Cost-effectiveness analysis of neoadjuvant pertuzumab and trastuzumab therapy for locally advanced, inflammatory, or early HER2-positive breast cancer in Canada
Bibliographic record
Abstract
OBJECTIVE: The NeoSphere trial demonstrated that the addition of pertuzumab to trastuzumab and docetaxel for the neoadjuvant treatment of HER2-positive locally advanced, inflammatory, or early breast cancer (eBC) resulted in a significant improvement in pathological complete response (pCR). Furthermore, the TRYPHAENA trial supported the benefit of neoadjuvant dual anti-HER2 therapy. Survival data from these trials is not yet available; however, other studies have demonstrated a correlation between pCR and improved event-free survival (EFS) and overall survival (OS) in this patient population. This study represents the first Canadian cost-effectiveness analysis of pertuzumab in the neoadjuvant treatment of HER2-positive eBC. METHODS: A cost-utility analysis (CUA) was conducted using a three health state Markov model ('event-free', 'relapsed', and 'dead'). Two separate analyses were conducted; the first considering total pCR (ypT0/is ypN0) data from NeoSphere, and the second from TRYPHAENA. Published EFS and OS data partitioned for patients achieving/not achieving pCR were used in combination with the percentage achieving pCR in the pertuzumab trials to estimate survival. This CUA included published utility values and direct medical costs including drugs, treatment administration, management of adverse events, supportive care, and subsequent therapy. To address uncertainty, a probabilistic sensitivity analysis (PSA) and alternative scenarios were explored. RESULTS: Both analyses suggested that the addition of pertuzumab resulted in increased life-years and quality-adjusted life-years (QALYs). The incremental cost per QALY ranged from $25,388 (CAD; NeoSphere analysis) to $46,196 (TRYPHAENA analysis). Sensitivity analyses further support the use of pertuzumab, with cost-effectiveness ratios ranging from $9230-$64,421. At a threshold of $100,000, the addition of pertuzumab was cost-effective in nearly all scenarios (93% NeoSphere; 79% TRYPHAENA). CONCLUSION: Given the improvement in clinical efficacy and a favorable cost per QALY, the addition of pertuzumab in the neoadjuvant setting represents an attractive treatment option for HER2-positive eBC patients.
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".