A systematic review of rehabilitation and exercise recommendations in oncology guidelines
Bibliographic record
Abstract
Guidelines promote high quality cancer care. Rehabilitation recommendations in oncology guidelines have not been characterized and may provide insight to improve integration of rehabilitation into oncology care. This report was developed as a part of the World Health Organization (WHO) Rehabilitation 2030 initiative to identify rehabilitation-specific recommendations in guidelines for oncology care. A systematic review of guidelines was conducted. Only guidelines published in English, for adults with cancer, providing recommendations for rehabilitation referral and assessment or interventions between 2009 and 2019 were included. 13840 articles were identified. After duplicates and applied filters, 4897 articles were screened. 69 guidelines were identified with rehabilitation-specific recommendations. Thirty-seven of the 69 guidelines endorsed referral to rehabilitation services but provided no specific recommendations regarding assessment or interventions. Thirty-two of the 69 guidelines met the full inclusion criteria and were assessed using the AGREE II tool. Twenty-one of these guidelines achieved an AGREE II quality score of ≥ 45 and were fully extracted. Guidelines exclusive to pharmacologic interventions and complementary and alternative interventions were excluded. Findings identify guidelines that recommend rehabilitation services across many cancer types and for various consequences of cancer treatment signifying that rehabilitation is a recognized component of oncology care. However, these findings are at odds with clinical reports of low rehabilitation utilization rates suggesting that guideline recommendations may be overlooked. Considering that functional morbidity negatively affects a majority of cancer survivors, improving guideline concordant rehabilitative care could have substantial impact on function and quality of life among cancer survivors.
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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 | 0.014 | 0.082 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.014 | 0.016 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".