This study examines the impact of an online decision tool for patients with early stage invasive breast cancer. The study is a randomized controlled trial (RCT) of 444 newly diagnosed patients, recruited from multiple surgical practices in two SEER catchment areas. Participants will be randomized to receive either a basic version of a decision tool (similar to existing website with breast cancer information) or an enhanced version (featuring a knowledge building component, a values clarification exercise, and a patient activation module). Our hypothesis is that patients who use the enhanced version of the tool will have greater knowledge of their test and treatment options, have a higher rate of high quality (i.e., informed, preference-concordant) decisions, and report more positive appraisal of the decision-making process.
Patients newly diagnosed with breast cancer face a series of complex decisions regarding locoregional and systemic treatment. Currently many of these decisions do not meet the definition of a high quality decision, defined as one that is both informed (i.e., based on an accurate understanding of the treatment risks and benefits) and preference-concordant (i.e., consistent with the patients' underlying preferences). Moreover, the introduction of evaluative tests has made these decisions more complicated for many patients. There is a need to improve the quality of locoregional and systemic treatment decisions for breast cancer patients, and to help patients understand the role of evaluative tests in this decision process. Ensuring patients can deliberate effectively about these decisions, assert their views and communicate with their clinicians is likely to improve their overall decision preparedness and satisfaction. This study will focus on the third pillar of individualized care by evaluating the impact of an innovative decision tool on locoregional and systemic therapy decision making for newly diagnosed breast cancer patients. The innovative online decision tool has been developed and tested over the past two years by the CanSORT team (R21 CA129859). Pilot data suggests that this tool has a positive impact on patient knowledge and decision outcomes. The goal of this study is to evaluate the impact of this tool, after it is enhanced in collaboration with our Communication and Dissemination Core, on the quality of decision making for locoregional and systemic breast cancer treatment decision making.
Study Type
INTERVENTIONAL
Allocation
RANDOMIZED
Purpose
HEALTH_SERVICES_RESEARCH
Masking
SINGLE
Enrollment
537
University of Michigan Medical School
Ann Arbor, Michigan, United States
Number of Patients With Accurate Knowledge About Risks and Benefits of Treatment Options for Locoregional Breast Cancer.
Self reported knowledge about locoregional treatment using a 5 item Breast Cancer Knowledge Measure (adapted). A binary knowledge indicator was created for all patients whereby high knowledge indicated for patients scoring greater than 80% on the item scale. The binary knowledge variable was analyzed for intervention effect using both unadjusted and adjusted logistic mixed model regression.
Time frame: 4-5 weeks from date of enrollment
Number of Patients Choosing a Treatment Option for Locoregional Treatment That Was Values Concordant
Self reported values were evaluated using a 5 item question set adapted from Decision Quality Instrument. The questions determined patient desire for outcomes such as keeping their natural breast and avoiding radiation on a scale from 0 to 10. Patients were classified as values-concordant if their actual treatment aligned with their values score predicted treatment and otherwise were classified as non-concordant. The binary values-concordance variable was modeled as a function of intervention effect using both unadjusted and adjusted logistic mixed model regression.
Time frame: 4-5 weeks from date of enrollment
Patient Preparedness Decision Making for Locoregional Treatment.
A 12 item decision preparedness scale asked whether the web intervention helped patients prepare for their treatment decision. Each item asked about a diefferent aspect of decision preparation, with responses of 'not at all'/'a little'/'somewhat'/'quite a bit'/'a great deal'. Each response was assigned a value of 1('not at all') to 5('a great deal'), with a high value representing a greater amount of preparedness. The values of all 12 items were combined using the arithmetic mean, to create a standardized scale ranging from 1(not at all) to 5 (a great deal). The decision making scale was modeled by linear mixed model to determine the effect intervention on patient preparation for decision making.
Time frame: 4-5 weeks from date of enrollment
Patient Deliberation for Locoregional Breast Cancer Treatment.
A 4 item Breast Cancer Treatment Deliberation Scale asked how deliberative patients were in making their treatment decision. The items asked how often they performed deliberative activities with answers of 'not at all'/'a little'/'somewhat'/'quite a bit'/'a lot'. Each response was assigned a value of 1('not at all') to 5('a lot), with a high value representing a greater amount of deliberation. The values of all 4 items were combined using the arithmetic mean, to create a standardized scale ranging from 1 (not at all) to 5 (a lot). The deliberation scale was then modeled using linear mixed models to determine the effect of the intervention on patient deliberation.
Time frame: 4-5 weeks from date of enrollment
Patient Subjective Decision Quality for Locoregional Breast Cancer Treatment
A 5 item subjective decision quality scale measured how satisfied patients were with their treatment decision. Patients were asked how well they agreed with 5 statements, with responses of 'not at all'/'a little bit'/'somewhat'/'quite a bit'/'very much'. All responses were assigned values from 1 to 5, with higher values reflecting greater decision satisfaction. Two of the statements reflected satisfaction with the decision and were coded as 1 for 'not at all' through 5 for 'very much'. The other three statements reflected dissatisfaction with the decision and were coded as 5 for 'not at all' through 1 for 'very much' The values of all 5 items were combined using the arithmetic mean, to create a standardized scale ranging from 1 (not at all) to 5 (very much). The subjective decision quality scale was modeled by linear mixed model to determine the effect of intervention on patient response.
Time frame: 4-5 weeks from date of enrollment
Number of Patients With Accurate Knowledge About Risks and Benefits of Systemic Treatment Options for Breast Cancer
Self-reported knowledge about systemic treatment using a 5 item Breast Cancer Knowledge Measure (adapted) consisting of 5 questions to test patients' knowledge about systemic treatment options for breast cancer. We compared the number of patients who gave correct answers to at least 80% of the questions between two groups. We used both unadjusted and adjusted generalized linear mixed models with logit as the link function.
Time frame: 9 months after enrollment
Patient Preparedness Decision Making for Systemic Treatment
A 10-item decision preparedness scale asked whether the web intervention helped patients prepare for their treatment decision. Each item asked about a different aspect of decision preparation, with responses of 'not at all'/'a little'/'somewhat'/'quite a bit'/'a great deal'. Each response was assigned a value of 1('not at all') to 5('a great deal'), with a high value representing a greater amount of preparedness. The values of all 10 items were combined using the arithmetic mean, to create a standardized scale ranging from 1(not at all) to 5 (a great deal). The decision making scale was modeled by linear mixed model to determine the effect intervention on patient preparation for decision making.
Time frame: 9 months after enrollment
Patient Subjective Decision Quality for Systemic Breast Cancer Treatment
A 4 item subjective decision quality scale measured how satisfied patients were with their chemotherapy treatment decision. Patients were asked to rate the amounts of information, involvement, time, and overall satisfaction associated with their chemotherapy decisions. Possible responses ranged from 'not enough' to 'just right' to 'too much'. All responses were assigned values from 1 to 5, with a response of 'just right' coded as 5 points, and both 'not enough' and 'too much' coded as 1 point. The values of all 4 items were combined using the arithmetic mean, to create a standardized scale ranging from 1 (low decision quality) to 5 (high decision quality). The subjective decision quality scale was used as an outcome in linear mixed models to determine the effect of intervention on patient decision quality.
Time frame: 9 months after enrollment
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