Multinational Association of Supportive Care in Cancer (MASCC) clinical practice guidance for the prevention of breast cancer-related arm lymphoedema (BCRAL): international Delphi consensus-based recommendations
Bibliographic record
Abstract
Background: Developing strategies to prevent breast cancer-related arm lymphoedema (BCRAL) is a critical unmet need because there are no effective interventions to eradicate it once it reaches a chronic state. Certain strategies such as prospective surveillance programs and prophylactic lymphatic reconstruction have been reported to be effective in clinical trials. However, a large variation exists in practice based on clinician preference, organizational standards, and local resources. Methods: A two-round international Delphi consensus process was performed from February 27, 2023 to May 25, 2023 to compile opinions of 55 experts involved in the care and research of breast cancer and lymphoedema on such interventions. Findings: Axillary lymph node dissection, use of post-operative radiotherapy, relative within-arm volume increase one month after surgery, greater number of lymph nodes dissected, and high body mass index were recommended as the most important risk factors to guide selection of patients for interventions to prevent BCRAL. The panel recommended that prospective surveillance programs should be implemented to screen for and reduce risks of BCRAL where feasible and resources allow. Prophylactic compression sleeves, axillary reverse mapping and prophylactic lymphatic reconstruction should be offered for patients who are at risk for developing BCRAL as options where expertise is available and resources allow. Recommendations on axillary management in clinical T1-2, node negative breast cancer patients with 1-2 positive sentinel lymph nodes were also provided by the expert panel. Routine axillary lymph node dissection should not be offered in these patients who receive breast conservation therapy. Axillary radiation instead of axillary lymph node dissection should be considered in the same group of patients undergoing mastectomy. Interpretation: An individualised approach based on patients' preferences, risk factors for BCRAL, availability of treatment options and expertise of the healthcare team is paramount to ensure patients at risk receive preventive interventions for BCRAL, regardless of where they are receiving care. Funding: This study was not supported by any funding. RJC received investigator grant support from the Australian National Health and Medical Research Council (APP1194051).
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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 | 0.121 | 0.172 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.005 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.005 | 0.010 |
| Research integrity | 0.008 | 0.008 |
| Insufficient payload (model declined to judge) | 0.008 | 0.004 |
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".