Conservative Intervention Strategies for Adult Cancer-Related Lymphedema: A Systematic Review and Network Meta-Analysis
Bibliographic record
Abstract
PROBLEM IDENTIFICATION: The comparative effectiveness of available management options for cancer-related secondary lymphedema is unknown. LITERATURE SEARCH: CINAHL®, Embase®, and MEDLINE® were searched for randomized trials comparing conservative treatment strategies. DATA EVALUATION: A network meta-analysis was conducted for lymphedema volume, along with pairwise meta-analyses for remaining outcomes. Evidence certainty was assessed using the GRADE (Grading of Recommendations, Assessment, Development, and Evaluation) approach. SYNTHESIS: Overall, 36 studies with a total of 1,651 participants were included. Compared to standard care, conservative treatments did not significantly reduce lymphedema volume. There was low to very low certainty evidence of benefit for several treatments on secondary outcomes. IMPLICATIONS FOR PRACTICE: There is insufficient evidence to suggest important differences between standard care and conservative treatment strategies for reducing lymphedema volume and improving lymphedema-related symptoms. SUPPLEMENTAL MATERIAL CAN BE FOUND AT HTTPS: //onf.ons.org/supplementary-material-conservative-intervention-strategies-adult-cancer-related-lymphedema.
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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 | 0.017 | 0.039 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.024 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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 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".