Signature Assay as a New-generation Genomic Test for Treatment Decision-making in Early Breast Cancer

2015 ◽  
Vol 11 (2) ◽  
pp. 85 ◽  
Author(s):  
Nadia Harbeck ◽  
Rachel Wuerstlein ◽  
Karl Sotlar ◽  
◽  
◽  
...  
Keyword(s):  
Breast Cancer ◽  
Decision Making ◽  
Early Breast Cancer ◽  
Cancer Biology ◽  
Treatment Decision ◽  
Gene Signature ◽  
Treatment Decision Making ◽  
Prognostic Gene ◽  
Prognostic Gene Signature ◽  
Post Menopausal

The Prosigna® Breast Cancer Prognostic Gene Signature Assay is based on the characterisation of 50 genes relevant to breast cancer biology and provides intrinsic subtype identification based on the individual tumour biology, a prognostic risk of recurrence (ROR) score and a risk group classification, for each individual patient tested. The Prosigna assay is indicated for post-menopausal women with early-stage hormone receptor-positive breast cancer with or without nodal involvement. Running on the NanoString nCounter® DX Analysis system, which allows direct digital counting of target molecules, the assay offers a simple, reproducible and reliable method to profile many genes simultaneously with high sensitivity and precision. The Prosigna Breast Cancer Prognostic Gene Signature Assay has received 510(k) clearance from the US Food and Drug Administration. It has also received a CE mark and is available for use, among other geographical areas, in the EU, Israel and parts of the Middle East, through qualified local pathology laboratories. The de-centralised testing enables timely result delivery and direct interaction between the laboratory pathologists and treating physicians. The analytical reproducibility, precision and robustness of Prosigna have been demonstrated. Moreover, it has been clinically validated in two independent prospectiveretrospective studies using >2,400 samples from post-menopausal patients enrolled in the Austrian Breast & Colorectal Cancer Study Group 8 (ABCSG 8) and Arimidex, Tamoxifen Alone or Combined (ATAC) trials (Level 1B Evidence). These validation studies show that Prosigna identifies a clinically relevant low-risk subgroup among both node-negative and node-positive patients with 1-3 involved lymph nodes. Moreover, the ROR score predicts risk of late distant recurrence as well as for high risk of local recurrence. Prosigna thus can offer clinically relevant information, which may help guide treatment decision-making in early breast cancer.

Decision-making tools to assist prognosis and treatment choices in early breast cancer: a review

2012 ◽  
Vol 12 (8) ◽  
pp. 1033-1043 ◽  
Author(s):  
Asmaa Al-Allak ◽  
Paul D Lewis ◽  
Gianfilippo Bertelli
Keyword(s):  
Breast Cancer ◽  
Decision Making ◽  
Early Breast Cancer ◽  
Treatment Choices
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