Real‐world comparative effectiveness and safety of Pertuzumab in patients with HER2+ metastatic breast cancer: A pan‐Canadian population‐based cohort study
Bibliographic record
Abstract
We assessed the comparative effectiveness and safety of pertuzumab plus trastuzumab and chemotherapy versus trastuzumab and chemotherapy for patients with HER2+ metastatic breast cancer (mBC) in Canada. We conducted a population-based retrospective study of patients receiving first-line treatment for mBC across eight Canadian provinces. Patients receiving trastuzumab and chemotherapy were historical comparators, and patients receiving pertuzumab plus trastuzumab and chemotherapy were the treatment group. Patients were followed until death or up to 5 years following the start of treatment (maximum follow-up to December 31, 2019). The primary outcome was overall survival (OS). One-year cumulative incidence and RDs were calculated for safety outcomes including hospitalization, emergency department visits, febrile neutropenia, and cardiac-related events. Propensity score matching (PSM) and inverse-probability of treatment weighting (IPTW) were applied within provinces. Individual provincial survival estimates were pooled using random effects meta-analysis. 3063 patients who received first-line treatment for mBC were identified. Median OS was higher among treatment patients compared to comparator patients in most provinces. Pertuzumab was associated with a statistically significantly lower risk of mortality (pooled HRs, PSM: 0.65, 95%CI: 0.57-0.74; IPTW: 0.65, 95% CI: 0.61-0.70). The treatment group had a lower risk of hospitalization compared to the comparator group (pooled RD: -0.05, 95% CI: [-0.09]-[-0.01]). No difference in 1-year cumulative incidence of cardiac-related events was identified between groups. Pertuzumab use in practice was associated with statistically significant improved survival without apparent safety concerns among patients with mBC. Real-world evaluations allow for assessments of publicly funded treatments to inform funding policies.
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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 | 0.005 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".