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A Trial of a Comprehensive Breast Cancer Treatment Patient Decision Tool

Primary Purpose

Breast Cancer

Status
Completed
Phase
Not Applicable
Locations
United States
Study Type
Interventional
Intervention
Static version of CanSORT tool
CanSORT Online Tool
Sponsored by
University of Michigan
About
Eligibility
Locations
Arms
Outcomes
Full info

About this trial

This is an interventional health services research trial for Breast Cancer

Eligibility Criteria

21 Years - 84 Years (Adult, Older Adult)FemaleDoes not accept healthy volunteers

Inclusion Criteria:

  • Stage 1-2 invasive breast cancer diagnosis,
  • DCIS
  • Ability to read English

Exclusion Criteria:

  • Male

Sites / Locations

  • University of Michigan Medical School

Arms of the Study

Arm 1

Arm 2

Arm Type

Other

Other

Arm Label

CanSORT Online Tool

Static version of CanSORT tool

Arm Description

Comprehensive decision tool

Static version (non-interactive) version of CanSORT decision tool

Outcomes

Primary Outcome Measures

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.
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.

Secondary Outcome Measures

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.
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.
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.
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.
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.
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.

Full Information

First Posted
April 16, 2013
Last Updated
October 9, 2018
Sponsor
University of Michigan
Collaborators
Emory University
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1. Study Identification

Unique Protocol Identification Number
NCT01840163
Brief Title
A Trial of a Comprehensive Breast Cancer Treatment Patient Decision Tool
Official Title
Individualizing Decision Quality for Patients With Breast Cancer: A RCT of a Comprehensive Breast Cancer Treatment Patient Decision Tool
Study Type
Interventional

2. Study Status

Record Verification Date
October 2018
Overall Recruitment Status
Completed
Study Start Date
February 2014 (undefined)
Primary Completion Date
August 1, 2016 (Actual)
Study Completion Date
September 1, 2017 (Actual)

3. Sponsor/Collaborators

Responsible Party, by Official Title
Principal Investigator
Name of the Sponsor
University of Michigan
Collaborators
Emory University

4. Oversight

Studies a U.S. FDA-regulated Drug Product
No
Studies a U.S. FDA-regulated Device Product
No
Data Monitoring Committee
Yes

5. Study Description

Brief 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.
Detailed 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.

6. Conditions and Keywords

Primary Disease or Condition Being Studied in the Trial, or the Focus of the Study
Breast Cancer

7. Study Design

Primary Purpose
Health Services Research
Study Phase
Not Applicable
Interventional Study Model
Parallel Assignment
Masking
Participant
Allocation
Randomized
Enrollment
537 (Actual)

8. Arms, Groups, and Interventions

Arm Title
CanSORT Online Tool
Arm Type
Other
Arm Description
Comprehensive decision tool
Arm Title
Static version of CanSORT tool
Arm Type
Other
Arm Description
Static version (non-interactive) version of CanSORT decision tool
Intervention Type
Other
Intervention Name(s)
Static version of CanSORT tool
Intervention Type
Other
Intervention Name(s)
CanSORT Online Tool
Primary Outcome Measure Information:
Title
Number of Patients With Accurate Knowledge About Risks and Benefits of Treatment Options for Locoregional Breast Cancer.
Description
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
Title
Number of Patients Choosing a Treatment Option for Locoregional Treatment That Was Values Concordant
Description
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
Secondary Outcome Measure Information:
Title
Patient Preparedness Decision Making for Locoregional Treatment.
Description
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
Title
Patient Deliberation for Locoregional Breast Cancer Treatment.
Description
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
Title
Patient Subjective Decision Quality for Locoregional Breast Cancer Treatment
Description
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
Title
Number of Patients With Accurate Knowledge About Risks and Benefits of Systemic Treatment Options for Breast Cancer
Description
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
Title
Patient Preparedness Decision Making for Systemic Treatment
Description
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
Title
Patient Subjective Decision Quality for Systemic Breast Cancer Treatment
Description
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

10. Eligibility

Sex
Female
Minimum Age & Unit of Time
21 Years
Maximum Age & Unit of Time
84 Years
Accepts Healthy Volunteers
No
Eligibility Criteria
Inclusion Criteria: Stage 1-2 invasive breast cancer diagnosis, DCIS Ability to read English Exclusion Criteria: Male
Overall Study Officials:
First Name & Middle Initial & Last Name & Degree
Sarah T. Hawley, PhD, MPH
Organizational Affiliation
University of Michigan
Official's Role
Principal Investigator
Facility Information:
Facility Name
University of Michigan Medical School
City
Ann Arbor
State/Province
Michigan
ZIP/Postal Code
48109
Country
United States

12. IPD Sharing Statement

Citations:
PubMed Identifier
29152598
Citation
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.
Results Reference
background
PubMed Identifier
29364772
Citation
Hawley ST, Li Y, An LC, Resnicow K, Janz NK, Sabel MS, Ward KC, Fagerlin A, Morrow M, Jagsi R, Hofer TP, Katz SJ. Improving Breast Cancer Surgical Treatment Decision Making: The iCanDecide Randomized Clinical Trial. J Clin Oncol. 2018 Mar 1;36(7):659-666. doi: 10.1200/JCO.2017.74.8442. Epub 2018 Jan 24.
Results Reference
derived

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A Trial of a Comprehensive Breast Cancer Treatment Patient Decision Tool

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