Economic Evaluation of Population-Based <i>BRCA1</i> and <i>BRCA2</i> Testing in Canada
Bibliographic record
Abstract
Importance: Population-based BRCA testing can identify many more BRCA carriers who will be missed by the current practice of BRCA testing based on family history (FH) and clinical criteria. These carriers can benefit from screening and prevention, potentially preventing many more breast and ovarian cancers and deaths than the current practice. Objective: To estimate the incremental lifetime health outcomes, costs, and cost-effectiveness associated with population-based BRCA testing compared with FH-based testing in Canada. Design, Setting, and Participants: For this economic evaluation, a Markov model was developed to compare the lifetime costs and outcomes of BRCA1/BRCA2 testing for all general population women aged 30 years compared with FH-based testing. BRCA carriers are offered risk-reducing salpingo-oophorectomy to reduce their ovarian cancer risk and magnetic resonance imaging (MRI) and mammography screening, medical prevention, and risk-reducing mastectomy to reduce their breast cancer risk. The analyses were conducted from both payer and societal perspectives. This study was conducted from October 1, 2022, to February 20, 2024. Main Outcomes and Measures: Outcomes of interest were ovarian cancer, breast cancer, additional heart disease deaths, and incremental cost-effectiveness ratio ICER per quality-adjusted life-year (QALY). One-way and probabilistic-sensitivity-analyses (PSA) were undertaken to explore the uncertainty. Results: In the simulated cohort of 1 000 000 women aged 30 years in Canada, the base case ICERs of population-based BRCA testing were CAD $32 276 (US $23 402.84) per QALY from the payer perspective or CAD $16 416 (US $11 903.00) per QALY from the societal perspective compared with FH-based testing, well below the established Canadian cost-effectiveness thresholds. Population testing remained cost-effective for ages 40 to 60 years but not at age 70 years. The results were robust for multiple scenarios, 1-way sensitivity, and PSA. More than 99% of simulations from payer and societal perspectives were cost-effective on PSA (5000 simulations) at the CAD $50 000 (US $36 254.25) per QALY willingness-to-pay threshold. Population-based BRCA testing could potentially prevent an additional 2555 breast cancers and 485 ovarian cancers in the Canadian population, corresponding to averting 196 breast cancer deaths and 163 ovarian cancer deaths per 1 000 000 population. Conclusions and Relevance: In this economic evaluation, population-based BRCA testing was cost-effective compared with FH-based testing in Canada from payer and societal perspectives. These findings suggest that changing the genetic testing paradigm to population-based testing could prevent thousands of breast and ovarian cancers.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.002 | 0.003 |
| 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".