Management of Oligometastatic Breast Cancer: An Expert Committee’s Opinion
Bibliographic record
Abstract
Patients with oligometastatic breast cancer (BC) are candidates of choice for metastasis-directed therapy (MDT). This paper summarizes the opinions of an expert committee about the management of oligometastatic BC. The experts could complete the questionnaire from 13 September 2021, to 10 October 2021, followed by a discussion. The experts were physicians working in the Province of Quebec (Canada) and specialized in BC care, including surgical oncologists, medical oncologists, and radiation oncologists. The experts provided their opinions about the context of the disease and therapeutic approach, local and systemic therapies, and the prognosis of oligometastatic BC. In addition to the expert panel's opinions about the management of oligometastatic disease per se, the experts stated that a prospective data registry should be implemented to collect data about oligometastatic BC to improve knowledge about oligometastatic BC and implement data-driven MDT. These data could also allow for the design of treatment algorithms. In conclusion, this paper presents the expert panel's opinions about the management of oligometastatic BC and highlights the needs to be met to improve the care of this condition.
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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 | 0.032 | 0.053 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.010 | 0.007 |
| Insufficient payload (model declined to judge) | 0.003 | 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; 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".