A Single Institution Consensus on the Use of Sequential or Concurrent Hormonal Therapy for Breast Cancer Patients Receiving Radiation Therapy
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: For hormone-sensitive breast cancers, treatment with breast-conserving surgery, tamoxifen, or aromatase inhibitors, along with adjuvant radiation, is the mainstay of therapy. The ideal timing of hormonal and radiation treatment is not well defined, and there is a significant degree of practice variability between concurrent and sequential treatment regimes. This variability can cause confusion amongst the clinical team resulting in contradictory recommendations, loss of patient trust, and the potential for missed initiation of hormonal therapy. METHODS: To address this question, a systematic review of the literature was conducted and presented to the breast cancer multidisciplinary team at the London Regional Cancer Center. A three-round modified Delphi method was used to obtain a consensus on a series of a priori determined statements. RESULTS: With the currently available evidence, the consensus was that hormonal therapy should be given sequentially after radiation. This will limit potential overlapping adverse effects between hormonal therapy and radiation that may decrease completion of treatment. The sequential approach has not been associated with any harm in clinical outcomes, and there is some suggestion of increased toxicity with concurrent use. However, in patients at high risk of distant recurrence, they felt it would be reasonable to consider concurrent treatment to avoid any delay in therapy. CONCLUSION: The consensus of our institution to utilize a sequential approach will standardize the treatment decisions and reduce the risk of failing to initiate hormonal therapy. Despite the lack of level 1 evidence, the Delphi methodology did provide a high level of confidence for our group to choose the sequential approach. The consensus was developed after a review of the literature revealed that there was no clear superiority of one schedule over the other and evidence that concurrent treatment may increase adverse events.
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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 | 0.313 | 0.330 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.005 | 0.013 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".