Pertuzumab monotherapy following trastuzumab-based treatment: Activity and tolerability in patients with advanced HER2- positive breast cancer
Bibliographic record
Abstract
1022 Background: Pertuzumab binds to the dimerization epitope of the HER2 receptor, inhibits HER dimerization and signal transduction, and induces ADCC. In 2 cohorts of pts (n = 66) with HER2-positive metastatic breast cancer which had progressed during trastuzumab therapy after ≤3 lines of chemotherapy with or without trastuzumab, pertuzumab plus trastuzumab has been shown to be active (CR 7.6%, PR 16.7%, SD ≥6/12 25.8%) (Gelmon et al. ASCO 2008, Abs 1026). To assess the activity of pertuzumab monotherapy in this clinical setting, the protocol was amended to include a 3rd cohort of pts. Methods: Pt selection was not changed except that ≥1 month between the last dose of trastuzumab and study start was required. Pts received pertuzumab monotherapy. If the tumor failed to respond or responded and then progressed, trastuzumab could be added to pertuzumab. 27 pts were to be recruited to ensure that ≥24 were fully evaluable for objective response and stabilization of disease ≥6 months. Standard 21-day schedules of the antibodies were given. Results: 29 pts were recruited. Tolerability was good: the major adverse events were mild diarrhea and rash with no clinical cardiac events. To date, 2 responses have been reported, and several pts have ongoing stabilization of disease. 14 pts have received trastuzumab plus pertuzumab following inadequate response (or response then relapse) on pertuzumab monotherapy. Of these 14, 2, having progressed during trastuzumab, failed to respond to pertuzumab monotherapy but underwent confirmed response when trastuzumab was added to the pertuzumab –possibly the first report of such a phenomenon and providing good evidence of an enhanced effect when the antibodies are combined. Updated results will be presented. Conclusions: Pertuzumab monotherapy is active against HER2-positive breast cancer which has progressed during trastuzumab-based therapy. The combination of the two antibodies appears to be more active than either antibody alone. The combination is also active in patients that had failed both antibodies given separately. In clinical studies, the use of the two antibodies combined is justified. [Table: see text]
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".