Abstract
Background: Discrepancies may exist between what oncologists communicate and what patients understand about their cancer stage and its implications.
Objective: We explored patients' ability to identify their stage of breast cancer.
Methods: As part of a study testing a cancer self-management intervention we asked women to identify their stage of disease and compared responses to the electronic medical record (EMR) for validation. The sample included women with recently diagnosed nonmetastatic (stage I-III) disease. We calculated descriptive statistics and used logistic regression to examine relationships between knowledge of stage, demographic and clinical variables, and study outcomes. Measurement instruments were the Control Preferences Scale (CPS), Knowledge of Care Options Test (KOCO), Measurement of Transitions Scale (MOT), Medical Communication Competence Scale (MCCS), Chronic Disease Self-Efficacy Scale (CDSE), Uncertainty in Illness Scale (MUIS-C), and Hospital Anxiety and Depression Scale (HADS).
Results: Participants (n = 98) had a mean age of 52.3 years (range 27–72). Per the EMR, 19 participants (19.4%) had stage I breast cancer, 56 (57.1%) had stage II, and 23 (23.5%) had stage III. Of the 28 participants (28.6%) unable to identify their stage of cancer correctly, 11 (39.3%) provided vague responses, 11 (39.3%) reported an incorrect stage, and 6 (21.4%) did not know their stage. Younger age (p = 0.0412) and earlier cancer stage (p = 0.0136) were predictive of correctly identifying stage. Participants who at baseline had a greater knowledge of care options (curative, palliative, and hospice care) were more likely to correctly identify their stage (KOCO, p = 0.0345).
Conclusions: Clinicians should revisit conversations about cancer stage and care options to ensure patients' understanding and support self-management.
Introduction
Self-management is the “tasks that individuals undertake to deal with the medical, role, and emotional management of their health condition(s).”1 The Self- and Family Management Framework2 illustrates processes and outcomes of self-management. A key process is learning about one's health condition,3 which includes learning stage of disease. Understanding stage of disease and its implications is a critical part of cancer self-management because stage-related goals of care influence self-management tasks.
Goals of care vary by stage of disease. For breast cancer, the goal of care for stage I and II disease is curative, with self-management focusing on short-term coping with treatment side effects and psychosocial issues.4 The goal of care for stage III breast cancer is likewise curative, but these women must monitor their bodies during remission and cope with uncertainty and fear of metastasis. Stage IV breast cancer is a chronic disease with palliative treatment goals. At this stage, self-management is often more intensive in the frequency and variety of tasks required.
Knowledge of cancer stage among women with breast cancer has not been extensively investigated. Studies have found 40%–77% of women unable to correctly identify their cancer stage.5,6 Other studies have examined advanced cancer patients' understanding of whether their therapy was curative or palliative. Data consistently suggest that patients are unaware of their prognosis and/or do not understand the severity of their disease.7–10 Correct identification of cancer stage has been correlated with age, gender, and income, wherein men and women who were older and had lower income had less understanding of their diagnosis and stage.6–11
To understand better the relationship between knowledge of cancer stage and self-management, we aimed to (1) explore knowledge of cancer stage among women with nonmetastatic breast cancer, (2) examine the influence of demographic and clinical characteristics on women's knowledge of their stage, and (3) examine the relationship between knowledge of cancer stage and self-management.
Methods
This study, approved by the Human Investigation Committee at Yale University, is a secondary analysis of data collected in an evaluation of a cancer self-management intervention.12 We enrolled women with nonmetastatic breast cancer between July 2011 to May 2013 at a cancer center. Eligible participants were English-speaking women aged 21+ who were diagnosed with stage I, II, or III breast cancer within the prior six months.
Infusion nurses identified and approached potential participants to determine interest in the study. A research assistant described the study to any interested potential participant and obtained written consent. In accordance with the Self- and Family Management Framework,2 we measured facilitators and barriers to self-management with the following instruments. The Knowledge of Care Options test (KOCO) uses 11 true/false questions to assess knowledge of curative, palliative, and hospice care.13 With permission, we modified wording of the Control Preferences Scale (CPS) to measure desired and actual self-management roles.14 We used the Medical Communication Competence Scale (MCCS) to measure medical communication skills.15 The Measurement of Transitions Scale (MOT) captures perceived amount of and ability to manage various transitions. Anxiety and depression were reported via the Hospital Anxiety and Depression Scale (HADS).16 We used the Uncertainty in Illness Scale (MUIS-C) to assess uncertainty regarding disease, prognosis, and treatment.17 To measure self-management self-efficacy we used the Chronic Disease Self-Efficacy Scale (CDSE).18
Using a clinical information form we asked participants, “What stage of breast cancer do you have?” with response options of stage I, II, III, IV, or “Don't Know.” Research staff documented responses verbatim, capturing the stage identified and related comments. We compared the participant-identified stage to the cancer stage documented in the electronic medical record (EMR). We considered participants to have correctly identified their stage of cancer if they knew their numeric disease stage, i.e., we considered women with stage IIb cancer who responded “stage II” to be correct.
We calculated descriptive statistics for demographic and clinical data using means and frequencies. We performed logistic regression to determine associations between demographic and clinical characteristics and correct identification of cancer stage, and compared knowledge of cancer stage with all outcome measures.
Results
Sample description
Nurses approached 165 women; 110 consented to participate. Of these, we excluded two women who ultimately had stage IV disease and two who had bilateral disease. We excluded one woman because her stage had not been determined, six who did not complete data collection, and one who did not want to know her stage. Our final sample included 98 participants (see Table 1) who had a mean age of 52.3 years (range 27–72, SD = 10.4), were mostly Caucasian (77.5%), married (64.3%), and had at least some college education (82.6%). Per the EMR, 19 (19.4%) had stage I, 56 (57.1%) had stage II, and 23 (23.5%) had stage III disease.
Table 1.
Sample Demographic and Clinical Characteristics (n = 98)
| Demographic characteristics | Clinical characteristics | ||
|---|---|---|---|
| Age (years) | Time since diagnosis (months) | ||
| Mean (SD) | 52.3 (10.6) | Mean (SD) | 4.0 (2.6) months |
| Range | 27–72 | Range | 0.7–17.6 |
| Number of symptoms | |||
| Race | n(%) | Mean (SD) | 6.2 (3.8) |
| White | 76 (77.5) | n(%) | |
| Black | 9 (9.2) | Stage of breast cancer | |
| Hispanic | 6 (6.1) | I | 19 (19.4) |
| Other | 7 (7.2) | II | 56 (57.1) |
| Marital status | III | 23 (23.5) | |
| Married | 63 (64.3) | Treatment | |
| Divorced/separated | 13 (13.3) | Chemotherapy | 93 (94.9) |
| Widowed | 4 (4.1) | Radiation | 4 (4.1) |
| Living with partner | 1 (1.0) | Surgery | 27 (27.5) |
| Never married | 17 (17.3) | Hormone therapy | 4 (4.1) |
| Education | Zometa | 1 (1.0) | |
| Up to 8th grade only | 2 (2.0) | Other | 5 (5.1) |
| High school graduate | 12 (12.2) | ||
| Trade school | 3 (3.1) | ||
| Some college | 17 (17.3) | ||
| College graduate | 31 (31.6) | ||
| Graduate school | 33 (33.7) | ||
| Income | |||
| <$50,000 | 25 (25.5) | ||
| $50,000–$89,999 | 33 (33.7) | ||
| >$90,000 | 38 (38.8) | ||
| Unreported | 2 (2.0) | ||
| Religion | |||
| Catholic | 45 (45.9) | ||
| Christian | 22 (22.4) | ||
| Jewish | 8 (8.2) | ||
| Muslim | 4 (4.1) | ||
| Other | 8 (8.2) | ||
| None | 11 (11.2) |
Knowledge of cancer stage
Seventy women (71.4%) correctly identified their stage and 28 (28.6%) incorrectly identified their stage (see Table 2). Of the latter group, most had stage II (n = 18) or III (n = 8) disease. We analyzed incorrect responses and grouped them into three categories: Incorrect Stage (n = 11, 39.3%); Vague Response (n = 11, 39.3%); and Did Not Know (n = 6, 21.4%). Incorrect responses showed a mismatch between patients' report of their stage with the stage recorded in the EMR. We categorized seven participants' responses as incorrect because they reported themselves as having a higher cancer stage than reported in the EMR. Vague responses included reported stages that were not clinically accurate but reflected some knowledge of cancer stage, such as “2.5” or “between II and III.” The Did Not Know category included responses of participants who did not know their stage.
Table 2.
Participants' Reported and Actual Stage of Breast Cancer (n = 98)
| Reported stage | Actual stage | |
|---|---|---|
| Correct | 70 (71.4) | |
| I | I | 17 (24.3) |
| II | II | 38 (54.3) |
| III | III | 15(21.4) |
| Incorrect | 28 (28.6) | |
| Vague response | 11 (39.3) | |
| “1/2” | IA | 1 |
| “late I, early II” | IIA | 1 |
| “I or II” | IIB | 1 |
| “between I and II” | IIA | 1 |
| “between II and III” | II | 1 |
| “between II and III” | IIA | 1 |
| “between II and III” | IIIA | 1 |
| “combined II–III” | IIIA | 1 |
| “II or III, not sure” | IIB | 2 |
| “between III and IV” | IIIA | 1 |
| Incorrect response | 11 (39.3) | |
| “not staged yet, inflammatory” | IIIB | 1 |
| “stage I, part II” | IIA | 1 |
| “I” | IIB | 1 |
| “II” | IA | 1 |
| “IIB” | IIIA | 1 |
| “III” | II | 1 |
| “III” | IIB | 5 |
| Did not know | 6 (21.4) | |
| “Do not know” | IIA | 2 |
| “Do not know” | III | 1 |
| “Do not know” | IIIA | 1 |
| “Do not know” | IIIC | 1 |
| “Unsure” | IIB | 1 |
Associations with correct identification of cancer stage
Younger age (p = 0.0412) and earlier cancer stage (p = 0.0136) were predictive of correctly identifying cancer stage. Women who had greater knowledge of care options (curative, palliative, and hospice care) were more likely to correctly identify their cancer stage (KOCO, p = 0.0345). The CPS, MCCS, MOT, HADS, MUIS-C, and CDSE did not correlate with correct identification of cancer stage.
Discussion
More than a quarter of our participants were unable to identify their stage of breast cancer correctly. While still of concern, this percentage is lower than has been reported in other studies.8–10 This result may be influenced by our recruitment site, which offers a palliative care service to facilitate communication about cancer stage and goals of care, and which produced a highly educated sample. We found that significant predictors of correct identification of cancer stage were younger age, which is consistent with previous studies,6,19 and having an earlier stage of cancer.
Correct identification of cancer stage significantly correlated with knowledge of care options, suggesting that understanding the nature of curative, palliative, and hospice care and the goals of care for each relates to understanding cancer stage. This is a significant connection due to the importance of appropriately matching cancer stage and care options as a foundation of self-management.
Clinicians should revisit discussions about cancer stage to ensure patients' understanding. Some oncologists may stress disease biology rather than specific details of cancer stage. Studies have reported that cancer patients and their family caregivers are often dissatisfied and overwhelmed by communication about diagnosis and treatment goals.8,20–25 Clinicians should be mindful to discuss cancer stage in a way that allows patients to digest this information and understand their prognosis, thereby facilitating effective self-management.22
Limitations
All participants were from one cancer center, so results only reflect the participating hospital. Although we approached all eligible women, our sample was mostly Caucasian, which did not permit exploration of racial and ethnic differences in knowledge of cancer stage and implications for cancer self-management. Future work should include a more diverse sample that also includes women with stage 0 and stage IV breast cancer for clinical completeness. It would also be beneficial to follow women for longer than two months to observe if their understanding of cancer stage changes over time. We are currently conducting a randomized controlled trial of the cancer self-management intervention, which we hope will show additional effects of knowledge of cancer stage on self-management outcomes.
Although unlikely, it is possible that participants' stage of cancer changed (i.e., their cancer progressed) in the short time (usually one to three weeks) between when we screened for eligibility and when we approached patients. However, this time lag was short, so the risk of our noting a participant's cancer stage as incorrect when the participant was actually correct at the time of screening was minimal. As a safeguard against error, for the seven patients who reported higher stages than their records indicated, we rechecked the EMR to ensure that the cancer had not actually progressed.
Conclusion
More than a quarter of our participants incorrectly identified their stage of breast cancer, suggesting that they did not fully understand their diagnosis and its implications. Lack of knowledge of cancer stage impedes cancer self-management, because cancer stage informs treatment options and self-management tasks. Knowledge of cancer stage is not only a precursor to self-management, but is an ongoing part of self-management throughout the course of disease. Clinicians should revisit discussions about cancer stage as a springboard to active and informed patient self-management.
Acknowledgments
For their assistance with this study, the authors would like to thank Tony Ma, data manager at the Yale School of Nursing, and the nurse managers and infusion nurses at the Breast Center of Smilow Cancer Hospital. This work was supported by a Mentored Research Scholar Grant, MRSG08-292-05-CPPB, from the American Cancer Society.
Author Disclosure Statement
No competing financial interests exist.
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