Abstract
Objectives:
The study’s goals were to characterize decisional conflict and preparedness for making the decision about having CPM among breast cancer patients considering CPM who do not carry cancer-predisposing mutation and to evaluate correlates of decisional conflict and preparedness.
Methods:
93 women considering CPM completed a survey of decisional conflict and preparedness for the CPM decision, knowledge, perceived risk, self-efficacy, reasons for CPM, input from others and discussion with the doctor about CPM, and cancer worry.
Results:
Between 8% and 27% of women endorsed elevated decisional conflict. Most women were satisfied with preparatory information that they were provided. Knowledge was low. Top reasons for choosing CPM were the desire for peace of mind, lowering the chance of another breast cancer, and improving survival.
Conclusions:
Decisional conflict is elevated in a subset of patients considering CPM. A more well-informed decision may be fostered by a comprehensive discussion about CPM with the patient’s clinician, fostering self-efficacy in managing cancer worry, and helping patients understand their motivations for CPM.
Practice implications:
Clinicians working with breast cancer patients considering CPM should discuss the CPM decision, foster self-efficacy in managing cancer worry, and help patients understand their motivations for the surgery.
Keywords: Contralateral prophylactic mastectomy, Decisional processes, Decisional conflict, Breast cancer
1. Introduction
Contralateral prophylactic mastectomy (CPM) is a procedure that involves surgically removing the unaffected breast as part of breast cancer treatment. CPM is medically considered for women who carry a high risk for contralateral breast cancer (e.g., BRCA 1/2 carriers) because carriers of the BRCA1 and BRCA2 mutation have 3.4–4.5 fold increased risk of contralateral breast cancer [1], and bilateral mastectomy reduced in mortality in carriers [2,3]. Although women with sporadic breast cancer are at risk for a contralateral breast cancer (about 2–4% over 5 years) [4,5], bilateral mastectomy does not confer a survival advantage for these patients [6]. It is for this reason that the American Society of Breast Surgeons’ 2016 consensus statement concluded that CPM should be discouraged in average risk women with unilateral breast cancer [7]. For average risk patients, the decision to have bilateral breast removal is guided by patient preference [8]. The use of CPM has risen exponentially in the past decade, and it is thought that CPM uptake among women who are at average risk are the main driver of this increase [6,9-11].
In a patient-centered approach to medical decision making, preparing patients to make high quality decision is a primary goal. The Ottawa Decision Support Framework [12-14] is a conceptual framework that has been developed to understand and improve medical decisions. This conceptual framework was derived from work on decisional conflict [15], which is defined a state of uncertainty about the course of action to take. According to this framework, reducing decision uncertainty and improving preparedness are the key goals of decision support interventions. This outcome is accomplished by addressing modifiable factors contributing to decision uncertainty, which include a lack of knowledge about options and outcomes, unrealistic expectations of the likelihood of certain outcomes, risks, and benefits, improving knowledge of treatment options, and clarifying relevant values and motivations, and fostering confidence in the ability to obtain and act on information [15-17]. The Ottawa Framework outlines factors which contribute to decision conflict. First, low knowledge about treatment options contributes to decisional uncertainty and low preparedness. Second, patient’s expectations of the likelihood of specific outcomes, such as exaggerating or minimizing the risk for negative outcomes, contribute to decisional uncertainty [13,17]. Third, a lack of personal resources to make and implement specific decisions contributes to decisional uncertainty and preparedness. Personal resources include confidence in one’s ability to obtain and act on information or manage downstream adverse effects, perceived benefits of specific options, support and influence of family, friends, and health care providers, and emotions experienced during the decision making process [12,13,17,18]. Finally, socio-demographic characteristics including younger age, lower education, and lower income, contribute to decisional conflict. These factors have been associated with decisional conflict regarding treatment decisions in other at-risk cancer populations [19-22].
Prior research has examined the role of factors that influence CPM uptake among women who are at average risk and at high risk for hereditary breast and ovarian cancer syndromes [23]. In terms of demographics, women who are younger, more educated, and/or Caucasian ethnicity are more likely to undergo CPM [16,24,25]. Women who have a family history of breast cancer and women who are interested in breast reconstruction are more likely to have CPM [16,25]. Less understanding of cancer treatment and genetic risk [26,27] and survival benefit [28-31] are associated with uptake. Anxiety about cancer [29,31-33], concern about cancer recurrence [31,34,35], overestimation of risk of cancer or CBC [36], and positive expectations of the cosmetic outcomes of bilateral breast reconstruction [31,33,37] are associated with CPM uptake. Perceived CPM benefits are: Reducing risk for another primary breast cancer, improving survival, avoiding additional chemotherapy or radiation, reducing future surveillance, and improving breast symmetry [31,38-40]. Finally, social influences include media norms such as the use of bilateral mastectomy among celebrities [41], spouse advice [33], advice from family and friends [32], and surgeon recommendation influence the decision [30,42,43].
As has been pointed out in a recent review of the CPM decision making and satisfaction literature [23], there are several areas where empirical research is lacking. First, there is a paucity of research on this process at the time when the decision is being made. Research has evaluated decision making outcomes and contributing factors after the surgical decision was made. A better understanding of this process and ultimately the development of effective methods of facilitating well-informed decisions might be achieved if the process was studied at the time the patient is considering this surgery. Second, there is a paucity of research are the level of knowledge about the CPM surgery and its risks before the decision is made. Third, prior studies have not evaluated the relative contribution of knowledge, psychological, and social influence variables in the CPM decision. Considering factors together would elucidate which factors play a stronger role than others. Finally, few studies have utilized a theoretical framework to guide the research, which could more easily guide decision support interventions.
As noted above, little is known about decisional conflict and preparedness for decision making and the factors associated with decisional conflict among breast cancer patients at average risk at the time they are considering CPM. Towards this goal, the present study had three aims. The first aim was to characterize decision conflict and preparedness to make the decision among newly diagnosed average risk breast cancer patients considering CPM. The second aim was to characterize the Ottawa Framework variables – knowledge of treatment options, expectations about the likelihood of negative outcomes, and personal resources to make and implement specific decisions – in decisional conflict and preparedness. The third aim was to evaluate the association between Ottawa Framework factors in decisional conflict and preparedness. We examined demographic factors as well as knowledge, expectations, and personal resources. We proposed that young age, less education, less knowledge about CPM, overestimated risk for a new breast cancer after treatment, lower self- efficacy for managing post-treatment worry and surveillance, less informational support, and greater worry about recurrence would be associated with greater decisional conflict and less preparedness.
2. Methods
2.1. Participants and procedures
The data for this study is from the baseline survey associated with a pilot randomized clinical trial evaluating the efficacy of a decision support aid for patients considering CPM (NCT03061175). Women were recruited at the appointment with a breast surgeon when treatment options were being discussed. For patients who were having surgery as their first treatment, this was at the initial appointment with the surgeon. For patients who were having neo-adjuvant chemotherapy as their first treatment, recruitment was at the appointment after completion of chemotherapy. Eligible patients were: a) scheduled for a consult with a breast cancer surgeon at one of two study sites; b) considering CPM, regardless of primary breast cancer surgery (lumpectomy/mastectomy); c) diagnosis of Stage 0-3a breast cancer; d) > 18 years; e) speaks and reads English; f) sporadic risk. Risk level was determined by family and medical history. If there was uncertainty, the surgeon used the Tyrer Cuzick [44] risk model to calculate risk [45]; g) had home internet access, and; h) was able to provide meaningful informed consent.
Because this study targeted women considering CPM, participants were identified by surgeon/staff and then approached after the appointment with the breast surgeon when surgical options were discussed. The surgeon referred the patient to the study if the participant was considering CPM and met the risk criterion. Eligible participants were provided written or electronic consent and completed a survey in clinic or online. Participants were randomized to one of the two clinical trial arms after the baseline was completed. Thus, the baseline survey that formed the basis for this analysis was collected after the consent was completed. Participants were paid $25 for the survey. Participants were drawn from two cancer centers in the Northeastern US. One hundred twenty-seven eligible patients were approached. Of these, 93 patients consented and completed a baseline survey, 27 refused participation, and seven patients consented but did not complete the baseline before surgery or withdrew from the study. Thus, the acceptance rate was 73.2%. The most common reasons for refusal were having: already made a decision (n = 7), feeling over-whelmed/no time (n = 5) and not interested in research (n = 4). A comparison of the 93 participants with the 27 patients who declined participation on available data suggested that there were no differences between participants and refusers with regard to age, race/ethnicity, and time since diagnosis.
2.2. Measures
2.2.1. Outcome measures
2.2.1.1. Decisional conflict.
The Ottawa Decisional Conflict scale [17] has 16 items and five subscales: support for the decision, uncertainty about the decision, level of relevant information, clarity of relevant values, and effective decision. Participants rated the CPM decision. Items are rated on a 5-point Likert scale. Scores for the total scale and the five subscales were calculated by an average that was multiplied by 25, which is recommended by the scale’s developers. Thus, scores can range from 0 (no decision conflict) to 100 (high decision conflict). Internal consistency as calculated by Cronbach’s alpha was .96 for the total scale and ranged between .77 and .95 for the five subscales.
2.2.1.2. Preparedness for decision-making.
The Ottawa Preparation for Decision Making scale [46] is a 16-item scale. Items evaluated the amount of and satisfaction with information, and were modified to assess CPM. Sample item: “I have a sufficient amount of information about the actual risk reduction offered by CPM.” Items were rated on a 4-point Likert scale. Higher scores indicate more preparedness. A mean item score was used. Internal consistency as calculated by Cronbach’s alpha was .92.
2.2.2. Ottawa framework measures
2.2.2.1. Knowledge.
A ten-item multiple choice scale developed specifically for this study by the three senior breast cancer surgeons assessed level of knowledge about the definition of CPM, CPM surgical recovery time and risks/side effects, whether or not CPM improves survival, and whether CPM reduced the risk for disease progression. Items are shown in Table 2. Scores reflect the percent of questions answered correctly. Cronbach’s alpha was .53.
Table 2.
Descriptive Information on Decisional Conflict and Preparedness Variables.
| Variables | M | SD | Range |
|---|---|---|---|
| Decisional conflict total | 26.7 | 21.8 | 0-75 |
| Uncertainty about decision | 37.8 | 31.3 | 0-100 |
| Low Support for decision | 20.7 | 21.0 | 0-75 |
| Feel uninformed about options | 25.1 | 22.7 | 0-100 |
| Unclear values for decision | 29.3 | 25.2 | 0-100 |
| Effective decision made | 21.8 | 21.9 | 0-81.3 |
| Preparedness | 3.2 | 0.65 | 1.4-4.1 |
Note: The Preparedness scale score is an item mean.
2.2.2.2. Perceived risk for contralateral breast cancer.
A single item assessed the chances that cancer will come back in the other breast as compared with other women with early stage breast cancer. This was assessed using a categorical scale with three response choices: “higher,” “lower,” and “about the same”.
2.2.2.3. Self-efficacy to manage future worry and surveillance.
Confidence was assessed using a three-item self-efficacy scale that was developed by the authors to evaluate confidence in the ability to manage key tasks for the future: worries and uncertainty about a possible recurrence of breast cancer in the future, follow-up surveillance (mammography, breast MRI), and worries about undergoing future surveillance such as mammography or Breast MRI. Items were rated on a 5-point Likert scale. Response choices (1 = not at all confident, 5= extremely confident) were modeled after the decision self-efficacy scale [17]. A mean item score was used. Cronbach’s alpha was .70.
2.2.2.4. Reasons for CPM.
An 11-item scale was developed based on a review of the qualitative and quantitative literature regarding perceived benefits of having CPM [16,31,33], as well as interviews with breast cancer survivors at sporadic risk who either chose or did not choose CPM regarding the benefits and reasons for selecting or not selecting CPM. Items assessed the desire to improve survival, lower the chance of getting breast cancer in the other breast, prevent cancer from spreading, the desire for peace of mind, the desire for breast symmetry, to reduce worry about the efficacy of mammography, abnormal breast imaging prior to surgery, family history of breast cancer, desire to follow the doctor’s recommendation, avoid future cancer treatment. Items were rated on a 5-point scale as to the degree to which each was a reason the participant was considering CPM. A mean item score was used. Cronbach’s alpha was .73.
2.2.2.5. Support and influence of health care professionals, family, and friends.
This construct was assessed using two measures. First, we developed a five-item scale evaluating the importance of information and input from others (doctors, nurses, family and friends, media, and the internet) in making the CPM decision (1 = not at all important, 4= extremely important). A mean item score was used. Cronbach’s alpha was .73. Second, we developed a single item measure to assess how often reasons to have or not have CPM were discussed with the doctor(s) (1 = not at all, 4 = a lot).
2.2.2.6. Worry about breast cancer recurrence.
A single item assessed how worried the participant was about having another form of breast cancer in the future on a 4-point Likert scale (1 = not at all worried, 4 = very worried).
2.3. Statistical analyses
All statistical analyses were conducted using SPSS. First, we used descriptive statistics to characterize the primary outcomes of decisional conflict and preparedness and the Ottawa Framework measures. Second, we examined associations between the Ottawa Framework measures and decisional conflict and preparedness. In the first step, we evaluated univariate relationships. For the dichotomous predictors (insurance/none, White/not, married/ not), t-tests were conducted. For the categorical predictor (perceived risk), an ANOVA was conducted. Correlations were calculated for the continuous variables. In the second step, those variables that were significantly associated with the outcome were included in a multivariate regression model. Significant demographic factors were entered in the first step in the regression model, before Ottawa Framework variables.
3. Results
3.1. Descriptive information on sample
Sample characteristics are shown in Table 1. The sample was comprised primarily of non-Hispanic white, married women with a relatively high income, and high education level who carried insurance. The average participant age was 47 years.
Table 1.
Characteristics of participants (n = 93).
| Characteristic | N | % | M | SD |
|---|---|---|---|---|
| Age (in years) | 47.1 | 8.3 | ||
| Race/ethnicity | ||||
| Non-Hispanic White | 71 | 76.3 | ||
| Non-Hispanic Black | 5 | 6.2 | ||
| Hispanic white | 3 | 3.2 | ||
| Hispanic Black | 1 | 1.1 | ||
| Asian/Pacific Islander | 5 | 5.4 | ||
| Other | 8 | 8.6 | ||
| Education | ||||
| High school graduate or less | 5 | 5.4 | ||
| Some college/trade school/business school | 16 | 17.3 | ||
| 4-year degree | 43 | 34.4 | ||
| Some graduate education | 5 | 5.4 | ||
| Graduate degree | 35 | 37.6 | ||
| Annual household income (in dollars) | ||||
| ≤ $59,999 | 17 | 18.2 | ||
| $60,000-$99,999 | 14 | 15.1 | ||
| $100-$139,999 | 20 | 21.5 | ||
| $140,000– 179,999 | 11 | 11.8 | ||
| $180,000 | 24 | 25.8 | ||
| Missing | 7 | 7.5 | ||
| Marital Status | ||||
| Married/in relationship | 77 | 82.7 | ||
| Single | 8 | 8.6 | ||
| Separated/divorced/widowed | 6 | 8.6 | ||
| Employment status | ||||
| Full time | 51 | 54.8 | ||
| Part time | 17 | 18.7 | ||
| On leave | 9 | 9.7 | ||
| Retired/does not work outside home | 4 | 4.3 | ||
| Unemployed | 12 | 12.9 | ||
| Insurance Status (Insured) | 90 | 96.8 | ||
| Site | ||||
| MSKCC | 73 | 78.5 | ||
| MGH | 20 | 21.5 | ||
| Time since diagnosis (days) | 54.8 | 56.1 | ||
Note: MSKCC = Memorial Sloan Kettering Cancer Center; MGH = Massachusetts General Hospital.
3.2. Decision conflict and preparedness
Descriptive information is in Table 2. Comparisons with other studies using the same conflict measure indicated that total decisional conflict (M = 26.7, SD = 21.8) was similar to prior studies among cancer patients making clinical trial enrollment decisions (M = 26.3, SD = 19.3) [20], but higher than studies of breast cancer patients making decisions about their breast cancer surgery (M =15.8–19.9) [47]. Of the five subscales of this measure, decisional uncertainty was higher in the current sample (M = 37.8, SD = 31.3) than other studies focusing on cancer patients making decisions about clinical trials (M = 28.7) [48]. Three decisional conflict subscales - feeling unsupported, feeling uninformed, and perceived quality of the decision – evidenced lower average scores than prior work (indicating more support, more information, and greater anticipated quality of the final decision) [48].
We also examined the percentage of women who had elevated decisional conflict using a cutoff of 2, based on evidence that scores greater than two have been associated with adverse decision making outcomes [17,49]. The percentage of women with total decision conflict total scores using the cutoff of greater than 2 was 16.3%. When the subscale means were evaluated using the same metric, the percentage of women with decisional conflict subscale scores greater than 2 ranged between 6.6% (Effective decision subscale) and 36.9% (Uncertainty subscale).
Levels of preparedness to make the CPM decision were moderate, with an average score on the 4-point Likert scale (M = 3.12) corresponding to “moderately agree”. An examination of individual item means indicated that the items with the highest average score were: “How satisfied are you with the way the information about CPM was presented to you?” (M = 3.69) and “How satisfied are you with the amount of information you received thus far?” (M = 3.65). The items with the lowest average score were: “The information I have covers the main reasons some women choose not to have CPM” (M = 2.63) and “The information I have covers the risk and complications of CPM” (M = 2.88).
3.3. CPM knowledge, perceived risk, self-efficacy, reasons for CPM, support and influence, and worry about CBC
Average CPM knowledge was relatively low (46.6% correct). An examination of frequencies indicated that 61.3% of women answered fewer than half of the items correctly. The knowledge item answered incorrectly by the highest proportion of women was the awareness of strategies to reduce one’s future risk for CBC (e.g., Tamoxifen if the tumor is estrogen-sensitive).
In terms of perceived risk for future CBC, 28% reported that their CBC risk was “higher” than other women with early stage breast cancer. Average self-efficacy was high, with the average rating of “very” confident. The reasons for considering CPM which were rated the highest were: To lower chances of getting cancer in the other breast, peace of mind, and to improve survival. In terms of support and influence from others, the average score for the input from others in making the CPM decision (M = 2.4) corresponded with a rating of “somewhat important.” An examination of item frequencies indicated that physicians were the most important source of input in the CPM decision (M = 3.3), followed by nurses (M = 2.5), and family and friends (M = 2.5). Average levels of discussion with the doctor about CPM (M = 3.0) corresponded with “some.” An examination of frequencies indicated that 28% of women reported that the physician discussed CPM “a little” or “not at all.” Finally, the average score for worry about breast cancer recurrence corresponded with a rating of “somewhat worried.” An examination of item frequencies indicated that than half of women reported that were “very worried” about having another form of breast cancer in the future.
3.4. Correlates of decisional conflict and preparedness
3.4.1. Decisional conflict
No socio-demographic variables were associated with decisional conflict. Correlations between the Ottawa Framework variables and decisional conflict (Table 3) illustrated that breater decision conflict was significantly associated with significantly lower self-efficacy to manage worry and future surveillance, fewer reasons for CPM, less frequent discussion about CPM with one’s physician, and more worry about breast cancer recurrence. CPM knowledge, perceived risk for recurrence, and input from others were not significantly associated with decisional conflict. The final regression model that included self-efficacy to manage worry and future surveillance, reasons for CPM, discussion with one’s physician, and worry about recurrence (Table 4) indicated that higher self-efficacy, more reasons for CPM, and more discussion with the physician were significantly associated with less conflict. The full model accounted for 30% of the variance in decisional conflict.
Table 3.
Correlations between Ottawa Decision Framework Factors, Decisional Conflict, & Preparedness.
| Variable | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1. Age | .29** | .16 | −.15 | .12 | −.16 | .01 | .10 | −.11 | −.02 | .15 | |
| 2. Education | .34** | .27** | .09 | −.04 | .02 | −.10 | −.17 | .18 | −.09 | ||
| 3 Income | .28** | .10 | −.01 | −.09 | .07 | −.23* | −.01 | .08 | |||
| 4. CPM knowledge | .18 | −.18 | −.04 | .17 | −.06 | −.07 | .20 | ||||
| 5. Self-efficacy | .03 | .06 | .17 | −.42** | −.39** | .30** | |||||
| 6. Reason for CPM | .02 | .09 | .17 | −.25* | .10 | ||||||
| 7. Input from Others | −.06 | −.12 | .06 | −.04 | |||||||
| 8. Discussion with Surgeon | .04 | −.35** | .46** | ||||||||
| 9. Worry about CBC | −.19 | .23* | |||||||||
| 10. Decisional conflict | −.64*** | ||||||||||
| 11. Preparedness |
Note:
p < .05
p < .01
p < .001
CPM = contralateral prophylactic mastectomy.
Table 4.
Full Regression Models predicting Decisional Conflict and Preparedness Independent variable β R2 t.
| Independent variable | β | R2 | t |
|---|---|---|---|
| Dependent variable: Decisional Conflict | |||
| .29*** | |||
| Self-efficacy | −.28** | −2.7** | |
| Reasons for CPM | −.23* | −2.5* | |
| Discussion with doctor | −.27 | 2.9** | |
| Worry about recurrence | .13 | 1.3 | |
| Dependent variable: Preparedness | |||
| .26*** | |||
| Self-efficacy | .23* | 2.5* | |
| Discussion with doctor | .42*** | 4.6*** | |
Note: CPM = Contralateral Prophylactic Mastectomy
p < .05
p < .01
p < .001.
3.4.2. Preparedness
No socio-demographic variables were associated with preparedness. Correlations between Ottawa Framework variables and preparedness (Table 3) indicated that greater preparedness was significantly associated with greater self-efficacy to manage worry and future surveillance and more frequent discussion about CPM with the doctor. Knowledge, perceived risk for recurrence, reasons for CPM, worry about recurrence, and information support were not significantly associated with preparedness. The full regression model (Table 4) indicated that both self-efficacy and discussions with one’s doctor were significantly associated with preparedness (see Table 4). More preparedness was associated with less self-efficacy and more frequent discussion with the physician. The model accounted for 28.7% of the variance in preparedness.
4. Discussion and conclusion
4.1. Discussion
With patients diagnosed with average risk breast cancer choosing CPM at an increasing rate, it is important to understand this decision at the time when the choice is being made. This study’s goals were to characterize decisional conflict and preparedness and both characterize and evaluate the role of Ottawa Framework variables in decisional conflict and preparedness. Our findings suggest that decisional conflict was elevated in a relatively small subset of patients considering CPM. The one component of decisional conflict that was elevated in a greater proportion of women was decisional uncertainty, which was elevated in about one third of the sample. In terms of preparedness, the majority of women were satisfied with the amount of information they received about CPM and its possible benefits. Patients were less satisfied with information received about the reasons women choose not to have CPM and possible CPM risks and complications.
The second aim was to characterize Ottawa Framework factors including knowledge, self-efficacy to manage future worry and surveillance, perceived risk for a future cancer in healthy breast, reasons for CPM, input from others, and worry about cancer recurrence. CPM knowledge was very low in our sample, and about a quarter overestimated their risk for a cancer in the healthy breast. Personal resources that we examined were self-efficacy to manage future worry and surveillance, reasons for CPM, the importance of information from family, friends, and health care providers, discussion with one’s surgeon about CPM, and worry about future breast cancer. Patients’ reported high levels of self-efficacy to manage future worry and surveillance. The highest-rated reasons for choosing CPM reported in this study - the desire for peace of mind, lower the chance of getting cancer in the other breast, and improve survival - are similar to other research that has targeted in retrospective studies of average- and high-risk patients. [24,31,34,38] These results extend the literature by illustrating that these reasons are also important considerations for sporadic risk patients during the time period when they are deciding about CPM. The present findings point to some differences with regard to the relative importance of reasons to choose CPM as compared to prior studies assessing similar reasons among patients assessed post-surgery. For example, in our study, breast symmetry was not a top-rated reason for CPM, but it is a commonly-reported reason in prior retrospective studies [31,32,34,35]. In contrast to other work [27], family and friends’ input was not considered important influence in the CPM. Although the health care team was rated by patients as the most important information sources as compared with other sources of influence, about a quarter of our sample reported “little” or “no” discussion about CPM with their physicians. In terms of emotions experienced, worry about recurrence of breast cancer in the future was common. This finding is consistent with retrospective studies of breast cancer patients after cancer surgery [24].
Our analysis of the role of Ottawa Framework factors yielded five main findings. First, in the final regression model when all factors were considered together, less discussion with one’s physician was associated with both more decisional conflict and less preparedness to make the decision. Second, in the final regression model, lower self-efficacy to manage future worries about breast cancer recurrence and surveillance was associated with both more decisional conflict and less preparedness to make the decision. These findings are consistent with prior studies of patients making cancer treatment decisions [50]. Third, in both correlational and regression analysis, CPM knowledge was not associated with either decisional conflict or preparedness. This is a surprising finding and supports the contention that these decisions may not be based upon actual knowledge about the CPM procedure. Fourth, other factors that have been associated with CPM uptake, such as worry about recurrence [31,34,35] and higher estimation of risk for a contralateral breast cancer [36] were not associated with decisional conflict and preparedness the current study. Fifth, patients reporting more reasons for considering CPM reported lower less decisional conflict. One possible explanation is that patients who have already identified their motivations for and the aspects of CPM that are driving their decision feel more certain that this choice was right for them. This finding is also consistent with prior work that has found that positive expectations of the cosmetic and psychological outcomes of bilateral breast reconstruction are associated with CPM uptake [31,33,37].
Contrary to literature assessing CPM decisions, which has found that younger [16,51,52], more educated [16,52], and white women [16,38,52,53] are more likely to have CPM, we did not find that age, education, or race were associated with decisional conflict or preparedness. Our lack of findings regarding demographic correlates may be attributed to the fact that we assessed decisional conflict and preparedness before the actual surgery and we did not assess actual surgical uptake, and prior work evaluated patients after surgery and examined surgical uptake [16,51,53]. The differences between findings of the present study and prior work may also be attributed to our sample’s composition, which was mostly non-Hispanic white, well-educated, high income, and insured patients, whereas other studies focused on more diverse samples [52,53].
The key strengths of this study are the focus on the average risk population at the time the decision was being made, utilization of a theoretical framework, and the inclusion of a broad set of Ottawa Framework measures assessed together in a regression model. However, several limitations should be noted. First, the sample was primarily non-Hispanic white, well-educated, and insured. Data were collected at two comprehensive cancer centers, where patients had access to the most advanced breast cancer and reconstructive surgical approaches. Future studies should evaluate decision making in a more diverse population of patients. Second, because there are no validated measures for some constructs such as CPM knowledge and reasons for CPM, we composed scales for this study. Third, we did not assess the actual content of patients’ discussions with their physicians. Qualitative retrospective work suggests that physician’s statements about whether to pursue CPM and the content of the physician-patient interaction are important to patients [40]. Future studies should more carefully evaluate physician-patient discussions. Fourth, other than worry about recurrence, we did not assess emotional experiences during decision making. Future studies should assess anxiety and anticipated regret, which may play a role. Fifth, we did not assess physician-level factors such as whether the surgeon reported s/he initiated a discussion about CPM and what s/he recommended. Sixth, we did not examine the role of decisional conflict and preparedness and Ottawa Framework factors in the ultimate surgical choice. Seventh, participants consented to a randomized clinical trial testing an online decision support tool. Patients who were interested in a decision support intervention study may have different levels of decision conflict. Eighth, although we assessed patients in the time period after the initial surgical consultation and before surgery, it is possible that survey responses did not reflect input from plastic surgeons or other medical providers. Finally, it is known that physician factors (e.g., gender of surgeon) [51] and geographic and health system resource factors that influence availability of the procedure (e.g., state of residence) [54] impact uptake of CPM. We did not assess these factors in this study.
4.2. Conclusions
This study documents the relatively low level of decisional conflict experienced by patients who are considering CPM during the time they are making this decision. Although surgeons were rated as the most important source of information in the decision among these patients and less discussion was associated with more decisional conflict and less preparedness, only a third of patients engaged in a substantive discussion about CPM with their physician. Our findings suggest that a more well-informed decision may entail facilitating a comprehensive discussion about CPM with the physician and health care team, by assisting patients in enhancing their self-efficacy to manage worries about cancer recurring and future surveillance, and fostering a greater understanding of the reasons motivating the consideration of CPM.
Acknowledgements
We would like to thank Tyler Wind, Elena Zarcaro, Cristina Olcese, and Rachel Hepp for data collection, Monica Morrow for her assistance with the knowledge scale, and the oncologists who facilitated recruitment into this study.
Funding
This study was funded by an R21 grant to Sharon Manne and Laurie Kirstein from the National Cancer Institute (CA187643).
Footnotes
Declaration of interest
The authors declare that they have no conflict of interest.
Ethical approval
I confirm all patient/personal identifiers have been removed or disguised so that patient/person described is not identifiable and cannot be identified through the details of the story.
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