Endocrine and targeted manipulation of breast cancer: Summary statement for the Sixth Cambridge Conference
Bibliographic record
Abstract
The Sixth Cambridge Conference on Endocrine and Targeted Manipulation of Breast Cancer was convened in Cambridge, Massachusetts on April 30 and May 1, 2007. The purpose of this multidisciplinary meeting of leaders in clinical and basic research and patient treatment was to assess the most recent data in the field, articulate current best practices, and identify the next steps to advance both patient care and research. Topics included a review of data from major recent and ongoing trials of endocrine treatment in patients with early breast cancer and from studies combining endocrine therapy with other treatment. The current status of breast cancer prevention efforts was examined. Preclinical models of response and resistance, initial efforts to profile tumor response and resistance during endocrine therapy in patients, and new developments in pharmacogenomics were also highlighted. In this article, a synopsis of the key issues discussed, conclusions, and recommendations are summarized; these are presented at greater length in the individual articles and accompanying Open Discussions that comprise the full conference proceedings. In the 2 years since the Fifth Conference, we have gained valuable follow-up data from key trials in early breast cancer, which have helped to clarify both the efficacy and safety and tolerability of the available strategies for endocrine therapy. Observations using endocrine agents in combination with other treatment have been similarly extended. More detailed analysis of preclinical models has improved our understanding of resistance to endocrine therapy, and efforts to explore these and other mechanisms in the clinic are now underway. All of this has and continues to contribute to a growing understanding of how to optimize the use of endocrine agents in both treating and preventing breast cancer.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.010 | 0.008 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.009 | 0.011 |
| Insufficient payload (model declined to judge) | 0.019 | 0.012 |
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".