Bibliographic record
Abstract
TO THE EDITOR: Rabinovitch and Kavanagh seek a middle ground between the Fisher and Halsted concepts of breast cancer. They report that a meta-analysis showed a highly significant reduction in annual breast cancer mortality when patients who had undergone lumpectomy also received radiation therapy. Yet the single largest trial evaluating these treatments reported no difference in overall survival (OS) out to 20 years. Should meta-analyses always trump prospective trials? In fact, the B-06 trial can be interpreted as a confirmation of the B-04 trial. Both trials illustrate the lack of effect on OS when local control is clearly not obtained. In the case of B-04, 39% of the patients with clinically negative axillae randomly assigned to radical mastectomy had histologically positive nodes. Those randomly assigned to no axillary treatment obviously had the same incidence of histologic disease, yet only 18% ever developed clinical evidence of recurrence in the axilla. Although that subset had an inferior survival, the overall group of patients with untreated axillae had the same OS as those having the Halsted radical mastectomy. Similarly, after lumpectomy, radiation therapy reduced the local recurrence rate from 38% to 9%. Although the subsets with local recurrence did worse, the overall outcome of the total mastectomy group or the radiation therapy group was not better than the lumpectomy alone group. One fairly obvious conclusion is that pathologic margin sampling does not find all positive margins and it is the radiation therapy that helps boost local control, but this does not translate to better OS. In both trials, the group suffering locoregional recurrence does worse, but there is a danger of confusing cause and effect and interpreting this to mean that local control improves OS. The better interpretation is that some local recurrences are really a manifestation of systemic disease, and these cause the subgroup to have inferior survival. This would explain why in these trials improved local control did not improve OS. This leaves these trial results at odds with the meta analysis, but these two large randomized prospective clinical trials tested the same hypothesis in two different clinical arenas—B04 was a trial of lymph node control, B-06 was a trial of breast parenchyma. Both have provided confirmation of the Fisher hypothesis with 20and 25year follow-up.
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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 | 0.021 | 0.141 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.006 | 0.001 |
| Research integrity | 0.015 | 0.026 |
| Insufficient payload (model declined to judge) | 0.009 | 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".