Bibliographic record
Abstract
At this year's annual meeting of the American Society of Clinical Oncology (ASCO 2016), held June 3 to 7 in Chicago, investigators discussed the latest findings in cancer research. The editors of NEJM Journal Watch Oncology and Hematology were on hand to report highlights of the conference. Here, Editor-in-Chief William J. Gradishar, MD, reviews key presentations on new breast cancer treatments. All meeting abstracts can be viewed in the ASCO meeting library). Extending Adjuvant Letrozole for Early-Stage Breast Cancer A study by Goss and colleagues presented in the Plenary session suggested that extending the duration of treatment with the aromatase inhibitor letrozole for as long as 10 years may further reduce the risk for disease recurrence in postmenopausal patients with estrogen receptor (ER)-positive, early-stage breast cancer (abstract LBA1). The data were derived from the NCI-Canada MA-17R trial, an outgrowth of the MA-17 trial, which demonstrated that after 4 to 6 years of adjuvant tamoxifen, administration of letrozole for 5 years versus placebo significantly improved disease-free survival (DFS). In MA-17R, 1918 postmenopausal patients who had received letrozole for 5 years were re-randomized to receive an additional 5 years of letrozole or placebo. At a median follow-up of 6.3 years, 165 DFS events had occurred, including 42 distant recurrences in the letrozole group and 53 distant recurrences in the placebo group. Of note, contralateral breast cancer occurred in fewer patients receiving letrozole than placebo (13 vs. 31). Overall survival (OS) was identical between the two groups. Extended letrozole therapy resulted in further reduction in the odds of a …
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.101 | 0.093 |
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".