Prehabilitation Program for Lung and Esophageal Cancers (Boosting Recovery and Activity Through Early Wellness): Protocol for a Nonrandomized Trial (Preprint)
Bibliographic record
Abstract
BACKGROUND Cancer is the leading cause of death in Canada, responsible for 28.2% of all deaths. Based on surgical candidacy and disease status, both lung and esophageal cancer are treated through surgical resection by a thoracic surgeon. Although surgery contributes to improved outcomes, the 30-day postoperative mortality risks are as high as 10% and 2.8%, respectively. Evidence has shown that prehabilitation is a way in which patients can have improved postoperative outcomes. Prehabilitation is multimodal, often including some form of movement, nutrition, stress management, and smoking cessation. Given the complexity of the health care system, pragmatic trials are important methodological tools to assess internal validity and improve current practice under real-world conditions. Concurrently, using community resources is imperative to keep people active in their community and create sustainable programming. OBJECTIVE The Boosting Recovery and Activity Through Early Wellness (BREATHE WELL) study aims to explore the feasibility, implementation, and preliminary effectiveness of a clinically integrated, community-based, prehabilitation health coaching program. This includes nutrition, smoking cessation, sleep hygiene, and movement for individuals scheduled to undergo surgery for lung or esophageal cancer. METHODS This is a pilot, nonrandomized, pragmatic, repeated measures, mixed methods trial. We will recruit 32 participants diagnosed with lung or esophageal cancer and are scheduled to undergo surgical resection into the prehabilitation program, with 32 additional participants who decline participation to act as a control group. Participants who agree will then go through an 8-week tailored prehabilitation program (in person or virtual), covering movement, nutrition, stress management, nutrition, goal setting, and smoking cessation. They will complete 6 sessions prior to surgery and then have 4 sessions, 1×/week following surgery. Following the completion of the program, they will have 3 booster sessions via phone or Zoom (Zoom Video Communications). The primary outcome is feasibility: (1) recruitment feasibility—recruitment rate (the number of participants referred per month), enrollment rate (the number of enrolled participants divided by the number of referred participants), reasons for declining, and prehabilitation window (time between consent and surgery); and (2) intervention feasibility—adherence to the movement intervention, attrition, safety, study completion rate, and adverse events. Secondary outcomes include measures of preliminary effectiveness including patient-reported outcomes, such as well-being, fatigue, and functional measures. All measures will be assessed before, during, and after the prehabilitation program. RESULTS Enrollment has begun in January 2025, with 2 participants enrolled in the health coaching program. The full study is expected to be completed in approximately 3 years and be published in winter 2027. CONCLUSIONS This study will inform the feasibility, implementation, and preliminary effectiveness of a clinically integrated, community-based, prehabilitation program in Nova Scotia, Canada, for people scheduled to undergo curative intent surgery for lung and esophageal cancer. CLINICALTRIAL ClinicalTrials.gov NCT06354959; https://clinicaltrials.gov/study/NCT06354959 INTERNATIONAL REGISTERED REPORT PRR1-10.2196/60791
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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 | 0.029 | 0.037 |
| Meta-epidemiology (narrow) | 0.005 | 0.003 |
| Meta-epidemiology (broad) | 0.008 | 0.005 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.105 | 0.016 |
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".