Abstract
Previous studies have shown that breast cancer patients’ beliefs regarding radiation therapy (RT) are influenced by a multitude of factors encompassing demographic, socioeconomic, cultural, and healthcare-related domains. The association between consultation with a multidisciplinary care team and breast cancer patients’ attitudes towards RT, however, remains understudied. Using survey and medical record data from 185 women with invasive, non-metastatic breast cancer who received breast conserving surgery, we aimed to characterize the relationship between the number and type of oncological specialties consulted and women’s belief in RT’s ability to decrease the likelihood of breast cancer recurrence. Using multivariable models, we found that compared to women who discussed RT with only one oncologist (medical, radiation, or surgical), women who discussed RT with all three oncologists were more likely to report increased agreement with RT’s ability to reduce cancer recurrence. No single specialty of oncology, including radiation oncology, showed increased associations with women’s beliefs regarding RT’s efficacy. We conclude that women’s beliefs in the ability of radiation therapy to reduce breast cancer recurrence are associated with an increased number of oncologic physicians consulted.
Keywords: Radiotherapy, Patient beliefs, Breast cancer, Patient education
Introduction
For decades, radiation therapy (RT) has been an important component in the treatment of breast cancer, both in the postmastectomy [1] and breast-conservation [2] settings. Recent evidence has explored the patient demographic and diseasecharacteristics that are likely to benefit most from radiotherapy. For example, the oncologic benefit of adjuvant RT in specific populations, like in the elderly with low-risk breast cancer, has been under question [3, 4]. Despite the evolving role of RT in breast cancer therapy, understanding women’s attitudes towards the efficacy of breast RT is of paramount importance. Characterizing women’s attitudes and beliefs surrounding RT will not only help unearth patient information needs, but it will aid in improving patient-physician interactions across cancer care.
Within the general population, up to two-thirds of people have neutral or negative views of RT, associating radiation with atomic bombs, cancer, and nuclear reactors [5–9]. Within the breast cancer population, the general misconceptions surrounding RT are compounded with mistrust of the medical system, fear of side effects, and ineffective communication between patients and healthcare providers [10–15]. In one study, nearly half of patients had read or heard frightening things about RT, though 3% actually reported the negative stories of RT to be true and 85% found their experience to be “less scary” than originally expected [16].
Currently, there are many studies that describe the informational needs of breast cancer patients undergoing radiation therapy [17–20]. Most patients desire information about diagnosis, prognosis, the purpose of treatment, and treatment side effects [18, 19]. However, very little is known about how perceptions of RT are molded. The few qualitative studies that address this topic have concluded that information provided by the physician regarding the benefits and risks of radiation therapy is integral to decision-making [14, 21].
Fortunately, studies have shown that women find healthcare professionals to be the most trustworthy source of information about RT [9, 21]. Given this finding, further investigation into the association between multidisciplinary cancer care teams and level of patient education and understanding of RT is merited. To our knowledge, very little is known about how a patient’s oncological team affects the understanding of RT. In this study, we aimed to characterize the association between the number and discipline of providers discussing RT with women undergoing treatment for breast cancer and their views on the efficacy of RT. We hypothesized that women who spoke with only a radiation oncologist would have the similar views towards the efficacy of radiation therapy as women who consulted with all three disciplines of oncology.
Methods
Setting and Population
The full details of this study can be found in Sheppard et al. [22]. In brief, women with primary invasive, non-metastatic breast cancer (or ductal carcinoma in situ) were recruited and interviewed from three hospitals in the Washington, DC area and one hospital in Detroit, Michigan, between July 2006 and April 2011. Outreach efforts, in the form of fliers and posters, were also made to bolster hospital recruitment. Women who were over age 21, spoke English, self-identified as either African-American or white race, and had invasive, non-metastatic breast cancer were eligible for the study. We followed Snead et al. [23] in defining individuals who were eligible for radiation therapy. Women were interviewed via telephone by trained clinical research assistants 3 months after their definitive surgery, on average. Interviews lasted about 90 minutes. Treatment information was then abstracted from medical records 12 to 18 months after the interview.
From an initial cohort of 678 women who were screened, 477 were eligible to participate in the study and 395 (82.8%) women were ultimately consented. Of the 395 women consented, 68 had missing medical chart abstraction or RT data and were excluded, rendering an analytic sample of 315 breast cancer patients. This study was approved by the Institutional Review Boards at all involved institutions.
Given that our study focused on women’s understanding of RT’s role in reducing the probability of breast cancer recurrence, we elected to consider only women who received a lumpectomy. In this sample, the role of adjuvant RT is relatively clear. Its role in the postmastectomy setting is less intuitive and may be more difficult for patients to comprehend. For example, postmastectomy radiation therapy is not recommended in node-negative lesions less than 5 cm (T2 N0 or below), and its role is controversial in similarly node-negative lesions greater than 5 cm (T3 N0). We therefore excluded 102 women who received a mastectomy. Finally, we excluded 28 women with missing data on independent or key dependent variables, resulting in a final analytic sample of 185 women. Of these women, 128 received radiation therapy. We consider our analyses in this subset of patients as a sensitivity analysis. A separate study by Snead et al. considers correlates of radiation receipt using this data set [23].
Measures
Demographic Variables
The data collection measures used in this study were composed of a combination of proprietary surveys. Demographic and socioeconomic factors were obtained via telephone interview, including age, race, highest level of education, marital status, employment status, and health insurance coverage.
Physician Consultation
Whether or not a patient saw a surgeon, medical oncologist, or radiation oncologist was asked directly. An explanation of the role of the physician was also described. For example, the interviewer stated “A radiation oncologist is a physician who specializes in the treatment of cancer with radiation therapy” followed by, “Did you see a radiation oncologist?” The survey also asked, “Was radiation therapy discussed with you by any of the doctors you saw?” and “If so, which doctors?” Choices included medical oncologist, radiation oncologist, surgeon, and other. Patients were given the option of choosing one or more (or no) providers with whom they discussed radiation therapy.
Perceived Severity, Benefits, and Risks of Therapy
All participants were read brief, two to three sentence explanations of chemotherapy, hormone therapy, and radiation therapy. For example, RT was explained by the following statement, “Some women who have breast surgery sometimes get radiation therapy which is treatment with high-energy rays or particles that destroy cancer cells. This treatment may be used to destroy cancer cells that remain in the breast, chest wall, or underarm area after surgery.” They were then asked to answer questions regarding their discussions of these topics with their cancer care team and whether or not they received that type of treatment. Participants were also presented with questions regarding their understanding of specific types of treatment. In this study, we analyzed the answer to the statement “women are less likely to have the cancer come back if you have radiation therapy.” Women were asked to rate how much they agreed with the statement on a scale of 1 to 4 scale, with 1 being “not at all” and 4 being “very much.”
Statistical Analysis
We used t-tests and χ2 tests to understand the unadjusted bivariate relationships between the level of agreement with RT’s role in reducing breast cancer recurrence and the discussion of RT with various oncologic specialists. Multivariable logistic regression models were employed to assess the relationships after adjusting for other clinical and demographic variables. Odds ratios (ORs) are reported. Huber-White standard errors, clustered at the treatment site level, were used. Data were analyzed with Stata/MP v15.1.
Results
Demographic characteristics for the 185 participants included in this study are described in Table 1. The study sample was all female, predominantly self-identified as African-American (n = 105, 57%), had at least some college education (n = 137, 74%), was mostly unemployed or retired (n = 94, 51%), and had private insurance (n = 120, 65%). The mean age was 56.2 years with a standard deviation of 11.3 years and a range of 21 to 86 years. The majority of women had either stage I or II disease (80%), had no involved lymph nodes (61%), had hormone receptor positive disease (75%), and did not receive chemotherapy (62%).
Table 1.
Descriptive characteristics of breast cancer patients by attitudes towards radiation therapy (RT) benefits
| Response to “women are less likely to have the cancer come back if you have radiation therapy” | ||||||
|---|---|---|---|---|---|---|
| Demographic characteristics | ||||||
| Age | 56.2 (11.3) | 56.4 (10.9) | 47.6 (13.3) | 55.5 (10.6) | 57.0 (11.4) | 0.18 |
| Race | ||||||
| Black | 105 (56.8%) | 9 (64.3%) | 5 (71.4%) | 32 (66.7%) | 59 (50.9%) | 0.21 |
| White | 80 (43.2%) | 5 (35.7%) | 2 (28.5%) | 16 (33.3%) | 57 (49.1%) | |
| Highest level of education | ||||||
| High school or less | 48 (25.9%) | 4 (28.6%) | 3 (42.9%) | 14 (29.2%) | 27 (23.3%) | 0.72 |
| Any college | 56 (30.3%) | 4 (28.6%) | 3 (42.9%) | 15 (31.3%) | 34 (29.3%) | |
| Bachelors and above | 81 (43.8%) | 6 (42.9%) | 1 (14.3%) | 19 (39.6%) | 55 (47.4%) | |
| Marital status | ||||||
| Divorced/separated/widowed | 47 (25.4%) | 1 (7.1%) | 2 (28.6%) | 17 (35.4%) | 27 (23.3%) | 0.25 |
| Married | 89 (48.1%) | 8 (57.1%) | 2 (28.6%) | 23 (47.9%) | 56 (48.3%) | |
| Never married | 49 (26.5%) | 5 (35.7%) | 3 (42.9%) | 8 (16.7%) | 33 (28.4%) | |
| Employment status | ||||||
| Full time | 65 (35.1%) | 7 (50.0%) | 4 (57.1%) | 22 (45.8%) | 32 (27.6%) | 0.097 |
| Part-time | 19 (10.3%) | 0 (0.0%) | 0 (0.0%) | 7 (14.6%) | 12 (10.3%) | |
| Unemployed/retired | 94 (50.8%) | 7 (50.0%) | 2 (28.6%) | 18 (37.5%) | 67 (57.8%) | |
| Never worked/student | 7 (3.8%) | 0 (0.0%) | 1 (14.3%) | 1 (2.1%) | 5 (4.3%) | |
| Insurance type | ||||||
| Private only | 120 (64.9%) | 10 (71.4%) | 5 (71.4%) | 31 (64.6%) | 74 (63.8%) | 0.93 |
| Medicare and private | 30 (16.2%) | 2 (14.3%) | 0 (0.0%) | 8 (16.7%) | 20 (17.2%) | |
| Public | 35 (18.9%) | 2 (14.3%) | 2 (28.6%) | 9 (18.8%) | 22 (19.0%) | |
| Religiosity scale | 17.5 (6.7) | 18.0 (7.0) | 16.3 (7.3) | 15.8 (6.7) | 18.2 (6.5) | 0.21 |
| Stage | ||||||
| 0 | 17 (9.2%) | 3 (21.4%) | 0 (0.0%) | 5 (10.4%) | 9 (7.8%) | 0.72 |
| 1 | 88 (47.6%) | 5 (35.7%) | 3 (42.9%) | 20 (41.7%) | 60 (51.7%) | |
| 2 | 60 (32.4%) | 4 (28.6%) | 3 (42.9%) | 16 (33.3%) | 37 (31.9%) | |
| 3 | 20 (10.8%) | 2 (14.3%) | 1 (14.3%) | 7 (14.6%) | 10 (8.6%) | |
| Number of involved lymph nodes | ||||||
| 0 | 113 (61.1%) | 9 (64.3%) | 5 (71.4%) | 31 (64.6%) | 68 (58.6%) | 0.89 |
| 1–3 | 41 (22.2%) | 2 (14.3%) | 2 (28.6%) | 10 (20.8%) | 27 (23.3%) | |
| 4–19 | 11 (5.9%) | 1 (7.1%) | 0 (0.0%) | 4 (8.3%) | 6 (5.2%) | |
| Unknown/not assessed | 20 (10.8%) | 2 (14.3%) | 0 (0.0%) | 3 (6.3%) | 15 (12.9%) | |
| Number of comorbid diseases | ||||||
| No comorbid disease | 57 (30.8%) | 5 (35.7%) | 3 (42.9%) | 9 (18.8%) | 40 (34.5%) | 0.47 |
| 1–2 comorbid diseases | 67 (36.2%) | 5 (35.7%) | 3 (42.9%) | 19 (39.6%) | 40 (34.5%) | |
| > 2 comorbid diseases | 61 (33.0%) | 4 (28.6%) | 1 (14.3%) | 20 (41.7%) | 36 (31.0%) | |
Note: Sample represents women with non-metastatic breast cancer who received breast conserving therapy as part of their initial therapy who participated in the “Narrowing the Gap” study.
Findings reported as N (%) for categorical variables and Mean (Std. Dev.) for continuous variables. P values reported for chi-squared tests for categorical variables and ANOVA for continuous variables. Percentages may not sum to 100 due to rounding.
A minority of women discussed radiation therapy with three oncologic specialties (20.5%); a total of 81 women (44%) discussed RT with only one specialty. Almost half of these women discussed RT with a radiation oncologist (38/81, 47%), while the remainder discussed radiation therapy only with a medical or surgical oncologist. The remaining 66 women discussed RT with two specialties, which were approximately evenly split between the possible combinations of radiation, surgical, and medical oncology.
The right columns of Table 1 report these variables by patient response to our key dependent variable: “women are less likely to have the cancer come back if you have radiation therapy.” A total of 116, or 63%, of surveyed women “very much” agreed to RT reducing cancer recurrence (scale of 1 to 4, 1 being “not at all” and 4 being “very much”). The mean response value was 3.44, with a standard deviation of 0.88, indicating that most women “somewhat” or “very much” agreed with RT’s ability to reduce recurrence.
The aggregate number of oncological specialties was significantly associated with women’s responses, with those consulting more specialties tending to have a more favorable view of RT’s ability to reduce local recurrence (p = 0.036). Further analyzing the data by the oncological specialty consulted showed no association with women’s beliefs in the efficacy of RT. Women’s beliefs about the efficacy of RT were not associated with other demographic and clinical variables in this bivariate analysis.
Using multivariable logistic regressions, we identified variables that were associated with women’s understanding of RT. The results of these models are reported as odds ratios in Table 2. We created two separate models, considering the aggregate number and type of oncologic specialty as key independent variables (models 1 and 2, respectively). The results of model 1 suggest that women who discussed RT with all three specialties were 2.19 times more likely to “very much” agree to RT’s usefulness in reducing breast cancer recurrence compared to those who discussed RT with just one specialty. However, when further breaking down the number of physicians consulted into their respective specialties (Model 2), consulting all three specialties was superior to consulting any single one type of specialty (with the exception of the surgical oncologist, which was not statistically significant). In other words, consultation with a radiation oncologist only was inferior to consultation with all three specialists when it came to women’s attitudes towards the efficacy of radiation therapy.
Table 2.
Multivariate logistic regression models predicting “very much” belief in efficacy of RT in lowering recurrence
| Model 1: number of oncological specialties (N = 185) | Model 2: type of oncological specialties (N = 185) | |||
|---|---|---|---|---|
| Odds ratio | 95% CI | Odds ratio | 95% CI | |
| Number of oncological specialties consulted | ||||
| 1 (reference) | 1.00 | - | - | - |
| 2 | 0.92 | 0.50–1.69 | - | - |
| 3 | 2.19** | 1.26–3.79 | - | - |
| Type of oncological specialty consulted | ||||
| All three oncological specialties (reference) | - | - | 1.00 | - |
| Surgical oncology Only | - | - | 0.75 | 0.35–1.56 |
| Medical oncology Only | - | - | 0.35* | 0.13–0.91 |
| Radiation oncology Only | - | - | 0.31** | 0.18–0.51 |
| Any two specialties | - | - | 0.40** | 0.32–005 |
| Age | 1.02 | 0.98–1.06 | 1.03 | 0.99–1.06 |
| Black race (reference: White race) | 0.46** | 0.29–0.73 | 0.43** | 0.26–0.70 |
| Education level | ||||
| High school or less (reference) | 1.00 | - | 1.00 | - |
| Any college | 2.25** | 1.28–3.94 | 2.45** | 128–4.71 |
| Bachelor’s or beyond | 1.55 | 0.52–1.60 | 1.59 | 0.51–.97 |
| Marital status | ||||
| Divorced/separated/widowed (reference) | 1.00 | - | 1.00 | - |
| Married | 1.11 | 0.39–3.16 | 1.15 | 0.40–3.31 |
| Never married | 3.04* | 1.08–8.59 | 3.67** | 1.39–9.69 |
| Employment status | ||||
| Full time (reference) | 1.00 | - | 1.00 | - |
| Part-time | 1.61* | 1.08–2.38 | 1.87** | 1.29–2.71 |
| Unemployed/retired | 4.86** | 3.43–6.88 | 5.54** | 3.48–8.81 |
| Never worked/full or part-time student | 3.03 | 0.71–13.01 | 3.24 | 0.65–16.18 |
| Insurance type | ||||
| Private (reference) | 1.00 | - | 1.00 | - |
| Medicare and private | 0.85 | 0.31–2.33 | 0.93 | 0.34–2.54 |
| Public | 0.56** | 0.36–0.87 | 0.55** | 0.37–0.84 |
| Stage | ||||
| 0 (reference) | 1.00 | - | 1.00 | - |
| 1 | 1.94 | 0.50–7.53 | 1.97 | 0.54–7.14 |
| 2 | 1.92 | 0.47–7.88 | 1.84 | 0.45–7.57 |
| 3 | 0.76 | 0.11–5.46 | 0.82 | 0.09–7.18 |
| Number of positive lymph nodes | ||||
| 0 (reference) | 1.00 | - | 1.00 | - |
| 1–3 | 1.42 | 0.35–5.81 | 1.51 | 0.31–7.45 |
| 4–19 | 1.54 | 0.28–8.45 | 1.31 | 0.21–8.38 |
| Unknown/not assessed | 1.30 | 0.70–2.41 | 1.30 | 0.82–2.06 |
| Hormone receptor status | ||||
| Positive (reference) | 1.00 | - | 1.00 | - |
| Negative | 0.58 | 0.25–1.34 | 0.58 | 0.24–1.40 |
In terms of other variables associated with reporting “very much” agreement to the question “women are less likely to have the cancer come back if you have radiation therapy” on multivariable analysis, we found that women with any college education, those who were never married, and those who reported less than full-time employment were more likely to believe in RT’s efficacy. Conversely, women who self-reported as African-American, had public health insurance, or had more than two comorbidities were less likely to report “very much” agreeing that RT can reduce breast cancer recurrence. These associations were similar between the two multivariate models.
Finally, we considered the multivariable analysis among the subsample of 128 patients who received radiation therapy. These results are substantively similar to those presented in Table 2 and are available from the authors upon request.
Discussion
Our study aimed to understand the association between a multidisciplinary oncological care team and breast cancer patients’ perceptions of the efficacy of radiation therapy. Using quantitative data, we found that women who consulted with all three oncological specialties were more likely to believe in the ability of radiation therapy to reduce disease recurrence. These findings did not support our hypothesis and show the integral role that every oncological discipline plays in shaping a woman’s beliefs regarding radiation treatment.
Our results shed light on the importance of the care team in helping women understand the role of radiation therapy in breast cancer care and disease recurrence. Currently, studies show that the majority of women have inaccurate perceptions of their recurrence risk. In a large sample of early-stage breast cancer survivors, only 17% of women accurately assessed their recurrence risk at 6 months after surgery [24]. In this series, 44% underestimated their risk of recurrence. An even smaller number had accurate estimates at 12 months, despite consultation with various oncologists. Although our study analyzed women’s views on the efficacy of radiation therapy, our findings, in combination with the findings of the Liu study, show a need for improved communication between patients and physicians regarding recurrence risk and treatment [23].
Janz et al. have extensively investigated the impact of doctor-patient communication on early-stage breast cancer patients’ perceptions of breast cancer recurrence [25]. Although their data were not separated by the specialty of the physician consulted, they found that patients who had more discussions regarding their risks had increased accuracy of their recurrence-risk estimate. This again shows the value of increased and improved patient-physician communication in women’s understanding of their recurrence risks and treatment efficacies.
There are many reasons to believe that discussing RT with all three primary oncological specialties can result in an increased trust in the efficacy of RT. Although the women in our study may not have necessarily had physicians who participated in a multidisciplinary group meeting, they were still likely exposed to a number of opinions. In a retrospective study of close to 1200 breast cancer patients, only 29% consulted a radiation oncologist prior to surgery [26]. Those who consulted a radiation oncologist were more likely to receive BCS followed by RT. As expected, those who only consulted with surgeons were least likely to receive BCS and radiation therapy. Of the women who underwent BCS, those who consulted radiation oncology were five times more likely to receive radiation therapy than those who did not consult radiation oncology [26]. Consultation with a medical oncologist did not affect RT rate. These patterns bring into question whether women’s beliefs in the efficacy of radiation therapy increase when a radiation oncologist is consulted. Despite these patterns, our study supports the need for all oncological disciplines when educating women about the efficacy of radiation therapy in reducing breast cancer recurrence.
A limitation in this study is our lack of knowledge regarding the exact RT information and recommendations discussed by physicians. We acknowledge the impactful existence of participant recall bias as well as the absence of a method of standardizing and assessing the quality of the information discussed with patients regarding RT. Although the majority of the participants had early-stage, node-negative disease with well-defined RT recommendations, differences in physician opinions regarding the need for radiation cannot be ignored. As delineated in many studies, patients’ views on RT are molded by information given by their physicians, making the physician’s knowledge and attitude towards RT key to shaping women’s beliefs in RT [9, 21]. Also, the physician’s attitude can greatly influence a patient’s understanding of outcomes and prognosis. In a mixed qualitative and quantitative study analyzing the effect of patient-oncologist communication on patient understanding of prognosis, Robinson and colleagues found that patients are more likely to concur with their oncologist about likelihood of cure if the oncologist showed more pessimism than optimism [27]. Although our study was not able to control for participant recall bias, the opinions of physicians towards the use of RT, or the quality of the explanations of RT given by physicians, it adds to the literature by shedding light on the possible impact of provider number and specialty on women’s attitudes towards the efficacy of RT.
Another limitation of our study was lack of information regarding treatment outcomes and the patient decision-making process. Additionally, matching disease characteristics with treatment recommendations and receipt was very difficult given the retrospective nature of the study and the variations in postsurgical time at which the survey was delivered. The factors underlying treatment decision-making of women is also unobserved.
These data included a large sample of African-American women, making it a useful tool for understanding racial biases within cancer care. Studies have shown that discordance of race between the provider and the patient can lead to significant implicit biases, which has the potential to impact communication, patient understanding, and treatment outcomes [28]. Further analysis should characterize women’s beliefs in the efficacy of radiation therapy with both the patient’s and physician’s race in mind.
In conclusion, breast cancer patients’ beliefs in the efficacy of radiation therapy are associated with the number of physicians they consult regarding their treatment. Our study suggests that more physician consultations are associated with an increased likelihood of women believing in RT’s ability to reduce breast cancer recurrence. The type of physician consulted may not be as influential on the understanding of RT’s efficacy. As a result, all oncological physicians should be cognizant of their roles in explaining RT. In order to improve women’s understanding of the benefits of RT and its role in their treatment, the information provided by every member of a multidisciplinary care team should be coherent and congruent with team goals.
Footnotes
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