NCT05222464

Brief Summary

Vasomotor symptoms (VMS) are a common consequence of systemic therapies for breast cancer. Breast cancer treatments can cause VMS in approximately 30% of postmenopausal women and 95% of premenopausal women with early stage breast cancer (EBC). There are many non-estrogen-based interventions available to manage VMS, including; lifestyle modifications, complementary and alternative medicine (CAM) therapies. However, a recent systematic review and meta-analysis of pharmacological and CAM interventions conducted by our team, found no single optimal treatment for VMS management in breast cancer patients. Given the complex patient, cancer and treatment variables influencing the experience of VMS, the numerous potentially effective VMS interventions available and the varying expectations for an effective intervention, the investigators believe Machine Learning (ML) is ideally suited to the analysis of this common and bothersome treatment related toxicity. The EPIC electronic medical record, and MyChart application has provided both clinicians and patients with increased tools for the documentation of health related outcomes. The investigators believe that the MyChart platform, and ML techniques can be utilized to collect, and analyze outcome data for breast cancer patients experiencing VMS.

Trial Health

87
On Track

Trial Health Score

Automated assessment based on enrollment pace, timeline, and geographic reach

Enrollment
56

participants targeted

Target at P25-P50 for phase_4 breast-cancer

Timeline
Completed

Started Feb 2022

Shorter than P25 for phase_4 breast-cancer

Geographic Reach
1 country

1 active site

Status
completed

Health score is calculated from publicly available data and should be used for screening purposes only.

Trial Relationships

Click on a node to explore related trials.

Study Timeline

Key milestones and dates

First Submitted

Initial submission to the registry

December 15, 2021

Completed
2 months until next milestone

First Posted

Study publicly available on registry

February 3, 2022

Completed
22 days until next milestone

Study Start

First participant enrolled

February 25, 2022

Completed
5 months until next milestone

Primary Completion

Last participant's last visit for primary outcome

July 22, 2022

Completed
2 months until next milestone

Study Completion

Last participant's last visit for all outcomes

September 22, 2022

Completed
Last Updated

December 18, 2025

Status Verified

December 1, 2025

Enrollment Period

5 months

First QC Date

December 15, 2021

Last Update Submit

December 17, 2025

Conditions

Keywords

Breast CancerVasomotor SymptomsMachine Learning

Outcome Measures

Primary Outcomes (4)

  • Patient Engagement (MyChart Accessibility and User Experience)

    Patient engagement will be defined by 60% of patients approached agreeing to participate in the study.

    3 Months

  • Physician Engagement (MyChart Accessibility and User Experience)

    Physician engagement will be defined by 60% of those completing the study log to approach patients for participation in study.

    3 Months

  • Patient Accrual (MyChart Accessibility and User Experience)

    Patient accrual will be defined by accruing 50 participants within 3 months.

    3 Months

  • MyChart Utilization

    MyChart utilization will be defined as 85% of participants completing both questionnaires (the Hot Flash Problem Score and the Composite Hot Flash Score) on the MyChart interface, and 50% of enrolled participants completing both questionnaires as per study protocol.

    Baseline and 6 weeks

Secondary Outcomes (5)

  • Hot Flash Severity (MyChart Feasibility)

    3 Months

  • MyChart Feasibility in assessing effectiveness of interventions for VMS

    3 months

  • Effectiveness of Interventions for VMS - Traditional Statistical Modeling

    3 Months

  • Effectiveness of interventions for VMS (MyChart feasibility)

    3 Months

  • Predicting effectiveness of interventions for VMS - machine learning

    3 Months

Study Arms (1)

Standard of Care Intervention

OTHER

Standard of care intervention - The intervention will consist of 4 classes of standard of care treatments, namely, lifestyle modifications, complementary and alternative medicine (CAM) therapies, prescription medications, or adjustment of anti-cancer therapy.

Other: Standard of care treatments

Interventions

Interventions will consist of 4 classes of standard of care treatments, namely, lifestyle modifications, complementary and alternative medicine (CAM) therapies, prescription medications, or adjustment of anti-cancer therapy.

Standard of Care Intervention

Eligibility Criteria

Age18 Years+
Sexall
Healthy VolunteersNo
Age GroupsAdult (18-64), Older Adult (65+)

You may qualify if:

  • Patients over the age of 18 who have histologically confirmed breast cancer, of any stage
  • Patients experiencing vasomotor symptoms
  • While the study is intended to evaluate the feasibility of the MyChart platform, patients without a MyChart account, who are interested in participating in the study, will have access to a paper or electronic email version. As participation in the MyChart program has benefits outside of this intended study, all patients without a MyChart account will be encouraged to sign up for the service

You may not qualify if:

  • Those who are unable to complete questionnaires in English

Contact the study team to confirm eligibility.

Sponsors & Collaborators

Study Sites (1)

The Ottawa Hospital Cancer Centre

Ottawa, Ontario, Canada

Location

Related Publications (4)

  • Cole KM, Clemons M, McGee S, Alzahrani M, Larocque G, MacDonald F, Liu M, Pond GR, Mosquera L, Vandermeer L, Hutton B, Piper A, Fernandes R, Emam KE. Using machine learning to predict individual patient toxicities from cancer treatments. Support Care Cancer. 2022 Sep;30(9):7397-7406. doi: 10.1007/s00520-022-07156-6. Epub 2022 May 25.

    PMID: 35614153BACKGROUND
  • Hutton B, Hersi M, Cheng W, Pratt M, Barbeau P, Mazzarello S, Ahmadzai N, Skidmore B, Morgan SC, Bordeleau L, Ginex PK, Sadeghirad B, Morgan RL, Cole KM, Clemons M. Comparing Interventions for Management of Hot Flashes in Patients With Breast and Prostate Cancer: A Systematic Review With Meta-Analyses. Oncol Nurs Forum. 2020 Jul 1;47(4):E86-E106. doi: 10.1188/20.ONF.E86-E106.

    PMID: 32555553BACKGROUND
  • Cole KM, Clemons M, Alzahrani M, Larocque G, MacDonald F, Vandermeer L, Hutton B, Piper A, Pond G, McGee S. Developing patient-centred strategies to optimize the management of vasomotor symptoms in breast cancer patients: a survey of health care providers. Breast Cancer Res Treat. 2021 Jul;188(2):343-350. doi: 10.1007/s10549-021-06186-8. Epub 2021 Jun 22.

    PMID: 34159473BACKGROUND
  • Cole KM, McGee S, Clemons M, Liu M, MacDonald F, Vandermeer L, Ng TL, Pond G, Emam KE. Development and application of a weighted change score to evaluate interventions for vasomotor symptoms in patients with breast cancer using regression trees: a cohort study. Breast Cancer Res Treat. 2024 Sep;207(2):313-321. doi: 10.1007/s10549-024-07360-4. Epub 2024 May 19.

Related Links

MeSH Terms

Conditions

Breast Neoplasms

Condition Hierarchy (Ancestors)

Neoplasms by SiteNeoplasmsBreast DiseasesSkin DiseasesSkin and Connective Tissue Diseases

Study Officials

  • Sharon McGee, MD

    The Ottawa Hospital Cancer Centre

    PRINCIPAL INVESTIGATOR

Study Design

Study Type
interventional
Phase
phase 4
Allocation
NA
Masking
NONE
Purpose
SUPPORTIVE CARE
Intervention Model
SINGLE GROUP
Sponsor Type
OTHER
Responsible Party
SPONSOR

Study Record Dates

First Submitted

December 15, 2021

First Posted

February 3, 2022

Study Start

February 25, 2022

Primary Completion

July 22, 2022

Study Completion

September 22, 2022

Last Updated

December 18, 2025

Record last verified: 2025-12

Locations