The cost-effectiveness of mammography-based female breast cancer screening in Canadian populations: a systematic review
Bibliographic record
Abstract
Abstract Introduction Mammography-based breast cancer screening is an important aspect of female breast cancer prevention within the Canadian healthcare system. The current literature on female breast cancer screening is largely focused on the health outcomes that result from screening. There is comparatively little data on the cost-effectiveness of the screening. Therefore, this paper sought to conduct a systematic review of the literature on the cost effectiveness of mammography-based breast cancer screening within female Canadian populations. Materials and methods A systematic review was performed in the PubMed database to identify all studies published within the last 10 years that addressed breast cancer screening and evaluate cost-effectiveness in a Canadian population. Results The search yielded five studies for inclusion, only three of which were applicable to average-risk Canadian women. The benefits of mortality reduction rose approximately linearly with costs, while costs were linearly dependent on the number of lifetime screens per woman. Moreover, triennial screening for average-risk women aged 50-69 years was found to be the most cost-effective in terms of cost per quality adjusted life year. The use of MRI in conjunction with mammography for women with the BRCA 1/2 mutation was found to be cost-effective while annual mammography-based screening for women with dense breasts was found to be cost-ineffective. Conclusion In spite of the growing interest to enhance breast cancer screening programs, analyses of the cost-effectiveness of mammography-based screening within Canadian populations are scarcely reported and have heterogeneous methodologies. The existing data suggests that Canada’s current breast cancer screening policy to screen average-risk women aged 50-74, biennially or triennially is cost-effective. These findings could be of interest to health policy makers when making decisions regarding resource allocation; however, further studies in this field are required in order to make stronger recommendations regarding cost-effectiveness.
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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 | 0.008 | 0.053 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.009 |
| Bibliometrics | 0.009 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".