The Real-World Clinical Outcomes of Heavily Pretreated HER2+ and HER2-Low Metastatic Breast Cancer Patients Treated with Trastuzumab Deruxtecan at a Single Centre
Bibliographic record
Abstract
BACKGROUND: Trastuzumab deruxtecan (TDXd) is an antibody-drug conjugate that has demonstrated impressive activity in randomized controlled clinical trials in the context of patients with HER2-amplified and HER2-low metastatic breast cancer. We aimed to review the activity and adverse event profile of TDXd in heavily pretreated breast cancer patients in real practice. METHODS: We describe a single-center retrospective case series of metastatic breast cancer patients who were treated with TDXd. The outcomes of interest were the overall response rate, overall survival, progression-free survival and grade 4-5 adverse events. Objective responses and PFS were assessed in accordance with RECIST 1.1 criteria. RESULTS: We identified 38 patients treated with TDXd. Of these, 15 patients had classically defined HER2-positive (HER2+) breast cancer, 4 of whom had active central nervous system (CNS) metastases. A total of 23 patients had HER2-low breast cancer, 2 of whom had active CNS disease. Of the 33 patients evaluable for response, 21 (63%) patients had a response to treatment, including three (9%) complete responses. Outcomes were similar between patients with a HER2+ and HER2-low status, as well as in patients with or without CNS metastases. No patients experienced grade 4 or 5 toxicities, and four of thirty-eight patients (10.5%) experienced pneumonitis (two patients with grade 3 pneumonitis, one patient with grade 2 and one patient with grade 1), resulting in TDXd discontinuation for three patients (with steroid administration in two patients). CONCLUSIONS: TDXd demonstrates impressive activity with manageable adverse event profiles in this heavily pretreated population that includes patients with active CNS metastases.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".