Wearable activity monitors in oncology trials: Current use of an emerging technology
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Physical activity is an important outcome in oncology trials. Physical activity is commonly assessed using self-reported questionnaires, which are limited by recall and response biases. Recent advancements in wearable technology have provided oncologists with new opportunities to obtain real-time, objective physical activity data. The purpose of this review was to describe current uses of wearable activity monitors in oncology trials. METHODS: We searched Pubmed, Embase, and the Cochrane Central Register of Controlled Trials for oncology trials involving wearable activity monitors published between 2005 and 2016. We extracted details on study design, types of activity monitors used, and purpose for their use. We summarized activity monitor metrics including step counts, sleep and sedentary time, and time spent in moderate-to-vigorous activity. RESULTS: We identified 41 trials of which 26 (63%) involved cancer survivors (post-treatment) and 15 trials (37%) involved patients with active cancer. Most trials (65%) involved breast cancer patients. Wearable activity monitors were commonly used in exercise (54%) or behavioral (29%) trials. Cancer survivors take between 4660 and 11,000 steps/day and those undergoing treatment take 2885 to 8300steps/day. CONCLUSION: Wearable activity monitors are increasingly being used to obtain objective measures of physical activity in oncology trials. There is potential for their use to expand to evaluate and predict clinical outcomes such as survival, quality of life, and treatment tolerance in future studies. Currently, there remains a lack of standardization in the types of monitors being used and how their data are being collected, analyzed, and interpreted. PRECIS: Recent advancements in wearable activity monitor technology have provided oncologists with new opportunities to monitor their patients' daily activity in real-world settings. The integration of wearable activity monitors into cancer care will help increase our understanding of the associations between physical activity and the prevention and management of the disease, in addition to other important cancer outcomes.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.052 | 0.098 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.023 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it