MEND 2: Making Treatment Decisions Using Genomic Testing
Phase: NA
Conditions: Breast Cancer Female
Sponsor: Georgetown University

PROTOCOL TITLE:  
Making Treatment Decisions Using Genomic Testing 
 
Page 1 of 15 
 
 
PROTOCOL TITLE: 
MEND 2: Making Treatment Decisions Using Genomic Testing 
 
PRINCIPAL INVESTIGATOR: 
 
Suzanne C. O’Neill 
Oncology 
202-687-0869 
Sco4@georgetown.edu 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Final Continuing Review completed 9/19/22 

PROTOCOL TITLE:  
Making Treatment Decisions Using Genomic Testing 
 
Page 2 of 15 
 
 
Table of Contents 
1.0 
Study Summary ........................................................................................................ 3 
2.0 
Objectives* .............................................................................................................. 4 
3.0 
Background* ............................................................................................................ 4 
4.0 
Study Endpoints* ..................................................................................................... 5 
5.0 
Study Intervention/Investigational Agent ................................................................ 5 
6.0 
Procedures Involved*............................................................................................... 5 
7.0 
Data and Specimen Banking* .................................................................................. 8 
8.0 
Sharing of Results with Subjects* ........................................................................... 8 
9.0 
Study Timelines* ..................................................................................................... 8 
10.0 Inclusion and Exclusion Criteria* ............................................................................ 8 
11.0 Vulnerable Populations* .......................................................................................... 8 
12.0 Local Number of Subjects ....................................................................................... 9 
13.0 Recruitment Methods ............................................................................................... 9 
14.0 Withdrawal of Subjects* .......................................................................................... 9 
15.0 Risks to Subjects* .................................................................................................... 9 
16.0 Potential Benefits to Subjects* .............................................................................. 10 
17.0 Data Management* and Confidentiality ................................................................ 10 
18.0 Provisions to Monitor the Data to Ensure the Safety of Subjects* ........................ 12 
19.0 Provisions to Protect the Privacy Interests of Subjects .......................................... 12 
20.0 Compensation for Research-Related Injury ........................................................... 12 
21.0 Economic Burden to Subjects ................................................................................ 12 
22.0 Consent Process ..................................................................................................... 12 
23.0 Process to Document Consent in Writing .............................................................. 13 
24.0 Setting .................................................................................................................... 13 
25.0 Resources Available............................................................................................... 13 
26.0 Multi-Site Research ............................................................................................... 13 
 
 
 
 
 

PROTOCOL TITLE:  
Making Treatment Decisions Using Genomic Testing 
 
Page 3 of 15 
 
1.0 
Study Summary 
 
Study Title 
MEND 2: Making Treatment Decisions Using Genomic 
Testing 
Study Design
Single Arm Feasibility and Efficacy Study
Primary Objective 
 Examine intervention feasibility via patient and 
oncologist acceptability, recruitment and retention, 
and fidelity  
Secondary 
Objective(s) 
 Evaluate intervention effects on comprehension and 
treatment preferences. 
 Assess potential intervention mechanisms on 
comprehension, preferences, and satisfaction.
Research 
Intervention(s)/ 
Investigational 
Agent(s) 
Two surveys and audio recordings of patient-physician 
encounter using the question prompt list.  
IND/IDE #  
N/A
Study Population
Patients 
Sample Size
75
Study Duration for 
individual 
participants
About a month, depending on appointment schedule. 
Study Specific 
Abbreviations/ 
Definitions  
QPL: Question Prompt List    
HER2: Human Epidermal Growth Factor Receptor 2 
ER: Estrogen Receptor 
PR: Progesterone Receptor 
LCCC: Lombardi Comprehensive Cancer Center 
WHC: Cancer Institute at Washington Hospital Center 
MCC: H. Lee Moffitt Comprehensive Cancer Center 
 
 

PROTOCOL TITLE:  
Making Treatment Decisions Using Genomic Testing 
 
Page 4 of 15 
 
2.0 
Objectives* 
 
2.1 Specific Aims. 
 Specific Aim 1: Examine intervention feasibility in 3 areas: 
1) patient and oncologist acceptability, 2) participant 
recruitment and retention, and 3) intervention dosage and 
fidelity. 
 Specific Aim 2: Evaluate intervention effects on 
comprehension and treatment preferences.  
 Specific Aim 3: Assess potential intervention mechanisms on 
comprehension, preferences, and satisfaction. 
2.2 Hypotheses/Research questions. 
 Aim 2 Hypothesis: Participants will demonstrate significant 
increases in comprehension about their disease and its 
treatments from pre- to post-QPL. Participants will be more 
likely to report Score-concordant preferences from pre to 
post-QPL.  
 Aim 3 Hypothesis: Patient comprehension and satisfaction 
will be higher following encounters with greater shared 
decision making, greater perceived communication quality, 
and more frequent discussion of risks/benefits of treatments. 
Patient preferences will likely be more Score-concordant 
following encounters with greater shared decision making, 
greater perceived communication quality, and more frequent 
discussion of risks/benefits of treatments. 
 
3.0 
Background* 
 
Breast cancer is the most common cancer among US women, with more than 230,000 new 
diagnoses and 40,000 deaths each year,1 along with decrements in quality of life.2 Half of all 
newly-diagnosed patients are affected with estrogen-receptor positive, early-stage disease. 
Clinical guidelines for these women integrate genomic tumor profiling tests such as the 
Oncotype DX® Recurrence Score to refine recurrence estimates and systemic therapy 
selection when combined with existing markers. Thousands of women receive testing each 
year.3–5 While these women should all receive hormonal therapy, guidelines suggest that the 
25% with a high Score benefit from additional chemotherapy and the 50% with a low Score 
can safely avoid chemotherapy.6 Appropriate treatment for the 25% of women with 
intermediate Recurrence Scores remains unclear until clinical trial (TAILORx) results are 
released in the next year.7  
Despite continuing dissemination, many challenges remain to maximize the benefits offered 
by testing and refined treatment selection. Many women have a poor understanding of their 

PROTOCOL TITLE:  
Making Treatment Decisions Using Genomic Testing 
 
Page 5 of 15 
 
Recurrence Score and its impact of treatment selection.8  Further, our data suggest that 
patients’ pretesting preferences do not shift following the receipt of their Recurrence Score, 
even following discussion of test results that should guide treatment selection. These 
preferences are a powerful driver of treatment utilization, predicting treatment received over 
and above the effect of the Recurrence Score and other clinical variables. Indeed, many 
patients do not receive Score-concordant care.4,9–11 Finally, tested patients who do not take 
an active role in their care and report poorer communication by their oncologist are at risk 
for higher distress and poorer quality of life.12 Our data suggest a need to test interventions 
that support communication about the Recurrence Score, improving patient comprehension 
and better aligning patient preferences with evidence-based recommendations, ultimately 
impacting patient morbidity and mortality. TAILORx results will continue to strengthen the 
evidence for clinical utility and increase testing rates. An effective intervention should be 
ready to respond to this increasing need.  
Street et al.’s model of patient-centered communication13 suggests pathways through which 
clinical communication has indirect effects on morbidity and mortality. Communication can 
influence more proximal outcomes, including patient comprehension of their disease and its 
treatments, treatment preferences and satisfaction, involvement in care decisions as well as 
longer-term outcomes of treatment adherence and quality of life.14 We aim to test the 
feasibility and impact of a patient activation intervention to support effective integration of 
the Recurrence Score into clinical encounters and treatment decisions. Patient activation 
interventions utilizing a question prompt list (QPL) can impact proximal outcomes of 
preferences, comprehension, satisfaction and involvement.15–18 A QPL could allow tested 
patients to better understand the rationale for their oncologist’s treatment recommendation 
and its impact on the management of their disease, as well as encourage alignment of 
treatment preferences, the Recurrence Score and treatment selection. In this trial, we will 
recruit newly-diagnosed breast cancer patients to a single-arm trial to demonstrate feasibility 
and preliminarily assess the impact of the QPL on key outcomes. 
 
4.0 
Study Endpoints* 
 
4.1 Primary Endpoint: Patient activation via a question prompt list 
intervention.  
4.2 Secondary Endpoints: ____.  
4.3 Safety Endpoints: Safety endpoints have not been established as this 
is a minimal risk study. 
 
5.0 
Study Intervention/Investigational Agent 
 
N/A 
 
6.0 
Procedures Involved* 

PROTOCOL TITLE:  
Making Treatment Decisions Using Genomic Testing 
 
Page 6 of 15 
 
6.1 This is a feasibility and efficacy study. Two participant interviews will be 
conducted by the study staff. Audio recordings will be collected of patient-
physician encounters using the QPL over a month time span. 
 
6.2 Eligible patients will be contacted by study staff via phone call. The study 
staff will describe the study, answer questions, obtain verbal consent, and 
complete the first, T1 interview before the patient receives Oncotype DX results. 
After obtaining a signed informed consent and HIPAA authorization by mail, the 
QPL will be provided to the patient. They will receive the QPL by mail or email, 
depending on their preference, before their Score disclosure appointment. Study 
staff will be available to audio record the patient-physician encounter during their 
appointment. The second, T2 interview will be done after patients receive their 
test results but prior to initiation of adjuvant chemotherapy. 
 
6.3   The risks of participation are minimal. The survey elements have been 
designed to minimize emotional distress. A distress protocol has been put in place 
to refer subjects to psychological consult when appropriate. It is possible that 
participants will derive benefit from the use of the QPL in how they communicate 
with their physician and make decisions regarding treatment options. 
 
6.4  Measures will include: 
Sociodemographics. We will assess age, race/ethnicity, education, marital, employment, 
income, insurance status, comorbidity, and family cancer history. 
 
Disease variables and treatments. We will assess diagnosis date, pathology (staging, 
grade, ER/PR/HER2), treatments, and dates.  
 
Oncotype DX Recurrence Score. We will assess the Recurrence Score and the related 
category. 
Chemotherapy Selection. In our work, 95% of women make definitive treatment 
decisions by T2. If not, this will be noted and the interview will continue. Data 
will be confirmed in the medical record. 
 
Self-Reported Measures: 
Table 1. Variables and Data  Sources
Variable
Measure/source
Timepoint
Controlling and Clinical Variables
T1
Encounter
T2
Sociodemographics 
X
Disease Variables, Treatments
Self-report and chart review
X
X
Recurrence Score
Self-report and chart review
X
Outcomes and Mediators 
Chemo. Selection 
Self-report and chart review 
 
 
X 

PROTOCOL TITLE:  
Making Treatment Decisions Using Genomic Testing 
 
Page 7 of 15 
 
 
Chemotherapy Preferences. We will assess preferences for chemotherapy by 
assessing the perceived pros (8 items) and cons (8 items) of treatment as we do in 
our ongoing work. Women rate the importance of each item on a scale from 1 
(Not at all important) to 4 (Very important). Ratings are averaged to create scales, 
with higher scores indicating greater importance of profs and cons. Internal 
relatability is high for pros-cons, with scores above zero indicating a preference 
for chemotherapy. Preference concordance will be determined through a match 
between post-Score preference and treatment received. 
Comprehension. We will assess comprehension of adjuvant treatment, 
Recurrence Score and category, and treatment implications (The Test helps 
women decide about chemotherapy (Y/N)). We will apply existing comprehension 
items, in which patients average 70% correct.14 
Satisfaction. We will assess Decisional Satisfaction with the valid and reliable 6-
item Satisfaction with Decision Scale, rated on a 5-point Likert scale (Strongly 
agree/ disagree), with a higher score indicating greater satisfaction. The measure 
has been used to assess satisfaction with breast cancer adjuvant treatment 
decisions.19 
Perceived communication quality. We will assess patients’ perceptions of 
quality of patient-physician communication using a 7-item scale from 1 (Very 
strongly disagree) to 6 (Very strongly agree). This scale has good reliability and 
validity and we have used this measure in our current observational study. Items 
are relevant to chemotherapy decisions (The doctor fully explained the risks of 
treatment recommended). Patients will respond to these regarding their primary 
Medical Oncologist.20 
Oncologist variables. We will record race, ethnicity, and gender of the patient’s 
primary medical oncologist for our measurement of concordance. 
Coding of Oncology Encounters. We will audio record, transcribe, and code 
clinical encounters to inform potential intervention mechanisms. Broadly 
speaking, coding systems capture an encounter’s content and process. No single 
coding system has emerged as definitive or captures our specific encounter 
content and communication processes. We will code encounters for RS- and 
treatment related information, shared decision making, patient active participation 
and patient-centered communication.21,22 Dr. O’Neill will merge these data with 
patient self-report using study ID. 
 
 
 
Chemo. Preferences 
Preferences 
X 
 
X 
Comprehension 
Adjuvant treatment, Recurrence Score, 
treatment implications
X 
 
X 
Coding of clinical encounters 
RS- and treatment related information, 
shared decision making, patient active 
participation 
and 
patient-centered 
communication
 
X 
X 
Decisional Satisfaction  
SDS 
 
 
X 
Communication Quality 
Makoul et al.  
 
 
X 

PROTOCOL TITLE:  
Making Treatment Decisions Using Genomic Testing 
 
Page 8 of 15 
 
 
7.0 
Data and Specimen Banking* 
7.1 N/A 
8.0 
Sharing of Results with Subjects* 
8.1 Study results will be shared with participants at the end of the study.  
9.0 
Study Timelines* 
9.1 The participants will be enrolled for about a month. They will 
complete the first interview after consenting and will also complete a 
follow up interview right after receiving Oncotype DX results. All 
study activities should be completed within 2 months. Recruitment 
and retention are described in Figure 1. 
10.0 Inclusion and Exclusion Criteria* 
10.1 Study staff at each site will monitor electronic patient records systems 
that track test orders, attend weekly Breast Cancer Meetings, and 
coordinate with clinic staff to recruit patients they determine to be 
eligible. 
10.2 Participants will be females aged 40-75 who will receive Oncotype 
DX testing prior to initiation of systemic treatment. 
10.3 We will not include patients with cognitive impairment that precludes 
informed consent as determined by self-report, our trained study 
personnel, or patient records. We will also exclude those who are 
unable to provide consent in English.  
11.0 Vulnerable Populations* 
11.1 Pregnant women, students, those economically disadvantaged and 
employees will not be excluded from this study if they are otherwise 
eligible to participate. We will ensure that all informed consent such 

PROTOCOL TITLE:  
Making Treatment Decisions Using Genomic Testing 
 
Page 9 of 15 
 
that they will be asked to repeat back the purposed of the study after a 
member of the study team has gone over written informed consent. In 
addition, although we will be providing incentives for participation in 
the form of a gift card the incentives are not so large as to be coercive. 
12.0 Local Number of Subjects 
60 
13.0 Recruitment Methods 
13.1 Participants will be recruited via phone call, identified as below, by 
research staff. 
13.2 Participants will be drawn from breast clinics at LCCC, Moffitt 
Cancer Center, and WHC. 
13.3 PI/Collaborators will recruit participants from his/her/their own 
patient population. 
13.4 Study materials include participant information/consent and 
interview done over a phone call. It will also include mailed 
introductory contact letter, informed consent form, study information 
sheet, and HIPPA waiver to be physically signed by participants. 
13.5 Participants will receive a $20 gift card to thank them for their time 
completing interviews and $25 for recording of their clinical 
encounter. 
14.0 Withdrawal of Subjects* 
14.1 Reason for withdrawing include lack of time and not being interested 
in participating in research related to breast cancer.  
14.2 N/A 
14.3 Participants will be informed that they can withdraw from the study at 
any time. We will track the number of eligible participants that 
withdraw. Data from participants that withdraw from the study will 
not be used. 
15.0 Risks to Subjects* 
15.1 
The primary sources of risk concerns data privacy, confidentiality, and 
psychological discomfort. There are few psychological risks to completing 
cognitive, decision making, and psychological assessments. However, interviews 
may contain questions that make participants feel uncomfortable or bring up 
unwanted thoughts or feelings. There is also minimal risk that using the QPL will 
increase any psychological distress. All participants will be informed in advance of 
participation and each data collection opportunity that any questions that make 
them feel uncomfortable may be skipped or ignored.  
 
The risk of gathering social, behavioral, and medical information is also present.  
 

PROTOCOL TITLE:  
Making Treatment Decisions Using Genomic Testing 
 
Page 10 of 15 
 
There is some risk for breach of confidentiality. However, we have taken multiple 
steps to ensure this risk is very low. Only key staff members will have access to 
individually identifiable private information about participants, including the 
principal investigator, the project coordinator, and research assistants. We also 
developed a rigorous data management plan to reduce this risk.  
 
16.0 Potential Benefits to Subjects* 
16.2 
There is no direct benefit to individual subjects. 
 
17.0 Data Management* and Confidentiality 
 
17.1 We will calculate descriptive and frequency distributions for all variables. We 
will assess the quality of the data and evaluate the extent and impact of missing data. For 
categorical variables, we will use Chi-Square tests or Fisher’s exact tests if needed. We 
will test continuous variables with Student t-tests or Mann-Whitney U tests for non-normal 
data. Any variable that exhibits a p<.10 association with the key predictors or outcomes 
will be controlled in multivariable analyses. Potential covariates include sociodemographic 
and clinical variables as well as differenced. 
 
Our primary endpoint is the percentage of patients activated via a question prompt list 
intervention. Women will demonstrate significant increase in comprehension from pre- to 
post-QPL. 
 
Using a 2-tailed α=0.05 and assumed a minimum of 75 participants at T2 and accounting 
for clustering by oncologist, we calculated effective sample sizes assuming an average 
cluster size of 10 patients per oncologist and an ICC of 0.02. This reduces the sample size 
by a factor of 1.18, leaving an effective N=64 at T2. We will have 80% power to detect 
changes in mean comprehension of 0.4 SD assuming a correlation of 0.5 between pre- and 
post- scores. We will use multilevel models to address the clustering of observations within 
patients and of patients within oncologists. These mixed effects regression models will 
include random effects for patient and oncologist and fixed effects for time, the main 
predictor, and covariates. The multilevel model for 2a will be a linear model and we will 
estimate the adjusted mean change in comprehension and the corresponding 95% 
confidence interval. We will estimate an adjusted odds ratio with the corresponding 95% 
confidence interval.    
 
 
17.2 Data collected in this study will be used exclusively for research purposes; it 
will be managed and stored according to our sites’ security standards for data that require 
the highest possible security to ensure there will be no inadvertent disclosure. Any 
computers storing or accessing data collected for the study will be required to comply with 
these standards. 
 
During the trial, all study data downloaded from REDCap or gathered from other sources 
will reside in a HIPAA-compliant study folder. Access to the study folder is provided based 

PROTOCOL TITLE:  
Making Treatment Decisions Using Genomic Testing 
 
Page 11 of 15 
 
on employee’s role, on a ‘need to know, least privilege’ basis. Georgetown BOX is a secure 
(HIPAA/PHI approved) place to store study files.  
 
No identifying data will be stored on laptop computers or other mobile computing 
hardware. Computers used to access the data will be protected by a username and password 
that meet our IT departments’ complexity and change requirements to ensure a high degree 
of security, and they will be protected with anti-virus software and scanned regularly for 
vulnerabilities.  
 
REDCap (Research Electronic Data Capture) is a research tool developed at Vanderbilt 
University as a secure web application to allow users to build and manage online surveys 
and databases, and to support data capture for research studies. It is a secure, IRB-
approved, web-based application designed for managing online surveys and for 
communication between study sites. A locally hosted instance of REDCap will be used to 
store study data (Surveys, selected clinical data and tracking information such as 
participant names, phone numbers, address, etc). Questionnaires or other paper forms 
collected from each participant will be identified solely by participants’ confidential study 
identification number and stored in a locked filing cabinet in study offices.  
 
All study staff members will be trained to use these procedures, which will be detailed in 
a study manual of operating procedures. We have found that using these procedures 
provides a high degree of protection with respect to the privacy of individuals and the 
confidentiality of data. 
 
17.3        N/A 
17.4 
N/A 
 
 
 
18.0 Provisions to Monitor the Data to Ensure the Safety of Subjects* 
18.1 We do not anticipate more than minimal risk to participants.  
 
19.0 Provisions to Protect the Privacy Interests of Subjects 
19.1 No one who is not a part of the study team will have access to the 
study records or data, unless it is necessary to reveal this information 
for regulatory or legal reasons. Only a code number will be used to 
identify study-related data. Matching lists of names and code 
numbers will be kept in locked storage facilities in the PI’s office 
and/or laboratory space. All data will be similarly stored in locked 
facilities. All computer files containing participant data will be 
accessed only through password protected security systems and are 
stored on a secure and private server. 

PROTOCOL TITLE:  
Making Treatment Decisions Using Genomic Testing 
 
Page 12 of 15 
 
 
20.0 Compensation for Research-Related Injury 
 
20.1 We do not anticipate more than minimal risk to participants. 
 
21.0 Economic Burden to Subjects 
 
21.1 n/a 
 
22.0 Consent Process 
22.1 We will obtain consent from participants prior to their first interview, 
QPL distribution, recorded patient-physician interaction, and follow 
up interview.  
 
Consent will be obtained verbally via phone call and physically 
through mailed consent form.  
Non-English Speaking Subjects 
 
N/A 
Waiver or Alteration of Consent Process (consent will not be 
obtained, required information will not be disclosed, or the 
research involves deception) 
 
We are requesting a limited HIPAA waiver to support 
recruitment. All information obtained for individuals who are 
not retained as participants will be destroyed.   
 
Consent will be obtained as an online consent. 
Subjects who are not yet adults (infants, children, teenagers) 
 
N/A 
Cognitively Impaired Adults 
 
N/A 
Adults Unable to Consent 
 N/A 
23.0 Process to Document Consent in Writing 

PROTOCOL TITLE:  
Making Treatment Decisions Using Genomic Testing 
 
Page 13 of 15 
 
23.1 Participants will complete verbal consent to all study activities either 
in clinic or over the phone. They will receive a printed copy of the 
consent over the mail along with a self-addressed, pre-stamped return 
envelope. 
 
24.0 Setting 
24.1 We anticipate recruiting from across the LCCC/MedStar clinical 
research (surgery and medical oncology) network. This network 
includes the main academic hospital and several local community 
referral hospitals in the metro-DC area. 
Eligible breast cancer patients will also be recruited from Moffitt 
Cancer Center. The Clinical Research Department at MCC utilized 
several means to screen patients to ascertain their potential eligibility 
for clinical trials. This site has a central Research Department to assist 
and facilitate with participant recruitment as follows. This includes 
screening of the electronic scheduling system, review of schedules 
posted within clinical care areas, attendance at tumor boards, and 
regular interaction with physicians and nurses.  
1) Access is sough solely to review PHI as necessary to prepare a 
research protocol for similar purposes preparatory research (i.e. 
screening), 
2) No PHI will be removed, and    
3) The PHI access and review is necessary for the research purposes. 
25.0 Resources Available 
 
25.1 The study will be conducted within the context of a funded research 
program and supported by trained research staff. All staff will be 
trained to support this protocol and methods. We will collaborate 
with existing shared resources within the cancer center for 
recruitment. 
 
26.0 Multi-Site Research* 
 
26.1 
Study-Wide Number of Subjects* 
We very conservatively project 60 eligible participants per year from 
LCCC/WHC and 120 eligible participants per year at MCC. 
 
26.2 
Subjects will be recruited according to methods under the control of the 
local site. Sites will have bi-monthly meetings to discuss strategies and any issues 
as they arise.  
 
 

PROTOCOL TITLE:  
Making Treatment Decisions Using Genomic Testing 
 
Page 14 of 15 
 
 
References 
 
1.  
Siegel RL, Miller KD, Jemal A. Cancer statistics, 2019. CA: A Cancer Journal for 
Clinicians. 2019;69(1):7–34.  
2.  
Ganz PA, Kwan L, Stanton AL, Bower JE, Belin TR. Physical and psychosocial 
recovery in the year after primary treatment of breast cancer. Journal of Clinical 
Oncology: Official Journal of the American Society of Clinical Oncology. 2011 Mar 
20;29(9):1101–1109. PMCID: PMC3083865 
3.  
Roberts MC, Weinberger M, Dusetzina SB, Dinan MA, Reeder-Hayes KE, Carey 
LA, Troester MA, Wheeler SB. Racial Variation in the Uptake of Oncotype DX Testing 
for Early-Stage Breast Cancer. J Clin Oncol. 2016 Jan 10;34(2):130–138. PMCID: 
PMC4872005 
4.  
Hassett MJ, Silver SM, Hughes ME, Blayney DW, Edge SB, Herman JG, Hudis 
CA, Marcom PK, Pettinga JE, Share D, Theriault R, Wong YN, Vandergrift JL, Niland 
JC, Weeks JC. Adoption of gene expression profile testing and association with use of 
chemotherapy among women with breast cancer. J Clin Oncol. 2012 Jun 
20;30(18):2218–2226. PMCID: PMC3397718 
5.  
O’Neill SC, Isaacs C, Chao C, Tsai HT, Liu C, Ekezue BF, Selvam N, Kessler 
LG, Schwartz MD, Lobo T, Potosky AL. Adoption of Gene Expression Profiling for 
Breast Cancer in US Oncology Practice for Women Younger Than 65 Years. J Natl 
Compr Canc Netw. 2015 Oct;13(10):1216–1224. PMCID: PMC4973473 
6.  
NCCN Clinical Practice Guidelines. Breast Cancer. Version 4.2024 [Internet]. 
Available from: https://www.nccn.org/professionals/physician_gls/pdf/breast.pdf 
7.  
Sparano JA, Paik S. Development of the 21-gene assay and its application in 
clinical practice and clinical trials. J Clin Oncol. 2008 Feb 10;26(5):721–728. PMID: 
18258979 
8.  
Richman AR, Tzeng JP, Carey LA, Retèl VP, Brewer NT. Knowledge of genomic 
testing among early-stage breast cancer patients. Psychooncology. 2011 Jan;20(1):28–35. 
PMID: 20200857 
9.  
Asad J, Jacobson AF, Estabrook A, Smith SR, Boolbol SK, Feldman SM, 
Osborne MP, Boachie-Adjei K, Twardzik W, Tartter PI. Does oncotype DX recurrence 
score affect the management of patients with early-stage breast cancer? Am J Surg. 2008 
Oct;196(4):527–529. PMID: 18809056 
10.  
Oratz R, Paul D, Cohn AL, Sedlacek SM. Impact of a commercial reference 
laboratory test recurrence score on decision making in early-stage breast cancer. J Oncol 
Pract. 2007 Jul;3(4):182–186. PMCID: PMC2793805 
11.  
Henry NL, Somerfield MR, Abramson VG, Ismaila N, Allison KH, Anders CK, 
Chingos DT, Eisen A, Ferrari BL, Openshaw TH, Spears PA, Vikas P, Stearns V. Role of 
Patient and Disease Factors in Adjuvant Systemic Therapy Decision Making for Early-
Stage, Operable Breast Cancer: Update of the ASCO Endorsement of the Cancer Care 
Ontario Guideline. J Clin Oncol. 2019 Aug 1;37(22):1965–1977. PMID: 31206315 
12.  
Sulayman N, Spellman E, Graves KD, Peshkin BN, Isaacs C, Schwartz MD, 
O’Neill SC. Psychosocial and Quality of Life in Women Receiving the 21-Gene 
Recurrence Score Assay: The Impact of Decision Style in Women with Intermediate RS. 
J Cancer Epidemiol. 2012;2012:728290. PMCID: PMC3413972 

PROTOCOL TITLE:  
Making Treatment Decisions Using Genomic Testing 
 
Page 15 of 15 
 
13.  
Street RL, Makoul G, Arora NK, Epstein RM. How does communication heal? 
Pathways linking clinician-patient communication to health outcomes. Patient Educ 
Couns. 2009 Mar;74(3):295–301. PMID: 19150199 
14.  
Lillie SE, Brewer NT, O’Neill SC, Morrill EF, Dees EC, Carey LA, Rimer BK. 
Retention and use of breast cancer recurrence risk information from genomic tests: the 
role of health literacy. Cancer Epidemiol Biomarkers Prev. 2007 Feb;16(2):249–255. 
PMID: 17267389 
15.  
Alegría M, Sribney W, Perez D, Laderman M, Keefe K. The role of patient 
activation on patient-provider communication and quality of care for US and foreign born 
Latino patients. J Gen Intern Med. 2009 Nov;24 Suppl 3:534–541. PMCID: 
PMC2764038 
16.  
Brown RF, Bylund CL, Li Y, Edgerson S, Butow P. Testing the utility of a cancer 
clinical trial specific Question Prompt List (QPL-CT) during oncology consultations. 
Patient Educ Couns. 2012 Aug;88(2):311–317. PMCID: PMC3376695 
17.  
Clayton J, Butow P, Tattersall M, Chye R, Noel M, Davis JM, Glare P. Asking 
questions can help: development and preliminary evaluation of a question prompt list for 
palliative care patients. Br J Cancer. 2003 Dec 1;89(11):2069–2077. PMCID: 
PMC2376858 
18.  
Eggly S, Tkatch R, Penner LA, Mabunda L, Hudson J, Chapman R, Griggs JJ, 
Brown R, Albrecht T. Development of a question prompt list as a communication 
intervention to reduce racial disparities in cancer treatment. J Cancer Educ. 2013 
Jun;28(2):282–289. PMCID: PMC3665702 
19.  
Holmes-Rovner M, Kroll J, Schmitt N, Rovner DR, Breer ML, Rothert ML, 
Padonu G, Talarczyk G. Patient satisfaction with health care decisions: the satisfaction 
with decision scale. Med Decis Making. 1996 Mar;16(1):58–64. PMID: 8717600 
20.  
Makoul G, Arntson P, Schofield T. Health promotion in primary care: physician-
patient communication and decision making about prescription medications. SocSciMed. 
1995;41(9):1241–1254.  
21.  
Elwyn G, Tsulukidze M, Edwards A, Légaré F, Newcombe R. Using a “talk” 
model of shared decision making to propose an observation-based measure: Observer 
OPTION 5 Item. Patient Educ Couns. 2013 Nov;93(2):265–271. PMID: 24029581 
22.  
Street RL, Tancredi DJ, Slee C, Kalauokalani DK, Dean DE, Franks P, Kravitz 
RL. A pathway linking patient participation in cancer consultations to pain control. 
Psychooncology. 2014 Oct;23(10):1111–1117. PMID: 24687847