Alliance A011801 (compassHER2 RD): Postneoadjuvant T-DM1 + Tucatinib/Placebo in Patients with Residual HER2-Positive Invasive Breast Cancer
Bibliographic record
Abstract
This report describes the rationale, purpose and design of A011801 (CompassHER2 RD), an ongoing prospective, multicenter, Phase III randomized trial. Eligible patients in the United States (US) and Canada with high-risk (defined as ER-negative and/or node-positive) HER2-positive (HER2+) residual disease (RD) after a predefined course of neoadjuvant chemotherapy and HER2-directed treatment are randomized 1:1 to adjuvant T-DM1 and placebo, versus T-DM1 and tucatinib. Patients have also received adjuvant radiotherapy and/or endocrine therapy, if indicated per standard of care guidelines. The primary objective of the trial is to determine if the invasive disease-free survival (iDFS) with T-DM1 plus tucatinib is superior to iDFS with T-DM1 plus placebo; other outcomes of interest include overall survival (OS), breast cancer-free survival (BCFS), distant recurrence-free survival (DRFS), brain metastases-free survival (BMFS) and disease-free survival (DFS). Correlative biomarker, quality of life (QoL) and pharmacokinetic (PK) end points are also evaluated.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".