Breast Cancer
Conditions
Keywords
Predict 2.1, Oncotype DX
Brief summary
A broad range of prognostic and predictive tools are available for patients with newly diagnosed early stage breast cancer. These range from free and publicly available mathematical algorithms, through to expensive genomic tests. It is not known how the use of these different scores affects physician decision making with respect to ordering genomic tests, nor how well these algorithms predict for the results of Oncotype DX ® in the real-world setting. This pragmatic study will help to answer these questions.
Detailed description
A broad range of prognostic and predictive tools are available for patients with newly diagnosed early stage hormone receptor positive, Her2 negative breast cancer. These range from free and publicly available mathematical algorithms (e.g. NHS Predict, Magee formulae, Gage and Tennessee equations) that incorporate standard pathology results, through to expensive genomic tests (e.g. Oncotype DX ® and Endopredict ®). It is not known how the use of these different scores affects physician decision making with respect to ordering genomic tests, nor how well these algorithms predict for the results of Oncotype DX ® in the real-world setting. This pragmatic study will help to answer these questions. In summary: Month 1 to 3: pathology and chemotherapy data is collected, no physician questionnaires given. Month 4 to 6: pathology and chemotherapy data collected, plus physician questionnaire administered. Intervention teaching after 6 months of study activation. Month 7 to 9: pathology and chemotherapy data collected, PREDICT 2.1 tool used, no physician questionnaire given. Month 10 to 12: pathology and chemotherapy data collected, PREDICT 2.1 tool used, plus physician questionnaire administered.
Interventions
None listed
Sponsors
Ottawa Hospital Research Institute
Study design
Observational model
COHORT
Time perspective
PROSPECTIVE
Eligibility
Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
No
Inclusion criteria
* Histologically confirmed primary breast cancer * No prior chemotherapy * Eligible for Oncotype DX ® testing as per current Ontario funding criteria including: ER positive, PR positive or negative, HER2 negative, lymph node status negative or micro-invasive disease, tumor \>1 cm in size (or if equal or \<1 cm, must be grade 2/3 or have lymph node micrometastasis).
Exclusion criteria
* Neoadjuvant treatment including window of opportunity trials * Recurrent breast cancer
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Number of Participants With Oncotype DX Testing Ordered | 12 Months | To assess whether providing individual patient prognostic and predictive scores from PREDICT 2.1 affects the rate of subsequent requests for Oncotype DX ® testing. This is measured as the number of participants with Oncotype DX ® testing ordered. |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Time From Resection to Treatment | 12 Months | To assess whether routine availability of PREDICT 2.1 affects adjuvant treatment (chemotherapy, radiation therapy and endocrine therapy). This will be done by identifying the time to starting chemotherapy, endocrine therapy or radiation therapy. |
| Oncotype DX ® Cost | 12 Months | Prognostic risk scores, including Magee formulae, Gage and Tennessee equations will be calculated using patient and tumour characteristics. These scores will be compared with Oncotype DX ® scores when performed. These will be used to determine Oncotype DX ® cost and total health system costs and subsequent health care utilization. |
| Physician Survey | Period 2 (Months 4-6) and Period 4 (Months 10-12) | A physician survey will be used to assess physician comfort when making systemic therapy decisions.It will determine whether the routine availability of PREDICT 2.1 score in the clinic enhanced their comfort with systemic therapy decision-making. |
Countries
Canada
Participant flow
Participants by arm
| Arm | Count |
|---|---|
| Period 1 Patients who were seen with clinical and pathological features in Months 0-3 | 198 |
| Period 2 Patients who were seen with clinical and pathological features in Months 4-6 | 123 |
| Period 3 Patients who were seen with clinical and pathological features in Months 7-9 | 125 |
| Period 4 Patients who were seen with clinical and pathological features in Months 10-12 | 156 |
| Total | 602 |
Baseline characteristics
| Characteristic | Period 1 | Period 2 | Period 3 | Period 4 | Total |
|---|---|---|---|---|---|
| Age, Continuous | 62.3 Years STANDARD_DEVIATION 12.6 | 64.5 Years STANDARD_DEVIATION 11.7 | 64.6 Years STANDARD_DEVIATION 11.2 | 62.3 Years STANDARD_DEVIATION 11.2 | 63.2 Years STANDARD_DEVIATION 11.8 |
| Race and Ethnicity Not Collected | — | — | — | — | 0 Participants |
| Sex: Female, Male Female | 197 Participants | 122 Participants | 124 Participants | 153 Participants | 596 Participants |
| Sex: Female, Male Male | 1 Participants | 1 Participants | 1 Participants | 3 Participants | 6 Participants |
Adverse events
| Event type | EG000 affected / at risk | EG001 affected / at risk | EG002 affected / at risk | EG003 affected / at risk |
|---|---|---|---|---|
| deaths Total, all-cause mortality | 0 / 0 | 0 / 0 | 0 / 0 | 0 / 0 |
| other Total, other adverse events | 0 / 0 | 0 / 0 | 0 / 0 | 0 / 0 |
| serious Total, serious adverse events | 0 / 0 | 0 / 0 | 0 / 0 | 0 / 0 |
Outcome results
Primary
Number of Participants With Oncotype DX Testing Ordered
To assess whether providing individual patient prognostic and predictive scores from PREDICT 2.1 affects the rate of subsequent requests for Oncotype DX ® testing. This is measured as the number of participants with Oncotype DX ® testing ordered.
Time frame: 12 Months
| Arm | Measure | Value (COUNT_OF_PARTICIPANTS) |
|---|---|---|
| Period 1 | Number of Participants With Oncotype DX Testing Ordered | 92 Participants |
| Period 2 | Number of Participants With Oncotype DX Testing Ordered | 62 Participants |
| Period 3 | Number of Participants With Oncotype DX Testing Ordered | 50 Participants |
| Period 4 | Number of Participants With Oncotype DX Testing Ordered | 74 Participants |
Comparison: Pre-Intervention (Period 1 and Period 2) vs Post-Intervention (Period 3 and Period 4)p-value: 0.37Fisher Exact
Secondary
Oncotype DX ® Cost
Prognostic risk scores, including Magee formulae, Gage and Tennessee equations will be calculated using patient and tumour characteristics. These scores will be compared with Oncotype DX ® scores when performed. These will be used to determine Oncotype DX ® cost and total health system costs and subsequent health care utilization.
Time frame: 12 Months
Secondary
Physician Survey
A physician survey will be used to assess physician comfort when making systemic therapy decisions.It will determine whether the routine availability of PREDICT 2.1 score in the clinic enhanced their comfort with systemic therapy decision-making.
Time frame: Period 2 (Months 4-6) and Period 4 (Months 10-12)
Population: Survey was only administered in Period 2 and Period 4. The number analyzed for each row differs from the overall number of participants analyzed because some surveys may have been incomplete and some items left unanswered.
| Arm | Measure | Group | Category | Value (COUNT_OF_PARTICIPANTS) |
|---|---|---|---|---|
| Period 1 | Physician Survey | I would use PREDICT tool again | Strongly Agree | 0 Participants |
| Period 1 | Physician Survey | PREDICT results make me more confident in my recommendation | Strongly Disagree | 0 Participants |
| Period 1 | Physician Survey | PREDICT tool influenced my treatment decision | Strongly Disagree | 0 Participants |
| Period 1 | Physician Survey | PREDICT results make me more confident in my recommendation | Strongly Agree | 0 Participants |
| Period 1 | Physician Survey | PREDICT results make me more confident in my recommendation | Agree | 0 Participants |
| Period 1 | Physician Survey | PREDICT results make me more confident in my recommendation | Disagree | 0 Participants |
| Period 1 | Physician Survey | I would use PREDICT tool again | Agree | 0 Participants |
| Period 1 | Physician Survey | I would use PREDICT tool again | Neither Agree nor Disagree | 0 Participants |
| Period 1 | Physician Survey | I would use PREDICT tool again | Disagree | 0 Participants |
| Period 1 | Physician Survey | I would use PREDICT tool again | Strongly Disagree | 0 Participants |
| Period 1 | Physician Survey | PREDICT tool influenced my treatment decision | Strongly Agree | 0 Participants |
| Period 1 | Physician Survey | PREDICT tool influenced my treatment decision | Neither Agree nor Disagree | 0 Participants |
| Period 1 | Physician Survey | PREDICT results make me more confident in my recommendation | Neither Agree nor Disagree | 0 Participants |
| Period 1 | Physician Survey | PREDICT tool influenced my treatment decision | Agree | 0 Participants |
| Period 1 | Physician Survey | PREDICT tool influenced my treatment decision | Disagree | 0 Participants |
| Period 2 | Physician Survey | I would use PREDICT tool again | Disagree | 1 Participants |
| Period 2 | Physician Survey | PREDICT results make me more confident in my recommendation | Neither Agree nor Disagree | 10 Participants |
| Period 2 | Physician Survey | PREDICT tool influenced my treatment decision | Strongly Disagree | 3 Participants |
| Period 2 | Physician Survey | PREDICT tool influenced my treatment decision | Neither Agree nor Disagree | 17 Participants |
| Period 2 | Physician Survey | I would use PREDICT tool again | Strongly Disagree | 1 Participants |
| Period 2 | Physician Survey | PREDICT results make me more confident in my recommendation | Strongly Disagree | 1 Participants |
| Period 2 | Physician Survey | PREDICT results make me more confident in my recommendation | Agree | 31 Participants |
| Period 2 | Physician Survey | PREDICT results make me more confident in my recommendation | Strongly Agree | 12 Participants |
| Period 2 | Physician Survey | PREDICT tool influenced my treatment decision | Disagree | 11 Participants |
| Period 2 | Physician Survey | PREDICT tool influenced my treatment decision | Agree | 32 Participants |
| Period 2 | Physician Survey | PREDICT tool influenced my treatment decision | Strongly Agree | 9 Participants |
| Period 2 | Physician Survey | PREDICT results make me more confident in my recommendation | Disagree | 8 Participants |
| Period 2 | Physician Survey | I would use PREDICT tool again | Neither Agree nor Disagree | 3 Participants |
| Period 2 | Physician Survey | I would use PREDICT tool again | Agree | 41 Participants |
| Period 2 | Physician Survey | I would use PREDICT tool again | Strongly Agree | 27 Participants |
| Period 3 | Physician Survey | PREDICT results make me more confident in my recommendation | Strongly Agree | 0 Participants |
| Period 3 | Physician Survey | I would use PREDICT tool again | Strongly Agree | 0 Participants |
| Period 3 | Physician Survey | PREDICT tool influenced my treatment decision | Neither Agree nor Disagree | 0 Participants |
| Period 3 | Physician Survey | I would use PREDICT tool again | Agree | 0 Participants |
| Period 3 | Physician Survey | PREDICT tool influenced my treatment decision | Agree | 0 Participants |
| Period 3 | Physician Survey | PREDICT tool influenced my treatment decision | Strongly Agree | 0 Participants |
| Period 3 | Physician Survey | PREDICT tool influenced my treatment decision | Disagree | 0 Participants |
| Period 3 | Physician Survey | I would use PREDICT tool again | Strongly Disagree | 0 Participants |
| Period 3 | Physician Survey | PREDICT results make me more confident in my recommendation | Disagree | 0 Participants |
| Period 3 | Physician Survey | I would use PREDICT tool again | Disagree | 0 Participants |
| Period 3 | Physician Survey | PREDICT tool influenced my treatment decision | Strongly Disagree | 0 Participants |
| Period 3 | Physician Survey | I would use PREDICT tool again | Neither Agree nor Disagree | 0 Participants |
| Period 3 | Physician Survey | PREDICT results make me more confident in my recommendation | Neither Agree nor Disagree | 0 Participants |
| Period 3 | Physician Survey | PREDICT results make me more confident in my recommendation | Agree | 0 Participants |
| Period 3 | Physician Survey | PREDICT results make me more confident in my recommendation | Strongly Disagree | 0 Participants |
| Period 4 | Physician Survey | PREDICT results make me more confident in my recommendation | Strongly Disagree | 3 Participants |
| Period 4 | Physician Survey | PREDICT tool influenced my treatment decision | Neither Agree nor Disagree | 47 Participants |
| Period 4 | Physician Survey | I would use PREDICT tool again | Neither Agree nor Disagree | 19 Participants |
| Period 4 | Physician Survey | I would use PREDICT tool again | Disagree | 5 Participants |
| Period 4 | Physician Survey | PREDICT results make me more confident in my recommendation | Disagree | 12 Participants |
| Period 4 | Physician Survey | I would use PREDICT tool again | Strongly Agree | 60 Participants |
| Period 4 | Physician Survey | PREDICT tool influenced my treatment decision | Agree | 56 Participants |
| Period 4 | Physician Survey | PREDICT tool influenced my treatment decision | Disagree | 21 Participants |
| Period 4 | Physician Survey | I would use PREDICT tool again | Agree | 68 Participants |
| Period 4 | Physician Survey | PREDICT results make me more confident in my recommendation | Agree | 71 Participants |
| Period 4 | Physician Survey | PREDICT tool influenced my treatment decision | Strongly Agree | 22 Participants |
| Period 4 | Physician Survey | PREDICT results make me more confident in my recommendation | Strongly Agree | 31 Participants |
| Period 4 | Physician Survey | PREDICT results make me more confident in my recommendation | Neither Agree nor Disagree | 32 Participants |
| Period 4 | Physician Survey | I would use PREDICT tool again | Strongly Disagree | 1 Participants |
| Period 4 | Physician Survey | PREDICT tool influenced my treatment decision | Strongly Disagree | 7 Participants |
Secondary
Time From Resection to Treatment
To assess whether routine availability of PREDICT 2.1 affects adjuvant treatment (chemotherapy, radiation therapy and endocrine therapy). This will be done by identifying the time to starting chemotherapy, endocrine therapy or radiation therapy.
Time frame: 12 Months
Population: The overall number of participants analyzed are the number of participants in each period. Each row in the outcome measure data table has a different number of participants analyzed per period because not every participant received each treatment type (chemotherapy, radiation, endocrine therapy).
| Arm | Measure | Group | Value (MEDIAN) |
|---|---|---|---|
| Period 1 | Time From Resection to Treatment | Resection to chemotherapy | 1.9 months |
| Period 1 | Time From Resection to Treatment | Resection to endocrine therapy | 1.8 months |
| Period 1 | Time From Resection to Treatment | Resection to radiation | 2.4 months |
| Period 2 | Time From Resection to Treatment | Resection to chemotherapy | 1.8 months |
| Period 2 | Time From Resection to Treatment | Resection to endocrine therapy | 1.9 months |
| Period 2 | Time From Resection to Treatment | Resection to radiation | 2.2 months |
| Period 3 | Time From Resection to Treatment | Resection to endocrine therapy | 2.3 months |
| Period 3 | Time From Resection to Treatment | Resection to radiation | 2.1 months |
| Period 3 | Time From Resection to Treatment | Resection to chemotherapy | 1.8 months |
| Period 4 | Time From Resection to Treatment | Resection to endocrine therapy | 2.2 months |
| Period 4 | Time From Resection to Treatment | Resection to chemotherapy | 1.9 months |
| Period 4 | Time From Resection to Treatment | Resection to radiation | 2.3 months |