Real-World Outcomes of Subcutaneous PHESGO® in HER2-Positive Breast Cancer: Pathological Response, Sequencing, and Safety
Bibliographic record
Abstract
Background: Subcutaneous pertuzumab and trastuzumab with hyaluronidase (PHESGO®) shorten chair time versus intravenous dual HER2 blockade, but real-world Asian data are scarce. Methods: We retrospectively reviewed 47 Asian patients with HER2-positive breast cancer treated with PHESGO® (January 2024–July 2025) across neoadjuvant, adjuvant, and metastatic settings. The primary endpoint was pathological complete response (pCR) in the neoadjuvant cohort; secondary endpoints included sequencing, safety, and metastatic activity. Results: Median age was 65 years. In the neoadjuvant cohort (n = 26), pCR was 65% (17/26). PHESGO®-first regimens achieved higher pCR than anthracycline-first regimens (85.7% vs. 41.7%; p = 0.038). Treatment was generally well tolerated: the most frequent events were dysgeusia (57%), diarrhea (38%), and rash (34%), mostly grade 1–2; one grade ≥3 event (thrombocytopenia) occurred, and no symptomatic cardiac dysfunction was observed. Adverse event profiles were broadly comparable in patients ≥ 70 versus <70 years. In metastatic disease (n = 10), objective response and disease control rates were 56% and 78%, respectively. Conclusions: In routine practice, PHESGO® showed substantial neoadjuvant activity, acceptable toxicity, and workflow advantages. Early use of subcutaneous dual HER2 blockade with taxane may enhance pCR and facilitate delivery; prospective validation is warranted.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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".