Adjuvant trastuzumab for breast cancer outside of clinical trials: Cardiotoxicity and economic evaluation
Bibliographic record
Abstract
6585 Background: Clinical and economic evaluations of adjuvant trastuzumab (aTZ) in breast cancer (BC) are based on clinical trial outcomes. Population based studies however provide unique opportunities to examine outcomes in a real world setting. We previously examined aTZ uptake in all patients diagnosed with stage I-III BC over one year in Nova Scotia, Canada (Snow et al SABCS 2007). We now report cardiotoxic events (CE) and an economic evaluation based on our previous cohort. Methods: A retrospective chart review of all patients treated with aTZ was conducted to abstract clinical-pathological characteristics, treatment details, CEs/significant LVEF declines, and associated medical resource utilization (MRU). Cardiac risk scores (CRS) (Rastogi et al ASCO 2007) were also computed for all patients. Biserial correlation was performed to detect differences in CRS scores among subgroups. Costs associated with aTZ were based on MRU; unit costs were derived from the literature and local resources. A probabilistic model (Skedgel et al ASCO 2008) was utilized to examine the cost per quality adjusted life year gained (QALYG) at a 25-year horizon with budget impact calculated in 2009 Cdn $. Results: Of a total population of 630 patients with stage I-III BC, 37 (5.9%) received aTZ as per HERA trial treatment schedule; two (5.4%) had a CE (one death) and five (13.5%) experienced significant LVEF decline. CEs and LVEF declines were higher in patients with baseline LVEF 50–55% vs. > 55% (10% vs. 4% and 20% vs. 11%, respectively). CRS accurately predicted the observed CE rate, and was also predictive of significant LVEF decline (p = 0.056). Compared to previous estimates, the mean cost per patient of $46,070 (95%CI: $38,541-$54,422) was lower and the cost-utility of $60,439/QALYG was more favourable. Based on the observed aTZ utilization rate, a budget impact of $59.9m (95%CI: 42.5 m-79.9 m) for 2009 in Canada is expected. Conclusions: CEs and significant LVEF declines in this population based cohort appear comparable to that reported in clinical trials. Based on the aTZ costs per patient in this study, the cost-utility of aTZ is more favourable than previous estimates although the associated budget impact remains substantial. No significant financial relationships to disclose.
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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 | 0.033 | 0.073 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".