ECONOMIC EVALUATION OF HER2 TARGETED BREAST CANCER THERAPY
Bibliographic record
Abstract
Background and Objectives: Economic evaluation and decision analysis provide a framework to evaluate incremental costs and effects associated with alternative health interventions. These methods can also be used as a tool to evaluate alternative clinical behaviours or practice patterns. The objective of this thesis was to investigate the impact of current Canadian practices in human epidermal growth factor receptor-2 (HER2) testing to target trastuzumab in early-stage breast cancer (BC). Methods: Project 1: A systematic review of previous trastuzumab and HER2 testing economic analyses was conducted to identify methodological gaps and key lessons. Project 2: A population-level, retrospective cohort was studied to determine HER2 testing and trastuzumab treatment patterns in Ontario early-stage BC patients. Project 3: A cost-utility analysis of alternative test-treat strategies was conducted using a Markov model of BC calibrated to the Canadian setting, and incorporating Project 2 findings. Results: Project 1: Previous economic evaluations demonstrated that HER2 test accuracy and sequencing were key considerations when modelling the cost-effectiveness of trastuzumab treatment. Consideration of local testing and treatment practices was lacking. Project 2: HER2 testing and treatment practice differed from guidelines, where documentation was available. Only 88% of equivocal results were confirmed, while 57% of HER2 positive patients received trastuzumab. Project 3: Calibration of the BC model minimised gaps between trial-based survival and expected Canadian survival patterns. Deviations from guidelines in practice suggest that primary testing with fluorescence in situ hybridization (FISH) would produce greater health gains at a reduced cost vs. primary immunohistochemistry with FISH confirmation. This finding was more apparent as the prevalence of HER2 positive disease increased. Introduction of newer in situ hybridisation tests may be cost-effective as well. Conclusions: Practice deviations from guidelines are an important consideration when modelling the cost-effectiveness of trastuzumab therapy. Underlying local disease progression and prevalence can also significantly impact outcomes.
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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 | 0.027 | 0.085 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".