Clinical practice guidelines for breast cancer rehabilitation
Bibliographic record
Abstract
BACKGROUND: Despite strides in early detection and management of breast cancer, the primary treatments for this disease continue to result in physical impairments for some of the nearly 3 million people diagnosed annually. Over the past decade, evidence-based clinical practice guidelines (CPGs) have been developed with goals of preventing and ameliorating these impairments. However, translation of these guidelines into clinical practice needs to be accelerated. METHODS: Relevant health science databases (2001-2011) were searched to identify CPGs on breast cancer rehabilitation for the following impairments: upper extremity restrictions, lymphedema, pain, fatigue, chemotherapy-induced peripheral neuropathy, treatment-related cardiotoxicity, bone health, and weight management. RESULTS: Recommendations from 19 relevant CPGs were first summarized by impairment within tables; commonalities across guidelines, within each impairment, were then synthesized within the article. The CPGs were rated using the Appraisal of Guidelines for Research and Evaluation II (AGREE II); wide variability was noted in rigor of development, clarity of presentation, and stakeholder involvement. The most rigorous and comprehensive of those rated was the adult cancer pain guideline from the Scottish Intercollegiate Guidelines Network. CONCLUSIONS: Based on a large body of evidence published in recent years, including randomized trials and systematic reviews, there is an urgent need for updating the guidelines on upper extremity musculoskeletal impairments and lymphedema. Furthermore, additional research is needed to provide an evidence base for developing rehabilitation guidelines on management of other impairments identified in the prospective surveillance model, eg, arthralgia.
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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 | 0.048 | 0.206 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.005 |
| Bibliometrics | 0.011 | 0.010 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.007 | 0.006 |
| Research integrity | 0.012 | 0.012 |
| Insufficient payload (model declined to judge) | 0.023 | 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".