A core outcome set for locoregional treatment reporting in neoadjuvant systemic breast cancer treatment trials
Bibliographic record
Abstract
Accurate information about locoregional breast cancer treatments following neoadjuvant systemic therapy (NST) is essential for meaningful interpretation of oncological outcomes but reporting is currently poor. We developed a core outcome set (COS) to improve the quality and consistency of locoregional outcome reporting in breast cancer NST trials. The COS was developed in three phases according to COS-STAD guidance, with the generation of a list of relevant outcome domains, prioritisation of outcomes through two rounds of an international online multi-stakeholder Delphi survey and a consensus meeting. 159 unique locoregional outcomes were classified into 101 outcome domains for inclusion in the Delphi survey, which was completed by 470 international professionals. The final 15-item COS, which included the pre-NST surgical plan, details of surgery performed following completion of treatment and details of radiation therapy, was agreed at an in-person consensus meeting. Widespread COS implementation will improve the quality and value of future NST trials.
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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 | 0.488 | 0.541 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.008 |
| Bibliometrics | 0.016 | 0.011 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.003 | 0.012 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".