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Clinical Trial Details — Status: Completed

Administrative data

NCT number NCT01840163
Other study ID # P01CA163233
Secondary ID
Status Completed
Phase N/A
First received
Last updated
Start date February 2014
Est. completion date September 1, 2017

Study information

Verified date October 2018
Source University of Michigan
Contact n/a
Is FDA regulated No
Health authority
Study type Interventional

Clinical Trial Summary

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.


Description:

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.


Recruitment information / eligibility

Status Completed
Enrollment 537
Est. completion date September 1, 2017
Est. primary completion date August 1, 2016
Accepts healthy volunteers No
Gender Female
Age group 21 Years to 84 Years
Eligibility Inclusion Criteria:

- Stage 1-2 invasive breast cancer diagnosis,

- DCIS

- Ability to read English

Exclusion Criteria:

- Male

Study Design


Related Conditions & MeSH terms


Intervention

Other:
Static version of CanSORT tool

CanSORT Online Tool


Locations

Country Name City State
United States University of Michigan Medical School Ann Arbor Michigan

Sponsors (2)

Lead Sponsor Collaborator
University of Michigan Emory University

Country where clinical trial is conducted

United States, 

References & Publications (1)

Hawley ST, Li Y, Jeanpierre LA, Goodell S, Jagsi R, Ward KC, Sabel MS, Katz SJ. Study protocol: A Randomized Controlled Trial of a Comprehensive Breast Cancer Treatment Patient Decision Tool (iCanDecide). Contemp Clin Trials Commun. 2017 Mar;5:123-132. doi: 10.1016/j.conctc.2017.02.001. Epub 2017 Feb 3. — View Citation

Outcome

Type Measure Description Time frame Safety issue
Primary 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. 4-5 weeks from date of enrollment
Primary 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. 4-5 weeks from date of enrollment
Secondary 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. 4-5 weeks from date of enrollment
Secondary 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. 4-5 weeks from date of enrollment
Secondary 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. 4-5 weeks from date of enrollment
Secondary 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. 9 months after enrollment
Secondary 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. 9 months after enrollment
Secondary 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. 9 months after enrollment
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