A Personalized Physical Activity Program With Activity Trackers and a Mobile Phone App for Patients With Metastatic Breast Cancer: Protocol for a Single-Arm Feasibility Trial
Bibliographic record
Abstract
BACKGROUND: About 5% of breast cancer cases are metastatic at diagnosis, and 20%-30% of localized breast cancer cases become secondarily metastatic. Patients frequently report many detrimental symptoms related to metastasis and treatments. The physical, biological, psychological, and clinical benefits of physical activity during treatment in patients with localized breast cancer have been demonstrated; however, limited literature exists regarding physical activity and physical activity behavior change in patients with metastatic breast cancer. OBJECTIVE: The primary objective of this study is to assess the feasibility of a 6-month physical activity intervention with activity trackers in patients with metastatic breast cancer (the Advanced stage Breast cancer and Lifestyle Exercise, ABLE Trial). Secondary objectives are to examine the effects of physical activity on physical, psychological, anthropometrics, clinical, and biological parameters. METHODS: We plan to conduct a single-center, single-arm trial with 60 patients who are newly diagnosed with metastatic breast cancer. Patients will receive an unsupervised and personalized 6-month physical activity program that includes an activity tracker Nokia Go and is based on the physical activity recommendation. Patients will be encouraged to accumulate at least 150 minutes per week of moderate-to-vigorous intensity physical activity. Baseline and 6-month assessments will include anthropometric measures, functional tests (eg, 6-minute walk test and upper and lower limb strength), blood draws, patient-reported surveys (eg, quality of life and fatigue), and clinical markers of tumor progression (eg, Response Evaluation Criteria In Solid Tumors criteria). RESULTS: Data collection occurred between October 2016 and January 2018, and the results are expected in August 2018. CONCLUSIONS: The ABLE Trial will be the first study to assess the feasibility and effectiveness of an unsupervised and personalized physical activity intervention performed under real-life conditions with activity trackers in patients with metastatic breast cancer. TRIAL REGISTRATION: ClinicalTrials.gov NCT03148886; https://clinicaltrials.gov/ct2/show/NCT03148886 (Accessed by WebCite at http://www.webcitation.org/71yabi0la). REGISTERED REPORT IDENTIFIER: RR1-10.2196/10487.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.016 | 0.013 |
| Meta-epidemiology (narrow) | 0.005 | 0.003 |
| Meta-epidemiology (broad) | 0.008 | 0.004 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.051 | 0.011 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".