A Review of Trastuzumab Biosimilars in Early Breast Cancer and Real World Outcomes of Neoadjuvant MYL-1401O versus Reference Trastuzumab
Bibliographic record
Abstract
The reduced cost of trastuzumab biosimilars has led to increased adoption for HER2-positive breast cancer. This review of trastuzumab biosimilars encompasses this development and real world clinical data in early breast cancer. In addition, we present a retrospective study evaluating the total pathological complete response (tpCR) rates (lack of residual invasive cancer in resected breast tissue and axillary nodes), of MYL-1401O to reference trastuzumab (TRZ) in the neoadjuvant setting for HER2+ early breast cancer (EBC) in Alberta, Canada. Neoadjuvant patients with HER2+ EBC treated with TRZ from November 2018–October 2019 and MYL-1401O from December 2019–September 2020 were identified. Logistic regression was used to control for variables potentially associated with tpCR: trastuzumab product, age, pre-operative T- and N-stage, grade, hormone receptor (HR)-status, HER2-status, chemotherapy regimen, and chemotherapy completion. tpCR was 35.6% in the MYL-1401O group (n = 59) and 40.3% in the TRZ (n = 77) group, p = 0.598. After controlling for clinically relevant variables, there was no significant difference in the odds of achieving tpCR in patients treated with TRZ versus MYL-1401O (OR 1.1, 95% CI 0.5–2.4, p = 0.850). tpCR rates were similar for patients treated with MYL-1401O compared to trastuzumab in our real world study of HER2+ neoadjuvant EBC and comparable to pivotal phase 3 trials.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".