Cost Implications of Unwarranted Imaging for Distant Metastasis in Women with Early-Stage Breast Cancer in Ontario
Bibliographic record
Abstract
INTRODUCTION: Despite the publication of multiple evidence-based guidelines recommending against routine imaging for distant metastasis in patients with early-stage (i/ii) breast cancer, such imaging is frequently performed. The present retrospective cohort study was conducted to estimate the cost of unnecessary imaging tests in women with stage i and ii breast cancer diagnosed between 1 January 2007 and 31 December 2012 in Ontario. METHODS: We obtained patient-level demographic and tumour data from a large provincial dataset. The total cost of unwarranted imaging tests (in 2015 Canadian dollars) was considered to be equal to the sum of imaging costs incurred between 2007 and 2012 and was stratified by disease stage, imaging modality, and body site. RESULTS: Of the 26,547 identified patients with early-stage breast cancer, 22,811 (85.9%) underwent at least 1 imaging test, with an average of 3.7 tests per patient (3.2 for stage i patients and 4.0 for stage ii patients) over 5 years. At least 1 imaging test was performed in 79.6% of stage i and 92.7% of stage ii patients. During a 5-year period, the cost of unwarranted imaging in patients with early-stage breast cancer ranged from CA$4,418,139 to CA$6,865,856, depending on guideline recommendations. CONCLUSIONS: Our study highlights the substantial cost of excess imaging that could be saved and re-allocated to patient care if evidence-based guidelines are followed. Future studies should assess strategies to ensure that evidence-based guidelines are followed and to increase awareness of the cost implications of nonadherence to guidelines.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".