Final Research Report

PATIENT-CENTERED OUTCOMES RESEARCH INSTITUTE FINAL RESEARCH REPORT

Contralateral Prophylactic Mastectomy and Breast Cancer: Clinical and Psychosocial Outcomes

Abenaa M. Brewster, MD, MHS1,; Susan Peterson, PHD, MPH1,; Scott Cantor, PhD1; Robert Volk, PhD1; Yu Shen, PhD1 ; Isabelle Bedrosian, MD, FACS 1; Herbert Dupont, MD1 Patricia Parker, PhD2

AFFILIATIONS: 1University of Texas MD Anderson Cancer Center, Houston 2Memorial Sloan-Kettering Cancer Center, New York, New York

PCORI ID: CE-1304-6293 HSRProj ID: 20143508 ClinicalTrials.gov ID: NCT02263014

______To cite this document, please use: Brewster AM, Peterson S, Cantor S, et al. (2018). Contralateral Prophylactic Mastectomy and Breast Cancer: Clinical and Psychosocial Outcomes. Patient-Centered Outcomes Research Institute (PCORI).

TABLE OF CONTENTS

ABSTRACT ...... 4 BACKGROUND ...... 6 Study Aim 1 ...... 6 Study Aim 2 ...... 8 Stakeholder Engagement ...... 10 Methodology Standards Adherence ...... 13 METHODS ...... 15 Study Aim 1 ...... 15 Analytic and Statistical Approaches ...... 18 RESULTS ...... 20 Study Sites ...... 20 Study Population ...... 20 Figure 1. CONSORT Diagram by Comparator Groups (no CPM and CPM) ...... 22 Demographic and Treatment Characteristics of Study Population by CPM Status ...... 23 Univariate and Multivariable Associations Between Demographic and Psychosocial Factors and Having CPM ...... 24 Table 1. Demographic and Treatment Characteristics of Study Population and by Contralateral Prophylactic Mastectomy Status ...... 25 Table 2. Univariate Analysis of Psychosocial Factors and Having Contralateral Prophylactic Mastectomy ...... 27 Table 3. Reduced Multivariable Model of Statistically Significant Demographic and Psychosocial Factors Associated With Having Contralateral Prophylactic Mastectomy (n = 224) ...... 27 Longitudinal Differences in Selected Psychosocial Variables by CPM Status ...... 27 Table 4. Longitudinal Assessment of Psychosocial Factors by Contralateral Prophylactic Mastectomy Status (n = 250)a ...... 29 Table 5. Effect of Contralateral Prophylactic Mastectomy Status on Psychosocial Factors Adjusted for Time Effect (Presurgery vs Postsurgery) (n = 250a) ...... 31 Specific Aim 2: Methods ...... 32 Probability Estimates ...... 33 Specific Aim 2: Results ...... 35 Table 6. Predicted Differences in Quality-Adjusted Life Expectancy by Degree of Family History of Breast Cancer for Having CPM Compared With Not Having CPM ...... 36

Table 7. Ten- and 20-year Overall and DFS Rate Differences by Degree of Family History of Breast Cancer for Having Contralateral Prophylactic Mastectomy Compared With Not Having Contralateral Prophylactic Mastectomy ...... 39 Figure 2. Boxplot Comparisons of Survival Outcomes ...... 41 Results for Risk-Prediction Tool ...... 43 DISCUSSION ...... 44 CONCLUSIONS ...... 48 REFERENCES ...... 49 APPENDIX ...... 54 Description of Contralateral Prophylactic Mastectomy Decision Support Tool ...... 54

ABSTRACT

Background: The majority of women diagnosed with breast cancer are at low risk of developing contralateral breast cancer; however, increasing numbers of women are choosing to have the cancer- free breast removed (contralateral prophylactic mastectomy [CPM]) in addition to the affected breast. The objective of the study was to examine the survival and psychosocial outcomes of women with unilateral breast cancer having CPM vs those not having CPM. The specific aims were to (1) prospectively examine the psychosocial outcomes of women with sporadic breast cancer having CPM vs those not having CPM, and (2) conduct a decision model to provide estimates of the effect of CPM on survival outcomes.

Methods: For study aim 1, we enrolled 308 women with newly diagnosed breast cancer before breast surgery at the MD Anderson Cancer Center and the Kelsey-Seybold community clinic between 2012 and 2015. Women completed validated questionnaires assessing psychosocial factors including quality of life (QOL), body image concerns, cancer worry, cancer distress, and decisional satisfaction at time points presurgery and at 1, 6, and 12 months postsurgery. We fitted repeated measures models to assess the association between psychosocial scores and CPM status, adjusting for time effect. For study aim 2, we developed a decision model to simulate the survival outcomes of women who undergo CPM and women who do not, considering age, stage, estrogen receptor (ER) status, and degree of family history of breast cancer. The results were used to develop an online risk-prediction tool.

Results of Study Aim 1: Among 252 women who completed presurgery and postsurgery questionnaires, mean age was 56 years (range, 25-82 years), 60% were non-Hispanic White, 16% were non-Hispanic Black, 16% were Hispanic, and 8% were of mixed race. Seventeen percent had CPM. Women who had CPM tended to be younger (P < .01) and Hispanic (P < .01). After adjusting for time effect (presurgery vs postsurgery), women who had CPM had higher scores for cancer distress (P = .03), body image concerns (P < .01), and QOL (P < .01) than did women who did not undergo CPM. There was no statistically significant difference by CPM status for decisional satisfaction.

Results of Study Aim 2: The decision model demonstrated that the greatest increase in quality- adjusted life expectancy with CPM was women aged 40 with an ER-negative, stage I breast cancer and a first- degree relative with breast cancer. CPM had no or a reduced effect on quality-adjusted life expectancy among women aged 50 or older regardless of stage or family history of breast cancer. The maximum 20-year absolute overall survival increase with CPM was 1.21%.

Conclusions: The results of study aim 1 suggest that psychosocial factors such as cancer distress, QOL, and body image concerns do not improve after having CPM. The results highlight the importance of evaluating women for these psychosocial factors presurgery and postsurgery in order to identify those for whom psychosocial assessment and counseling should be recommended. We will evaluate in a future study whether the risk prediction tool enhances a

woman’s understanding of the small survival benefit of CPM and whether that influences her decision about having CPM.

BACKGROUND Study Aim 1 We prospectively examined the psychosocial outcomes of women with sporadic breast cancer who had contralateral prophylactic mastectomy (CPM) vs those who did not. We also determined the impact of patient demographic and medical characteristics on the outcomes. We hypothesized that women who had CPM would have poorer psychosocial adjustment, including more cancer-specific distress, more cancer worry, and lower satisfaction than those who did not have CPM.

Introduction Breast cancer is the leading cause of cancer among women in the United States, estimated to affect approximately 231 840 women in 2016.1 The majority of patients in the United States (~93%) are diagnosed with operable disease and undergo surgical management of the affected breast, with either breast conserving surgery or mastectomy.2 Significant advances in screening and treatment have resulted in a 37% reduction in breast cancer mortality over the past decade.3 Among women with hormone-positive breast cancers, adjuvant treatment with tamoxifen or aromatase inhibitors reduces the risk of developing a contralateral breast cancer (CBC) by approximately 50%.4,5

For women diagnosed with unilateral breast cancer, a surgical option is the removal of the cancer-free breast (CPM) in addition to the affected breast. Despite the major achievements of treatments in reducing breast cancer mortality and CBC, the incidence of CPM among women with nonhereditary (sporadic) breast cancer has risen.6,7 The frequency of CPM is even higher among women seen at academic medical centers, and was estimated to be between 14% and 28% from 2006 to 2007.8-10 These higher-than-average annual rates of CPM at centers that offer multidisciplinary care reflect an increasing trend in the numbers of patients with sporadic breast cancer electing to undergo CPM and the availability of plastic surgery expertise for reconstruction. Our previous studies with breast cancer patients with sporadic disease showed that before meeting with their surgeons, 59% of women indicated they had at

least some interest in CPM.11 Hawley et al reported in a population-based survey of women from Detroit and Los Angeles that among women undergoing a mastectomy of their affected breast, 53% said that they considered CPM.12 Thus, this proposal’s topic affects the majority of women with stage I through III breast cancer.

Recent studies, including a prospective study conducted by our research team,11 have shown that the decision to have CPM is not entirely based on knowledge about survival outcomes and that psychosocial factors play a significant role in a woman’s decision whether to undergo CPM. Previous research that examined decision-making about women’s choice of mastectomy or breast conservation therapy for treatment of early-stage breast cancer has found that multiple factors influence women’s surgical decisions, including demographic characteristics (eg, age, race, marital status) and women’s own perceptions and values.13 Physicians have also been found to influence surgical decisions.14 A recent systematic review of 17 quantitative and qualitative studies explored patient-reported factors and psychological variables that influence the decision to have CPM; the studies included in the review were primarily cross-sectional and retrospective.15 Fear of breast cancer was the most common reason for having CPM, followed by a desire to have reconstructive symmetry.15 We previously conducted a prospective study of women with sporadic breast cancer and demonstrated that greater cancer worry was a significant predictor of interest in having CPM.11

An important gap in knowledge is how having CPM affects the psychosocial adjustment following surgery among women with sporadic breast cancer. These data are essential to provide women and their physicians with information about the long-term psychosocial impact of having CPM. The studies that have been conducted to date have been primarily retrospective,16-20 and they have included women who are BRCA1/2 mutation carriers, which puts these particular women at higher risk of contralateral breast cancer.21,22 Further, the lack of a prospectively followed control group in these studies limits the ability to ascertain whether CPM is associated with better or worse psychosocial outcomes.18,20,23

Prior studies have shed light on the concerns of women with unilateral sporadic breast cancer following CPM. Frost et al retrospectively collected data on a cohort of women who had

CPM from 1960 to 1993.24 The first questionnaire was administered to women, on average, 10.7 years and the second one 20.2 years after they received CPM. In this retrospective study, 90% of women were satisfied or very satisfied with their decision. Women who were dissatisfied reported adverse body image and adverse symptoms or complications.24 Of the sample, 54% reported adverse effects of CPM for 1 or more social or psychological domains; most adversely affected were body appearance, feelings of femininity, and sexual relationships. Importantly, all women in this cohort had a family history of breast cancer, and therefore the findings may not reflect the experiences of average-risk breast cancer patients. Hwang et al retrospectively surveyed women who had a history of breast cancer and reported that women in the CPM group had higher breast satisfaction and psychosocial well-being compared with women who did not have CPM.20 Rolnick et al examined what women wished they had known before prophylactic surgery (both women who had CPM and women who had bilateral prophylactic mastectomy) and found that more than 58% of women wished they had more information before having CPM—specifically about the potential for negative emotions following surgery.

Therefore, to provide essential information for informed, shared decision-making about CPM, we conducted an ethnically diverse, multicentered prospective study to examine the long- term patient-centered psychosocial outcomes of women with sporadic breast cancer who have had CPM vs those of women who have not undergone CPM.

Study Aim 2 We conducted a decision analysis model to estimate the effects of CPM on life expectancy and quality-adjusted life expectancy among women with sporadic unilateral breast cancer at varying risks of mortality from the index breast cancer, contralateral breast cancer, or other causes. We used the results of this model to develop an innovative online risk-prediction tool, designed to promote shared decision-making about CPM.

Background For each patient, the risk of developing contralateral breast cancer differs according to multiple clinical factors, such as her age at diagnosis, family history of breast cancer, risk of death from the primary breast cancer, and use of adjuvant endocrine therapy, which reduces the risk of contralateral breast cancer. The complexity of these factors poses a significant challenge to physicians who are asked to advise their patients about CPM and may lead patients to make decisions with incomplete information about their options. Indeed, studies have shown that the majority of women overestimate their risk of developing a contralateral mastectomy and cite a desire to improve survival or extend life as extremely important or very important reasons for choosing CPM.26

Observational studies comparing “CPM” or “No CPM” among women with sporadic breast cancer have been conducted to provide an estimate of CPM’s impact on breast cancer disease– free survival and overall survival benefit; however, selection bias, inadequate long- term follow- up, and residual confounding have contributed to mixed results.27-29 To overcome these limitations, decision analysis models have been developed for comparing CPM with surveillance only (no CPM) to inform outcomes of life expectancy, quality-adjusted life expectancy, and disease-free and overall survival.30,31 Portschy et al conducted a decision model of women with sporadic breast cancer and showed a less than 1% 20-year survival benefit due to CPM for patients with stage I breast cancer—and an even smaller benefit for patients with stage II breast cancer.30 However, the model did not take into account the survival benefit of CPM in relation to family history of breast cancer, which is an important consideration since epidemiologic studies have shown that the frequency of CPM is higher among women with a family history of breast cancer32,33 and women undergoing genetic testing even if they test negative for a mutation in BRCA1/2.8,34

To address this knowledge gap, we created a microsimulation model to assess the impact of CPM on quality-adjusted life expectancy as well as disease-free and overall survival for women with sporadic breast cancer, taking into consideration age at diagnosis, disease stage, estrogen receptor (ER) status, and degree of family history of breast cancer. The results

of the decision model were used to develop a risk-prediction tool for CPM. The goal of the tool is to provide a visual display showing the risk of developing contralateral breast cancer and of death with CPM vs no CPM, in order to aid informed decision-making about CPM.

Stakeholder Engagement This project developed from discussions with breast cancer patients who indicated that they felt overwhelmed and confused when trying to make their surgical decisions at the time of diagnosis. We conducted qualitative interviews with women at MD Anderson Cancer Center (MDACC) and Kelsey-Seybold (KS). For example, a woman who had CPM told us in an interview, “If I were to keep that breast, and—you know—fretting about it the whole 6 months [before each mammogram]—worrying myself sick—because I will!—I’ll worry myself sick.” Another woman, who was initially interested in CPM and then changed her mind after discussing the procedure with her surgeon, recapped this conversation: “I want to take them out—both. And then she [the surgeon] told me, no, that doesn’t work because your left one is good. Why take out something that is good? So, then she convinced me, and then I did only my one, the right one. And so I’m happy with that. I’m happy that I did not say, ‘Do the other one.’”

These examples from breast cancer patients demonstrate the complexity of surgical decisions and the concerns that many women have at the time of diagnosis. To understand whether patient decisions about CPM may be driven by fear and to evaluate patients’ psychosocial experiences after the surgery, it was essential to enroll women at the time of their breast cancer diagnosis and evaluate psychosocial factors both before and after surgery among women who had CPM and, as the comparison group, those who did not have CPM.

The stakeholders for the decision surrounding CPM are patients, spouses, and breast surgeons. We established a community advisory board (CAB) with representation from a diverse group of breast cancer advocates (Susan G. Komen Foundation, Pink Ribbons, Breast Health Collaborative of Texas, Reconstruction of a Survivor and Sister’s Network) and a community surgeon from the Texas Medical Association for guidance on the conduct of the study and dissemination of the study results. Patients were recruited from 10 different surgical practices at MDACC and KS, which demonstrates the engagement of the patient population and

surgeons in the study. Recently, we received an end-of-study survey from a patient who wrote on the survey’s front page, “Thanks, I enjoyed the journey.”

We conducted qualitative interviews of 20 patients (13 from MDACC and 7 from KS) who received a range of surgical procedures. Some women were very happy with their surgical decisions, whereas others described having regrets. For example, 1 woman indicated that she regretted not having CPM both because of cosmetic outcome and because she thought it might reduce her cancer worry. Some stated that they kept the news about their cancer mostly to themselves and their immediate family, whereas others discussed it widely with friends, bosses, and others. We also interviewed 10 spouses of enrolled patients (5 from MD Anderson and 5 from Kelsey-Seybold) to obtain their perspective. Generally, these spouses supported their wives’ treatment decisions. One spouse echoed what many patients stated—that they wanted to make sure the surgery would remove all the cancer, with an emphasis on minimizing risk of recurrence. A few spouses described the treatment process as easy and reported that their wives recovered quickly. Others, however, described the psychosocial difficulties that their wives had after the surgery. For example, 1 spouse indicated that his wife’s cancer experience “turned her into a whole different person” and that she became depressed and had lower self- esteem after diagnosis and treatment. Another spouse described his wife being very angry following the diagnosis (“Why me?”) and had difficulty looking in the mirror after surgery. We include additional responses in the results section of the report. These interviews enriched the quantitative information that was collected as part of the study.

The CAB, which met annually with the entire research team and communicated via emails with the study principle investigators (Drs. Brewster and Parker), played an important role in supporting the clinical relevance and conduct of the study. Members of the CAB expressed to the research team the importance of the research to their breast cancer community, and 1 of the CAB members, who herself had undergone CPM, freely shared her experiences in making the decision and after the surgery. Our Susan G. Komen representative on the CAB ensured that we received up-to-date information about the patient experience and regularly sent us links to newspaper articles about CPM. Although we provided study

participants with gift cards, we noticed delays in the turnaround time of the returned surveys. The CAB provided advice on additional, successful strategies to retain participants. We were advised to send the participants email reminders in addition to providing the gift cards at the time of survey completion. We incorporated these suggestions into the study design, and we added the option for patients to complete the questionnaires online via RedCap. We believe that this increased our questionnaire completion rates and that it was positively received by participants. In addition, the CAB recommended sending a thank-you letter to the participants, which we sent out in January 2016.

We relied on input from stakeholders to guide the selection of the end points that should be included in the decision tool that patients and providers care about and that guide informed decision-making. For example, the CAB and the surgeons were very interested in the tool showing the effect of CPM on CBC, risk of dying from breast cancer, and overall survival. We received feedback from the CAB that the text messages included in the tool appeared to support CPM, which was confusing to them; therefore, we tested other “take-home messages.” The surgeons’ feedback revealed that they wanted the tool to include information on quality- adjusted life expectancy, because this was clinically relevant to the decision-making process.

Our engagement with the surgeons and the CAB reinforced the importance of the study findings in guiding the discussion about CPM. The surgeons who reviewed the CPM decision tool indicated that they needed the information for clinical decision-making but felt it was premature to test the tool on patients who would be in the position to make real-time clinical decisions about CPM. We therefore hosted a booth at the Breast Health Summit in Texas in October 2016. There, we demonstrated the mockup version of the decision tool to breast cancer survivors who stopped by our booth, and we obtained their feedback. CAB members indicated that they wanted the final tool to include the findings of the psychosocial outcomes of CPM, as this information may be more meaningful to patients than the communication of CPM’s effect on CBC and survival. Although outside the scope of the current grant, expanding the tool to include the psychosocial outcomes obtained from study aim 1 will improve its patient-centered utility.

We disseminated study findings in several ways. We presented preliminary results of study aims 1 and 2 at scientific conferences—eg, American Society of Clinical Oncology (ASCO), American Association of Cancer Research, and Annual Puerto Rico Breast Cancer Conference— and at the Breast Health Collaborative of Texas General Membership Meeting. We published 2 manuscripts directly related to the project, and a third manuscript is in preparation. We will continue to work with members of the Center for Community-Engaged Translational Research at MDACC and our CAB to engage stakeholders and disseminate the study findings. For example, we presented the results of study aim 1 at the Susan G. Komen medical advisory board on May 2017, we submitted an abstract to the 2017 annual ASCO meeting, and the CAB has agreed to help us develop a newsletter that will describe the final research findings to the study participants.

Methodology Standards Adherence We followed the main methodology guidelines that are applicable for prospective cohort studies. In terms of formulating our questions, we identified gaps in the literature and obtained information by talking to breast cancer patients and a variety of oncology clinicians. It was clear that decision-making about CPM among women with sporadic cancer was an important health care decision for which there was considerable confusion and uncertainty. We used this information to develop the specific research aims for the project. Because most of the previous studies had been conducted at major academic centers, we included a community oncology setting in order to obtain a more representative sample. We based our outcome measures on the existing literature as well as the information provided by both patients and clinicians.

Because our research question emphasized the outcomes of women who did and did not have CPM, we utilized a variety of patient-reported outcome measures. From the beginning, we assembled and engaged our CAB, whose members provided important feedback at all phases of the study—from the initial implementation to the dissemination of study results.

Our study team, including our statisticians, developed methodology plans for data analysis before conduct of the study. During data collections, our research staff and investigators ensured that data were being collected appropriately and completely and that they were entered in secure databases. Throughout the study, we determined reasons for missing data, including dropout (lack of interest, too busy, etc) and those participants who were no longer eligible (eg, had surgery at another institution), and recorded that information in our tracking database (see CONSORT). We monitored the frequency of missing data at regular study team meetings and initiated online survey distribution as a means to improve the timeliness and collection of surveys. We engaged stakeholders throughout the conduct of the study and the dissemination of its results.

METHODS Study Aim 1 We prospectively examined the psychosocial outcomes of women with sporadic breast cancer who had CPM vs those who did not. We also determined the impact of patient demographic and medical characteristics on the outcomes. We hypothesized that women who had CPM would have more cancer-specific distress, more cancer worry, and lower satisfaction than those who did not have CPM.

Research Design We prospectively examined, using a mixed methods approach (ie, qualitative and quantitative), the psychosocial outcomes of women with sporadic breast cancer who had CPM vs those who did not.

Study Population Patients included women seen at The University of Texas MD Anderson Cancer Center (MDACC) or Kelsey-Seybold (KS) who met the following inclusion criteria: ductal carcinoma in situ or stage I through III newly diagnosed sporadic unilateral invasive breast cancer; over age 18; and able to speak, read, and write in English. Patients with previous breast cancer or a history of prophylactic mastectomy or those who were known to have a germline gene mutation that predisposed them to an increased risk of breast cancer (eg, BRCA1, BRCA2), and/or those who were considered at high risk for contralateral breast cancer on the basis of a strong family history of cancer, were excluded. Spouse/partner eligibility were the following: married or living with partner for at least 1 year; 18 years or older; able to speak, read, and write in English.

Recruitment and Study Procedures Potential participants were identified through clinic schedules and were recruited at their initial surgeon’s appointment at MDACC. For the KS site, potential participants were identified through clinic schedules and were recruited either at their initial surgeon’s visit, if

coming in with a known breast cancer diagnosis, or at a subsequent appointment at KS, or at a scheduled research appointment with a KS staff member. Patients completed questionnaires at 4-time points: baseline (around the time of study enrollment) and approximately 1, 6, and 12 months following their surgery for breast cancer. To compensate them for their time and effort, participants received a $20 gift card after completing the study questionnaire at each time point.

To supplement the quantitative data collected, we conducted semistructured interviews with 20 women from both sites to evaluate these patients’ perspectives on their surgical decision-making and how their diagnosis and treatment had affected their lives. Semistructured, in- depth interviews can provide a rich and detailed set of data about perceptions, thoughts, and impressions in an individual’s own words.35 We also interviewed 10 spouses/partners of breast cancer patients and 6 physicians to obtain their perspectives.

Study Measures Background information. Participants completed demographic information (ie, age, race, ethnicity, marital status, education, and occupation). Medical variables (stage, chemotherapy treatment, type of surgery, and ER and progesterone receptor [PR] status) were collected from patients’ charts).

Breast cancer and treatment knowledge. We assessed participant knowledge about breast cancer and treatment with an 11-item multiple choice scale developed by Street et al, which has been used with early-stage breast cancer patients.36 We added 5 items that assess knowledge about CPM.

Cancer-specific distress. We measured cancer-specific distress with the Revised Impact of Events Scale (IES). The IES assesses 2 common categories of responses to stressful events— intrusion and avoidance—and has good internal consistency reliability (0.70-0.85).37

Breast Cancer Worry Scale. We assessed breast cancer worry with a 4-item scale developed by Lerman et al, which assesses the extent to which worry about breast cancer interferes with women’s daily functioning.38

Trust in the Physician Scale. The Trust in the Physician Scale is an 11-item scale that assesses a patient’s perception about the level of trust he or she has in his or her physician. It has been shown to have good psychometric properties.38,39

Body image. We assessed body image with the Body Image Scale, a 10-item measure that was developed to assess body image in individuals with cancer. It has been shown to be sensitive to change and to have good psychometric properties.40

Quality of life. The Functional Assessment of Cancer Therapy Breast assesses physical, social, emotional, and functional well-being as well as additional concerns of women with breast cancer.41

Decisional Conflict Scale. We assessed decisional conflict with a 16-item scale that assesses personal perceptions of uncertainty in choosing options, modifiable factors contributing to uncertainty, and effective decision-making.43

Satisfaction With Decision Scale. This scale measures women’s satisfaction with their surgery decision.44 It has been used with a variety of health care decisions and has been shown to have good reliability and validity.44 We administered it to participants at 1, 6, and 12 months postsurgery.

Qualitative Interviews We purposively selected a subsample of 20 women from those who did and did not undergo CPM to ensure that the sample was balanced in regard to age, ethnicity, and clinical characteristics (eg, disease stage). These women were asked to complete semistructured interviews that assessed their perspective on why they chose their surgical options and that asked about quality of life (QOL) issues. Specifically, we asked women about their surgery

decisions (with or without CPM) and how their breast cancer and its treatment have influenced their lives in a variety of domains (eg, sense of self, body image, sexuality, worry, social relationships). We also interviewed 10 spouses/partners of breast cancer patients to obtain their perspectives on the decision-making process and their thoughts and feelings about CPM. Finally, we interviewed a sample of physicians (n = 6) to learn about their perspectives on treating patients with breast cancer who do and do not have CPM, their decision-making process with the patient regarding CPM, and how breast cancer and its treatment appears to influence their lives; we also asked them to identify, from their perspective, what the salient issues are for their patients. We recruited these patients and physicians from both study sites.

All semistructured interviews for patients, spouses/partners, and physicians were audio recorded. Interview recordings were professionally transcribed verbatim for analysis. Each transcript was validated by the staff person who conducted the interview to ensure accurate and complete transcription.

Analytic and Statistical Approaches We report frequencies and percentages for categorical variables. We provide summary statistics such as number of nonmissing observations (N), mean, median, standard deviation, minimum, and maximum for continuous data. We used the chi-square test and Fisher’s exact test to evaluate the association between categorical variables and CPM status. We used Wilcoxon’s rank sum test to compare the distributions of continuous variables (such as psychosocial scores at each time point) between the CPM and non-CPM groups. We used the Kruskal-Wallis test compare the distributions of psychosocial scores among different time points. We used a univariate logistic regression model to examine the association between baseline psychosocial scores and CPM status. We used a multivariable logistic regression model to examine the association between demographic characteristics, screen variables, treatment options, and psychosocial scores and CPM status. We performed the multivariable logistic regression analysis by first including all variables with P < .10 in univariate analyses. We then performed a backward stepwise selection method by removing the variable with the highest P value in the multivariable model (least contribution to the model) at each step. We performed

the multivariable analysis again with remaining variables, and we excluded the variable with the least contribution to the model. We repeated this process until all variables that remained in the model had a significant P value (< .05). Because the goal of this study was to identify variables that were significantly associated with the outcome—rather than building a prediction model, as is common practice—we excluded all variables that were insignificantly associated with the outcome variable. We fitted repeated measures models to assess the association between psychosocial scores and CPM status over different time points (presurgery, 1 month postsurgery, 6 months postsurgery, and 12 months postsurgery). All tests were 2 sided. We considered P values less than .05 to be statistically significant. We conducted all analyses using SAS 9.4 (SAS) software.

Qualitative Analyses We analyzed transcriptions of the semistructured interviews (with Atlas.Ti qualitative analysis software) using a content analysis approach to identify major and minor themes of interest. We first reviewed transcripts of interviews with patients, spouses/partners, and physicians to get an overall sense of meaning. We identified meaningful and recurrent themes; we then developed coding categories and organized the codes to form organized and meaningful clusters. Two individuals coded the transcripts. After the final qualitative and quantitative analyses were completed, we used a triangulation procedure to link the 2 approaches. We analyzed data with appropriate techniques (content analysis of the qualitative data and statistical analysis conducted on quantitative measures). We compared the major themes over time against the quantitative factors to enhance our understanding of the factors associated with various patterns.

RESULTS Study Sites To enhance generalizability and racial diversity of the study, we recruited participants from 2 types of medical settings: a comprehensive cancer center and a community clinic. The University of Texas MD Anderson Cancer Center (MDACC) is 1 of 47 National Cancer Center– designated Comprehensive Cancer Centers. The Nellie B. Connally Breast Center at the MDACC consists of a multidisciplinary team of 22 breast medical oncologists and 15 breast surgeons who evaluate and treat approximately 2400 newly diagnosed breast cancer patients annually. The race/ethnicity distribution of breast cancer patients at MDACC is 80% Caucasian, 9% Hispanic, and 7% Black. The Kelsey-Seybold Community Clinic (KS) is a large multispecialty medical organization that provides care to an ethnically diverse population of approximately 350 000 patients at 21 clinics in Houston, Texas. The clinic offers physician services in 34 medical specialties and subspecialties (hematology/oncology, surgery) and has more than 2.1 million patient visits annually. Each year, 350 newly diagnosed breast cancers are centrally referred to a multidisciplinary Breast Center at its main campus (2 to 3 miles from MDACC) for management. The Breast Center at KS has 6 medical oncologists and 4 surgeons. The race/ethnicity distribution of breast cancer patients at KS is 56% Caucasian, 14% Hispanic, and 27% Black.

Study Population A total of 465 eligible women were approached for this study at MDACC and KS (Figure 1). Of these, 345 (85%) agreed to participate and signed informed consent (245 at MDACC and 100 at KS). The reasons women provided for refusal of participation were too busy (n = 21), not interested (n = 23), too overwhelmed with diagnosis of breast cancer (n = 11), and other reasons (n = 7). The comparator groups were women who had CPM and women who did not have CPM. Before its completion, 27 patients withdrew from the study, including 3 women who died and 1 woman who developed a distant metastatic recurrence. We excluded from the study analysis 37 women who were subsequently determined ineligible for participation (reasons: BRCA1/2 carrier [n = 6], no breast surgery performed [n = 3], no breast surgery at institutions [n

= 22], metastatic disease at diagnosis [n = 6]) and 56 women who did not complete the baseline (presurgery) assessment. Therefore, we included 252 women in the study analysis (163 MDACC and 89 KS), and we used data from the survey assessments up to the date of study withdrawal, study completion, or database closure for the analysis of this final draft report (October 18, 2016), whichever occurred first.

Figure 1. CONSORT Diagram by Comparator Groups (no CPM and CPM)

Abbreviation: CPM, contralateral prophylactic mastectomy.

Demographic and Treatment Characteristics of Study Population by CPM Status Among participants, mean age was 56 years (range, 25-82 years), 60% were non- Hispanic White, 75% were married or living with a partner, 50% had completed college or higher, and 58% were employed full or part time (Table 1). Twenty-five percent reported having a family history of some type of cancer (including breast cancer [women with multiple first- degree relatives with breast cancer were not included in this study]); 19.4% had ductal carcinoma in situ; 36.5% had stage I, 36.9% stage II, and 7.2% stage III disease. Most women (82%) had ER+/PR+ breast cancers. Fifty-five percent had segmental mastectomy, 27% had unilateral mastectomy, and 17.5% had CPM (4 women had CPM ≥ 6 months after their primary breast cancer surgery). Of the women who had CPM, 79% had immediate reconstruction, and 20% of the women who had unilateral mastectomy had immediate reconstruction. Women who had CPM were also were more likely to be younger (P < .01) and Hispanic (P < .01) (Table 1).

Univariate and Multivariable Associations Between Demographic and Psychosocial Factors and Having CPM The psychosocial variables collected presurgery that were significantly associated with having CPM in the univariate analysis were higher distress (P = .05), higher cancer worry (P < .001), more body image concerns (P < .0001), and lower QOL (P = .02; Table 2). In the multivariable model adjusted for age and ethnicity, the factors that remained statistically significantly associated with having CPM were Hispanic ethnicity (P < .01), higher cancer worry (P = .01), more body image concerns (P < .01), and higher QOL (P = .04; Table 3).

Table 1. Demographic and Treatment Characteristics of Study Population and by Contralateral Prophylactic Mastectomy Status

Total population CPM No CPM Variable (N = 252) (n = 44) (n = 208) P valuea Age at diagnosis, mean 56.3 (25-82) 50.9 (30-75) 57.4 (25-82) <.01 (range), y Race/ethnicity, % <.01 Non-Hispanic White 144 40.9 60.6 Non-Hispanic Black 37 9.1 15.9 Hispanic 38 31.8 11.5 Other 20 11.4 7.2 Missing data 13 6.8 4.8 Education, % .89 Less than high school 7 2.3 2.9 High school/some 115 47.7 45.2 college College/graduate 123 45.5 49.5 Missing data 7 4.5 2.4 Marital status, % .61 Married/living with 185 75.0 73.1 partner Single/divorced 60 20.5 24.5 Missing data 7 4.5 2.4 Annual income, % .83 ≤30 000 48 20.5 18.8 30 000-75 000 80 29.5 32.2 >75 000 101 34.1 41.3 Missing data 23 15.9 7.7 Family history of cancer, .35 % Yes 63 29.5 24.0 No 181 63.6 73.6 Missing data 8 6.8 2.4 Genetic testing, % 1.00 Yes 23 9.1 9.1 No 149 56.8 59.6 Missing data 80 34.1 31.3

Total population CPM No CPM Variable (N = 252) (n = 44) (n = 208) P valuea History of cancer, % .79 Yes 27 11.4 10.6 No 217 84.1 86.5 Missing data 8 4.5 2.9 Stage, % .44 0 49 25.0 18.3 I 92 38.6 36.1 II 92 27.3 38.4 III 18 9.1 6.7 Missing data 1 - 0.5 Hormone receptor status, .93 % ER and PR negative 44 25.0 15.8 ER and/or PR positive 206 72.7 83.7 Missing 2 2.3 0.5 Type of surgery, % <.01 Bilateral mastectomy 44 100 0 Unilateral mastectomy 68 0 32.7 Breast conserving 140 0 67.3 Chemotherapy, % .82 Yes 122 50.0 48.1 No 130 50.0 51.9 Breast reconstruction, % <.01 Yes 76 79.5 19.7 No 176 20.5 80.3 Abbreviations: CPM, contralateral prophylactic mastectomy; ER, estrogen receptor; PR, progesterone receptor. aP value by chi-square or Fisher exact for comparison of CPM and no CPM.

Table 2. Univariate Analysis of Psychosocial Factors and Having Contralateral Prophylactic Mastectomy

Variable Odds ratio 95% CI Cancer distress (per unit increase) 1.01 0.99-1.03 Cancer worry (per unit increase) 1.21 1.09-1.34a Body image (per unit increase) 1.11 1.06-1.16a Quality of life (per unit increase) 0.98 0.96-0.99a Decisional uncertainty (per unit increase) 0.99 0.98-1.01 aP < .05.

Table 3. Reduced Multivariable Model of Statistically Significant Demographic and Psychosocial Factors Associated With Having Contralateral Prophylactic Mastectomy (n = 224)

Variable Odds ratio 95% CI Race Non-Hispanic White 1.0 0.33-3.87 Non-Hispanic Black 1.14 1.85-12.21 Hispanic 4.76 0.69-8.51 Other 2.42 Cancer worry (per unit increase) 1.19 1.03-1.37 Body image (per unit increase) 1.13 1.05-1.23 Quality of life (per unit increase) 1.03 1.00-1.06

Longitudinal Differences in Selected Psychosocial Variables by CPM Status The mean scores of the selected psychosocial factors presurgery, 1 month postsurgery, 6 months postsurgery, and 12 months postsurgery for the study participants by CPM status are shown in Table 4. Women who had CPM had statistically significant higher distress scores than those of women who did not have CPM presurgery (29.98 vs 24.62; P = .04), 6 months (23.43 vs 18.56; P = .03), and 12 months (25.30 vs 17.01; P = .01) postsurgery (Table 4). Women who had CPM had statistically higher mean scores for cancer worry compared with those of women who did not have CPM presurgery (9.49 vs 7.74; P < .01) but then had statistically significant lower

cancer worry at 1 month postsurgery (P < .01). There was no difference in cancer worry between women who had CPM and those who did not at 6 months (P = .38) and 12 months (P = .73) postsurgery. Women who had CPM had statistically significantly higher scores on the measure of body image concerns presurgery (8.15 vs 3.41; P < .01) and at 1 month (14.73 vs 6.95; P < .001), 6 months (13.97 vs 7.31; P < [value missing], and 12 months (14.33 vs 6.40; P < .001) postsurgery compared with women who did not have CPM. Women who had CPM had a statistically significantly lower QOL compared with women who did not have CPM presurgery (106.17 vs 112.62; P = .20) and 1 month (94.39 vs 109.73; P < .01), 6 months (101.1 vs 109.53; P = .05), and 12 months (101.56 vs 113.56; P = .01) postsurgery. There was no significant difference by CPM status for cancer knowledge, decisional satisfaction, or decisional conflict presurgery or postsurgery.

We fitted repeated measures models to assess the association between psychosocial scores and CPM status adjusting for time effect. After adjusting for time effect (pre- vs postsurgery), patients who had CPM had statistically significantly higher distress scores (P = .03) and more body image concerns (P < .0001) than those of women who did not have CPM (P = .02; Table 5). We investigated for an interaction between time and CPM status for each of the psychosocial factors, and the interaction between CPM status and time was significant only for cancer worry (P for interaction < .0001; data not shown).

Table 4. Longitudinal Assessment of Psychosocial Factors by Contralateral Prophylactic Mastectomy Status (n = 250)a

Presurgery 1 Month Postsurgery 6 Months Postsurgery 12 Months Postsurgery CPM Variable Status n Mean (SE) P value n Mean (SE) P value n Mean (SE) P value n Mean (SE) P value Cancer No 207 24.62 .04 189 19.84 .42 196 18.56 .03 169 17.01 .01 distress (16.52) (14.8) (16.11) (14.79) Yes 42 29.98 38 21.84 40 23.43 33 25.3 (16.77) (14.58) (14.69) (17.26) Cancer worry No 207 7.74 <.01 189 6.63 <.01 194 6.24 .39 169 6.09 .73 (2.94) (2.36) (2.3) (2.09) Yes 41 9.49 37 5.95 37 5.86 32 6.28 (3.46) (3.14) (2.02) (3) Body image No 196 3.4 <.01 187 6.95 <.001 196 7.31 <.001 168 6.4 <.001 (4.91) (7.22) (7.3) (6.5) Yes 41 8.15 37 14.73 39 13.97 33 14.33 (8.92) (8.59) (9.3) (7.75) Quality of life No 204 112.62 .20 187 109.73 <.01 195 109.53 .05 170 113.56 .01 (17.73) (18.88) (20.22) (18.83) Yes 42 106.17 36 94.39 40 101.1 32 101.56 (24.32) (23.88) (25.38) (25.99) Satisfaction No - 187 4.27 .62 192 4.33 .70 168 4.34 .99 with decision (0.81) (0.76) (0.75) Yes 38 4.23 39 4.18 32 4.35 (1.08) (1.06) (0.86) Decisional No 204 22.4 .67 187 19.11 .77 193 18.51 .96 167 18.55 .44 conflict (19.24) (17.62) (17.96) (18.9)

Presurgery 1 Month Postsurgery 6 Months Postsurgery 12 Months Postsurgery CPM Variable Status n Mean (SE) P value n Mean (SE) P value n Mean (SE) P value n Mean (SE) P value Yes 42 19.71 38 18.17 39 19.77 33 14.82 (15.22) (19.49) (21.64) (16.18) Abbreviation: CPM, contralateral prophylactic mastectomy. aTwo patients who had delayed CPM were removed from the analysis.

Table 5. Effect of Contralateral Prophylactic Mastectomy Status on Psychosocial Factors Adjusted for Time Effect (Presurgery vs Postsurgery) (n = 250a)

CPM vs no CPM, Variable estimate (SE) P value Cancer distress 4.86 (2.19) .03 Cancer worry 0.22 (0.36) .54 Body image 6.42 (1.22) <.01 Quality of life –9.33 (3.56) <.01 Decisional uncertainty –1.91 (2.51) .45 Abbreviation: CPM, contralateral prophylactic mastectomy. aTwo patients who had delayed CPM were removed from the analysis.

Qualitative Results Key themes that we identified regarding reasons for choosing treatments included CPM, dealing with uncertainty, cancer worry, and concerns about recurrence. Women who had CPM indicated that their choice allowed them to have peace of mind even though they were told the statistics on having a new cancer in the opposite breast. For example, a woman who had CPM stated, “I know statistically—they’ve showed me stuff that it doesn’t matter—but for my peace of mind, that’s why I chose that way.” Another woman who had CPM stated, “We have no family history, and there was no precursor to why it happened to me, you know. It was out of the blue. And I decided that I don’t want to go through this again, so I told him, ‘I don’t want markers. I just want to take them both out. Just take them both.’” Another reason women stated for having CPM was to feel like they had done everything they could for their cancer. For example, a woman who had CPM stated, “I’ll take everything out there available . . . if something did happen later, no regrets. You know, it’s like, ‘No, I did anything and everything. . . . But if it will save my life . . . then I want it. I want everything.’” These sentiments were echoed by the physicians for reasons why they believe women request CPM. For example, a plastic surgeon stated, “I think a lot of it is peace of mind almost. Like they don’t want . . . to always be wondering. What am I feeling? Is this a lump? They don’t want to have to have a mammogram every 6 months or every year. They’re worried if they’ve had cancer in 1 breast.

Will it come back? Will it affect the other side 5 years from now? Ten years from now, could this happen?” Cancer worry was commonly reported among women regardless of the treatment they had. For some women, they reported having less cancer worry following CPM, whereas others wondered if there was something else they should be doing to check for cancer recurrence. A woman who had CPM stated, “I don’t have any more breast[s] . . . but I know the tissue may be in there . . . I do worry, and I’m thinking maybe I have cancer somewhere else, you know, not just the breast.” A woman who had a mastectomy reported, “Yes, I do. I think about it . . . returning. You know, that’s something that, I guess before you get your mammograms every 6 months or whatever, that you’re going to continue to worry about for a while—well, forever probably.” A spouse also indicated that his wife had a great deal of worry: “Oh, yeah. She worries a lot. It’s always on her mind.”

For some women, they trusted their surgeon to make the best decision about treatment options: “Whatever he was going to say is what I was going to do.” Another woman stated, “And because of the aggressive . . . cancer that it was and the size of the tumor, once I got to MD Anderson and met with the surgeon there, she informed me that the mastectomy would probably be the best option. So, I immediately agreed with her. You know, I trusted her and if that’s what she recommended, then that’s what I was going to go with.” Other women knew their surgery decision from the beginning. For example, on women stated, “Yes. It was mainly me. I just told them what I was going to do.”

Specific Aim 2: Methods

Model Structure We developed an individual-level state transition model to simulate the long-term survival outcomes of women who undergo CPM and women who do not following a unilateral mastectomy or breast-conserving surgery of the primary breast cancer.45 The model assumes a population of women with early-stage breast cancer without a hereditary breast cancer syndrome. We conducted our analysis over a lifetime horizon, beginning at age 40, 50, 60, or 70 following treatment of the primary cancer. We assumed that patients received equivalent,

standard treatment for the primary breast cancer in the CPM and non-CPM strategies. We identified possible strategies for the management of women following treatment of a primary nonhereditary breast cancer, considered potential outcomes that might follow those actions, and identified the probabilities and preferences for those outcomes. Each year, after treatment, the women may remain in a cancer-free (survivor) state, die of the primary cancer, develop CBC, or die of other causes. The risk of CBC was incorporated into a 10-year period from the time of initial treatment. We then synthesized the information to determine the life expectancy and quality-adjusted life expectancy of the strategies. We presented results for the various combinations of attributes that may factor in the differences of survival and quality- adjusted survival, including cancer stage, age, ER status, and family history. We determined 10- and 20-year overall and disease-free survival rates by estimating life expectancy and disease- free life expectancy, respectively, over the corresponding time periods. We created the model using the decision analysis software TreeAge Pro 2014 (TreeAge Software).

Probability Estimates Our model incorporated annual breast cancer–specific mortality rates extrapolated from 10- year disease-specific risks of death for patients with stage I through III cancers that were derived from the relative survival curves in the Surveillance, Epidemiology, and End Results database as presented in Portschy et al.30 We obtained age-specific mortality rates from US life tables.46 We converted data on incidence of CBC from the Early Breast Cancer Trialists’ Collaborative Group to annual probabilities resulting in 0.4% and 0.5% annual risks of developing CBC for ER-positive and ER-negative patients, respectively.4 We estimated the risks of CBC according to family history from a population-based case control study of women without BRCA mutation who had a primary breast cancer, in 4 US cancer registries.47 We derived the stage distribution of a CBC among women diagnosed with a previous breast cancer from a study of the Oregon State Cancer Registry database by Quan et al.48 The risk of death associated with a CBC was estimated to be the same as the risk of death associated with a primary cancer of the same stage and was added to the risk associated with the primary breast cancer.

Utility Estimates We incorporated QOL for each health state using estimates of utilities reported in the literature,49,50 and we measured the impact of each treatment strategy in quality-adjusted life years (QALYs). We identified 2 primary health states: unilateral mastectomy or breast- conserving surgery (no CPM) and bilateral mastectomy involving CPM for which utility adjustments needed to be made.45 We assumed the initial utility of unilateral mastectomy or breast-conserving surgery to be 0.90 and the initial utility of bilateral mastectomy to be 0.70, because of the greater initial postsurgery disutility associated with bilateral mastectomy. If no CBC developed in years 2 to 5 after surgery, we assumed the utilities to be 0.79 for both health states; beyond year 5, we assumed the utility for both health states to be 0.84. If a CBC developed, the utility value was lowered to 0.73 for 2 years following the CBC diagnosis.

Between years 2 and 5, the utility value for the CBC health state was increased to 0.79. As with the primary (no-CBC) health state, this value was increased to 0.84 beyond year 5.

Sensitivity Analysis We conducted a sensitivity analysis of base case parameter estimates of reductions in the risk of developing CBC after CPM. We established the variable means and ranges on the basis of published estimates (Table 1 in Davies et al). In our sensitivity analysis, we used a CBC risk reduction in the range of 75% to 100% for each degree of family history. To perform a sensitivity analysis on the utility values, we conducted the sensitivity analysis of CBC risk and CPM-associated risk reduction with the utility associated with each health state set to 1 (ie, no health decrements in the model), resulting in life expectancy as the outcome.45 Refer to Table 1 in the published manuscript (Davies et al) for the base case probabilities, utilities, and ranges used in the sensitivity analysis.45

Specific Aim 2: Results

Effect of CPM on Life Expectancy by Degree of Family History of Breast Cancer CPM had an overwhelmingly minimal to negative QALY benefit for women aged 60-70 with stage I through III disease and no family history of breast cancer.45 Women aged 70 and older with stage III disease had a negative benefit from CPM regardless of degree of family history of breast cancer. Women aged 40-50 with a first-degree relative with breast cancer tended to have a positive benefit with CPM; however, the benefit was minimal to negative for those with either no or a second-degree family history, stage III disease, or ER-positive disease. For the 40- to 70-year age range, the benefit of CPM compared with no CPM ranged from –0.08 to 0.12 QALYs for women with no family history of breast cancer, from –0.07 to 0.17 QALYs for women with only a second-degree relative with breast cancer, from –0.06 to 0.31 QALYs for women with a first-degree relative with unilateral breast cancer, and from –0.02 to 0.65 QALYs for women with a first-degree relative with bilateral breast cancer (Table 6).

Table 6. Predicted Differences in Quality-Adjusted Life Expectancy by Degree of Family History of Breast Cancer for Having CPM Compared With Not Having CPM

Quality-adjusted life years Breast cancer in a first-degree relative Patient and disease Breast cancer in a characteristics No family history second-degree relative Unilateral Bilateral ER Age, y status Stage No CPM CPM D No CPM CPM D No CPM CPM D No CPM CPM D 40 Positive I 34.61 34.70 0.09 34.56 34.70 0.14 34.45 34.70 0.25 34.16 34.68 0.52 40 Negative I 34.48 34.60 0.12 34.43 34.60 0.17 34.28 34.59 0.31 33.92 34.57 0.65 40 Positive II 27.42 27.45 0.03 27.38 27.45 0.07 27.28 27.44 0.16 27.04 27.43 0.40 40 Negative II 27.33 27.41 0.08 27.28 27.41 0.13 27.18 27.40 0.23 26.89 27.39 0.50 40 Positive III 15.45 15.42 –0.03 15.42 15.42 0.00 15.38 15.41 0.03 15.28 15.41 0.14 40 Negative III 15.36 15.36 0.01 15.33 15.36 0.03 15.27 15.36 0.09 15.12 15.34 0.22 50 Positive I 26.92 26.97 0.05 26.88 26.97 0.09 26.79 26.96 0.17 26.58 26.95 0.38 50 Negative I 26.94 27.03 0.09 26.89 27.03 0.14 26.78 27.02 0.25 26.52 27.01 0.49 50 Positive II 21.65 21.66 0.02 21.62 21.66 0.05 21.55 21.66 0.11 21.38 21.65 0.27 50 Negative II 21.61 21.65 0.05 21.57 21.65 0.09 21.50 21.65 0.15 21.29 21.63 0.34 50 Positive III 12.57 12.52 –0.05 12.55 12.52 –0.03 12.52 12.52 0.00 12.43 12.52 0.08 50 Negative III 12.53 12.49 –0.04 12.51 12.49 –0.02 12.47 12.49 0.02 12.36 12.49 0.13 60 Positive I 19.85 19.84 –0.01 19.82 19.84 0.01 19.76 19.83 0.07 19.61 19.83 0.21 60 Negative I 19.87 19.88 0.01 19.83 19.88 0.05 19.76 19.88 0.12 19.58 19.87 0.28

Quality-adjusted life years Breast cancer in a first-degree relative Patient and disease Breast cancer in a characteristics No family history second-degree relative Unilateral Bilateral ER Age, y status Stage No CPM CPM D No CPM CPM D No CPM CPM D No CPM CPM D 60 Positive II 16.12 16.10 –0.02 16.10 16.10 0.00 16.06 16.10 0.04 15.93 16.09 0.17 60 Negative II 16.17 16.15 –0.02 16.15 16.15 0.00 16.10 16.15 0.05 15.97 16.14 0.17 60 Positive III 9.88 9.82 –0.06 9.87 9.81 –0.05 9.84 9.81 –0.03 9.78 9.81 0.03 60 Negative III 9.80 9.76 –0.04 9.79 9.76 –0.03 9.75 9.76 0.01 9.68 9.75 0.07 70 Positive I 13.38 13.34 -0.05 13.37 13.34 –0.03 13.33 13.33 0.00 13.25 13.33 0.08 70 Negative I 13.34 13.30 –0.03 13.32 13.30 –0.02 13.28 13.30 0.02 13.18 13.29 0.11 70 Positive II 11.18 11.12 –0.06 11.16 11.12 –0.05 11.13 11.12 –0.01 11.06 11.12 0.05 70 Negative II 11.18 11.13 –0.05 11.16 11.13 –0.03 11.12 11.13 0.01 11.03 11.12 0.09 70 Positive III 7.24 7.16 –0.08 7.24 7.16 –0.07 7.22 7.16 –0.06 7.18 7.16 –0.02 70 Negative III 7.24 7.17 –0.07 7.23 7.17 –0.06 7.22 7.17 –0.05 7.18 7.17 –0.01 Abbreviations: D, difference (CPM − no CPM); CBC risk reduction = 95% (base case); CPM, contralateral prophylactic mastectomy; ER, estrogen receptor.

Effect of CPM on CBC, Overall Survival, and Disease-Free Survival by Degree of Family History of Breast Cancer For all age groups, the greatest reduction in the range of the rates of CBC as a result of CPM occurred in women with a higher degree of family history and with ER-negative tumors.45 The maximum 10-year absolute overall survival rate benefit for CPM vs no CPM was 0.36% for women with no family history of breast cancer, 0.46% for women with only a second-degree relative with breast cancer, 0.69% for women with a first-degree relative with unilateral breast cancer, and 1.21% for women with a first-degree relative with bilateral breast cancer (Table 7; Figure 2). For example, a woman aged 50 with a ER-positive, stage II breast cancer, and a family history of a first-degree relative with breast cancer would have a 0.2% improvement in her 10- year disease-free survival if she had CPM vs if she did not have CPM. The maximum 20-year absolute disease-free survival rate benefit for CPM vs no CPM was 3.73% for women with no family history of breast cancer, 4.76% for women with only a second-degree relative with breast cancer, 6.97% for women with a first-degree relative with unilateral breast cancer, and 12.59% for women with a first-degree relative with bilateral breast cancer (Table 7; Figure 2).

For example, a 60-year-old woman with a stage I, ER-negative breast cancer with no family history of breast cancer would have a 0.3% improvement in her overall survival at 20 years if she had CPM compared with if she did not have CPM.

Development of Risk-Prediction Model We contracted with E-Health Technology at MDACC to create a web-based risk- prediction application based on a patient’s profile (age, ER/PR status, stage, family history) to demonstrate future risk of contralateral breast cancer and survival outcomes with or without CPM using outputs from the microsimulation model developed in study aim 2. Outputs for the risk prediction tool were derived by entered inputs and assessed from an 864 × 14 Excel spreadsheet that contained 10 columns with each of the 864 rows corresponding to a unique patient scenario.

10- and 20-year absolute OS and DFS rate difference, % Breast cancer in a first-degree relative Patient and Disease Breast cancer in a second- Characteristics No family history degree relative Unilateral Bilateral ER 10-y, 20-y 10-y, 20-y 10-y, 20-y 10-y, 20-y 10-y, 20-y 10-y, 20-y 10-y, 20-y 10-y, 20-y Age, y status Stage OS, D% DFS, D% OS, D% DFS, D% OS, D% DFS, D% OS, D% DFS, D% 40 Positive I 0.09 0.29 1.79 2.97 0.12 0.36 2.31 3.81 0.18 0.54 3.42 5.61 0.32 0.96 6.28 10.24 40 Negative I 0.12 0.35 2.22 3.73 0.14 0.43 2.83 4.76 0.21 0.65 4.18 6.97 0.43 1.21 7.74 12.59 40 Positive II 0.07 0.20 1.55 2.39 0.09 0.27 2.01 3.07 0.15 0.43 2.98 4.56 0.29 0.79 5.39 8.16 40 Negative II 0.09 0.27 1.91 2.92 0.12 0.36 2.47 3.77 0.17 0.50 3.65 5.54 0.35 0.94 6.75 10.09 40 Positive III 0.04 0.11 1.03 1.31 0.06 0.15 1.32 1.68 0.10 0.21 1.95 2.47 0.16 0.38 3.54 4.47 40 Negative III 0.07 0.17 1.32 1.69 0.09 0.20 1.70 2.15 0.12 0.29 2.43 3.08 0.21 0.52 4.42 5.54 50 Positive I 0.10 0.29 1.81 2.91 0.13 0.38 2.31 3.72 0.18 0.54 3.37 5.43 0.32 0.94 6.18 9.77 50 Negative I 0.14 0.36 2.22 3.59 0.17 0.46 2.83 4.59 0.26 0.69 4.20 6.75 0.45 1.18 7.69 12.17 50 Positive II 0.09 0.24 1.52 2.30 0.12 0.31 1.97 2.97 0.18 0.44 2.92 4.37 0.31 0.79 5.28 7.81 50 Negative II 0.13 0.30 1.92 2.88 0.15 0.38 2.47 3.70 0.20 0.52 3.56 5.31 0.36 0.92 6.45 9.57 50 Positive III 0.04 0.10 0.97 1.24 0.05 0.13 1.25 1.61 0.08 0.19 1.84 2.31 0.16 0.36 3.38 4.23 50 Negative III 0.07 0.13 1.25 1.56 0.08 0.17 1.62 2.02 0.12 0.25 2.40 2.97 0.22 0.47 4.34 5.34

10- and 20-year absolute OS and DFS rate difference, % Breast cancer in a first-degree relative Patient and Disease Breast cancer in a second- Characteristics No family history degree relative Unilateral Bilateral ER 10-y, 20-y 10-y, 20-y 10-y, 20-y 10-y, 20-y 10-y, 20-y 10-y, 20-y 10-y, 20-y 10-y, 20-y Age, y status Stage OS, D% DFS, D% OS, D% DFS, D% OS, D% DFS, D% OS, D% DFS, D% 60 Positive I 0.09 0.25 1.72 2.65 0.11 0.31 2.20 3.38 0.17 0.46 3.23 4.92 0.33 0.84 6.00 9.00 60 Negative I 0.11 0.30 2.08 3.16 0.15 0.39 2.75 4.13 0.22 0.58 4.03 6.06 0.40 1.04 7.38 10.97 60 Positive II 0.08 0.22 1.47 2.07 0.10 0.28 1.88 2.66 0.15 0.38 2.78 3.90 0.30 0.72 5.15 7.19 60 Negative II 0.08 0.20 1.88 2.64 0.11 0.26 2.37 3.33 0.14 0.36 3.44 4.82 0.28 0.69 6.32 8.75 60 Positive III 0.04 0.10 0.98 1.17 0.06 0.13 1.27 1.53 0.08 0.20 1.85 2.21 0.16 0.35 3.39 3.99 60 Negative III 0.07 0.15 1.26 1.51 0.09 0.18 1.62 1.94 0.15 0.31 2.39 2.86 0.24 0.49 4.28 5.04 Ygy6 70 Positive I 0.09 0.19 1.61 2.06 0.11 0.24 2.04 2.64 0.16 0.35 2.98 3.84 0.28 0.62 5.54 7.03 70 Negative I 0.12 0.23 2.01 2.58 0.14 0.29 2.57 3.29 0.21 0.42 3.74 4.78 0.37 0.75 6.83 8.64 70 Positive II 0.07 0.14 1.32 1.59 0.09 0.18 1.71 2.08 0.15 0.31 2.51 3.06 0.27 0.52 4.60 5.54 70 Negative II 0.08 0.18 1.65 2.03 0.10 0.23 2.12 2.58 0.17 0.37 3.11 3.79 0.31 0.67 5.70 6.85 70 Positive III 0.05 0.07 0.91 0.93 0.07 0.10 1.21 1.23 0.11 0.16 1.76 1.78 0.18 0.29 3.21 3.22 70 Negative III 0.05 0.10 1.08 1.12 0.06 0.13 1.40 1.46 0.09 0.17 2.06 2.12 0.18 0.30 3.80 3.86 Abbreviations: D%, difference %; CBC, contralateral breast cancer; DFS, disease-free survival; ER, estrogen receptor; OS, overall survival; risk reduction = 95% (base case).

Figure 2. Boxplot Comparisons of Survival Outcomes

Abbreviation: CPM, contralateral prophylactic mastectomy.

In other words, we ran the decision model 864 times to simulate each of the following scenarios:

1. Patient age ranging from 40 to 75 years old (ie, 36 possibilities)

2. Estrogen receptor status—positive or negative (ie, 2 possibilities)

3. Stage of primary cancer—stage I, stage II, or stage III (ie, 3 possibilities)

4. Family history—no family history, second-degree relative only, first-degree relative unilateral breast cancer, first-degree relative bilateral breast cancer (ie, 4 possibilities)

There are a total of 36 × 2 × 3 × 4 = 864 different combinations of the above parameters, and thus 864 possible scenarios. We ran the microsimulation model for all of the above scenarios, and we tabulated the following output in an Excel spreadsheet for use in the decision tool:

• Risk of developing contralateral breast cancer (CBC, No CPM) %

• Risk of developing contralateral breast cancer (CBC, CPM) %

• Risk of dying from breast cancer (No CPM) %

• Risk of dying from breast cancer (CPM) %

• Risk of dying from other causes (No CPM) %

• Risk of dying from other causes (CPM) %

• Overall survival (No CPM) %

• Overall survival (CPM) %

• Overall survival difference (CPM – No CPM)

• Overall survival difference (CPM – No CPM) %

• Disease-free survival (No CPM)

• Disease-free survival (CPM)

• Disease-free survival difference (CPM – No CPM)

• Disease-free survival difference (CPM – No CPM) %

The development process involved significant involvement from several stakeholder groups. We asked 4 breast cancer surgeons, 4 members of the CAB, and 4 breast cancer survivors to provide input about the design features using a paper mockup of the risk- prediction tool.

Cognitive testing was performed in which the stakeholder was asked to “think aloud” as he or she reacted to the risk information provided. Various presentation formats for the risk information were created and tested iteratively to ensure comprehension. We followed best practices for risk communication, such as using a common denominator in reporting probabilities (eg, x in 100), clarifying the time frame (eg, by 10 years from now . . .), and using loss and gain frames (eg, without CPM, 10 women will develop breast cancer in their other breast, while 90 will not develop breast cancer in their other breast).

Results for Risk-Prediction Tool The following design requirements guided the development of the tool, and we modified these requirements as needed, based on the feedback received from the CAB members, breast cancer survivors, and breast surgeons: (1) online, web-based platform to maximize dissemination; (2) simple user interface with drop-down menus for data input; (3) an engaging, visual design with multiple formats for displaying outcome probabilities (eg, icon arrays); and (4) a printout feature providing patients with a summary of their risk information. We are collaborating with Pixel Prime Design to develop a public-facing web interface for the tool that will be user-friendly to physicians and their patients in facilitating the decision-making process of CPM (see preliminary interfaces, Charts 1A-D), following standards from the International Patient Decision Aid Standards collaboration.

DISCUSSION

In this comprehensive study, we evaluated the long-term psychosocial and clinical outcomes of having CPM compared with not having CPM among women with early-stage sporadic breast cancer. Confirming previous results by our research group11 and others,51-53 women who had CPM experienced more cancer worry and body image concerns before the surgery than did women who did not have CPM. This was observed in each group’s responses to the questionnaires as well as the information provided in the qualitative interviews from women, their partners, and their physicians. Importantly, this is the first study to prospectively demonstrate that having CPM affects a woman’s psychosocial adjustment following surgery in several key areas. Women who had CPM had statistically significantly higher distress scores and body image concerns and lower trust in physician and QOL than did women who did not have CPM, after adjusting for the time effect of before vs postsurgery. The decision model demonstrated that although CPM improves DFS from 0.93% in women with no family history to 12.59% in women with a first-degree relative with a bilateral breast cancer, CPM has a minimal or an unfavorable effect on quality-adjusted life expectancy among women aged 50 or older regardless of their stage at diagnosis or family history of breast cancer.

The findings of our prospectively conducted study differed from a large cross-sectional and retrospective study that evaluated psychosocial outcomes of women after CPM and showed higher domains of QOL among women who had CPM.20 Hwang et al surveyed breast cancer survivors enrolled in the Army of Women cohort at a median time of 4.6 years since breast surgery and found that women who had CPM reported higher psychosocial well-being and breast satisfaction compared with the no CPM group.20 Information was not collected on cancer distress or cancer worry from the women surveyed. Our results showing higher cancer distress and lower QOL in women after CPM compared with the no-CPM group may have differed because we assessed psychosocial functioning prospectively before and after surgery in both groups.

This may reduce self-justification bias—a situation in which a person tends to justify behavior and deny any negative feedback associated with the behavior. In addition, we

prospectively collected data on these psychosocial factors at defined intervals up to 12 months postsurgery in both the CPM and no CPM groups, thereby allowing women to accurately report their psychosocial experiences in real time and therefore reducing recall bias.

Despite overall general satisfaction, studies have shown that women experience negative feelings regarding body image following CPM. Unokovych et al prospectively followed 60 women who underwent CPM, and more than half of them reported at least 1 body image problem 2 years postoperatively; however, there was no control group.54 In a retrospective survey of women aged 40 or younger who had CPM, 28% experienced negative physical side effects related to surgery, and 42% reported diminished sexuality.26 Our finding of higher and persistent body image concerns among women after CPM compared with no CPM at 12 months postsurgery is consistent with these reports. In our study, cancer worry was strongly predictive of having CPM and had a significant interaction with time, decreasing after surgery in women who had CPM compared with the no CPM group. This suggests that although having CPM may decrease specific cancer worry, other aspects of distress (eg, intrusive thoughts and body image concerns) remain.

An important strength of our prospective study is that we recruited women from both an academic medical center and a community hospital setting, which increases the generalizability of our results. The different recruitment methods used at the 2 study sites was unavoidable because the patient flow was different at each site. At MDACC, women were aware of their diagnosis of breast cancer before the surgeon’s visit and were therefore recruited before their visit with the surgeon; however, at KS, women met with their surgeon before knowledge of a breast cancer diagnosis and therefore were recruited after the visit. The sample was ethnically diverse (16% African American, 16% Hispanic, 8% other). Notably, we found that Hispanic women in our sample were more likely to have CPM than women who were non-Hispanic White. This is in contrast with some other studies that have shown higher CPM rates among non-Hispanic White women compared with women of other races/ethnicities.55-57 One possibility for the disparate findings may be that our participants had to be English speaking, and we recruited a larger percentage of Hispanic women than had many

previous studies, or that we included women from both academic and community settings. Alternatively, it may be that trends are changing as awareness of CPM increases. In our planned multivariable longitudinal modeling, we will explore the association between race/ethnicity and psychosocial adjustment after surgery.

Some limitations of our prospective study should be noted. First, the variables that we examined for this study were not based on a complete conceptual model but rather on factors examined in previous results are consistent with prior decision models that have not considered family history and have shown a less than 1% 20-year overall survival benefit for CPM.30 Lester-Coll et al conducted a decision analysis to evaluate women aged 45 by tumor subtype and cancer stages I through III, and suggested that CPM would not improve quality- adjusted life expectancy for the majority of women; however, family history was not included in this model. Indeed, after including family history, we showed that the greatest gain in quality- adjusted life expectancy was among women aged 40 with an ER-negative, stage I breast cancer, and a first-degree relative with either a unilateral or bilateral breast cancer. For this subgroup of women, the QALY benefit from CPM was similar to that reported for BRCA1/2 mutation carriers. Given the small difference in magnitude for the absolute 10- and 20-year OS benefit for CPM, additional information such as quality-adjusted life expectancy and long-term psychosocial outcomes should also be considered in the decision-making process, as they may ultimately play a significant role in a woman’s decision whether to have CPM.

Our decision model applied individual-level simulation to compare quality-adjusted health outcomes of CPM and surveillance only (no CPM). A strength of this analysis method was that it enabled us to estimate individual patient outcomes. We relied on probability estimates obtained from the literature, particularly those concerning the risk of CBC and utilities for health states. Because the increased risk of CBC associated with ER-negative cancers as it relates to family history is not explicitly stated in the literature, our estimate of this risk factor was based on a calibration of plausible CBC risk ranges from reported data. In our model we relied on health states that were already published and corresponded well to the model that we constructed.49,58 We did not collect health utility data from the participants of the

prospective study since it was an added burden for participants to complete the Gamble questionnaire. Therefore, negative feelings regarding body image and adverse psychosocial outcomes following CPM were not accounted for in the utilities; had they been accounted for, they would have resulted in a greater unfavorable quality-adjusted life expectancy.

CONCLUSIONS

Women who elect to have CPM tend to overestimate their risk of developing CBC and have little knowledge of the lack of benefit of CPM in reducing the risk of recurrence or improving overall survival. Results from our decision model showed that CPM has a minimal effect on overall survival and a minimal or unfavorable effect on quality-adjusted life expectancy regardless of family history of breast cancer for the majority of women diagnosed with breast cancer. Stakeholders for the dissemination of educational information about the effects of CPM on survival outcomes include providers as well as patients, as reports indicate that more effective patient–physician education and communication about CPM are needed to reduce overtreatment. The results of our prospective study highlight the need to incorporate education about psychosocial outcomes such as cancer distress, QOL, and body image concerns in addition to clinical outcomes into discussions about CPM. Women interested in CPM may be experiencing higher levels of distress and may anticipate that having the procedure will reduce the distress, but our results suggest that may not be many women’s experience. For women experiencing high levels of cancer distress, clinical psychological interventions that directly address this cancer distress and concerns about body image may be warranted before surgery. In our exploratory multivariable longitudinal model adjusted for age, race/ethnicity, and stage, the association between CPM and body image and QOL remained statistically significant. In addition to the key factors we adjusted for in this study, there may be other factors that influence women’s adjustment and QOL after breast cancer surgery.

The risk-prediction tool that was created from the decision model will be field tested for usability and acceptability among patients and their providers. We will evaluate in a future study whether the tool enhances a woman’s understanding of the small benefit of CPM and whether that understanding influences her decision about having CPM. The results of this comprehensive study will help inform the development of future evidence-based decision tools and psychosocial interventions that will enhance decision-making about CPM and improve the QOL of women with breast cancer.

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APPENDIX Description of Contralateral Prophylactic Mastectomy Decision Support Tool Screenshots of the Contralateral Prophylactic Mastectomy Decision Support Tool are provided in the following figures. The tool is designed to be used during a consultation between the patient and surgeon. There are 2 versions of the tool, 1 using icon arrays to provide a visual representation of the comparative magnitude of the 2 CPM patient-centered outcomes: (1) developing a new breast cancer, and (2) dying from any cause. The basic layout of the tool using icon arrays is given in Chart 1A. A second version of the tool uses bar graphs (see Chart 1D), and provides a slightly different visual picture of the outcomes.

All versions of the tool include inputs for specifying risk factors for a new breast cancer and overall mortality. These inputs include the patient’s age, family history of breast cancer (no family history, second-degree relative only, first-degree relative, first-degree relative bilaterally affected), estrogen receptor status (positive or negative), and breast cancer stage (I, II, or III). The outcomes (developing a new breast cancer, dying from any cause) and timeframe (within 10 years, within 20 years) are selected by the user and the visual display is adjusted accordingly

Chart 1A. Screenshot of CPM Decision Support Tool: Example of Layout (icon array version).

Chart 1B. Screenshot of CPM Decision Support Tool: Chances of developing a new breast cancer within 10 years (icon array version).

Chart 1C. Screenshot of CPM Decision Support Tool: Chances of dying for any cause within 10 years (icon array version).

Chart 1D. Screenshot of CPM Decision Support Tool: Chances of developing a new breast cancer within 10 years (bar graph version).

Disclaimer:

The [views, statements, opinions] presented in this report are solely the responsibility of the author(s) and do not necessarily represent the views of the Patient-Centered Outcomes Research Institute® (PCORI®), its Board of Governors or Methodology Committee.

Acknowledgment:

Research reported in this report was [partially] funded through a Patient-Centered Outcomes Research Institute® (PCORI®) Award (CE- 1304-6293). Further information available at: https://www.pcori.org/research-results/2013/mental-and-social-well-being-among- women-cancer-one-breast-who-underwent