Reduced Time to Breast Cancer Diagnosis with Coordination of Radiological and Clinical Care
Bibliographic record
Abstract
Introduction Diagnostic delays for breast problems is a current concern in British Columbia and diagnostic pathways for breast cancer are currently under review. Breast centres have been introduced in Europe and reported to facilitate diagnosis and treatment. Guidelines for breast centers are outlined by the European Society for Mastology (EUSOMA). A Rapid Access Breast Clinic (RABC) was developed at our hospital applying the concept of triple evaluation for all patients and navigation between clinicians and radiologists. We hypothesize that the Rapid Access Breast Clinic will decrease wait times to diagnosis and minimize duplication of services compared to usual care. Methods A retrospective review was undertaken looking at diagnostic wait times and the number of diagnostic centres involved for consecutive patients seen by breast surgeons with diagnostic workups performed either in the traditional system (TS) or the RABC. Only patients presenting with a new breast problem were included in the study. Results Patients seen at the RABC had a decreased time to surgical consultation (33 vs 86 days, p<0.0001) for both malignant (36 vs 59 days, p=0.0007) and benign diagnoses (31 vs 95 days, p<0.0001). Furthermore, 13% of the patients referred to the surgeon in the TS without a diagnosis were eventually diagnosed with a malignancy and waited a mean of 84 days for initial surgical assessment. Of the patients seen at the RABC, 5% required investigation at more than one institution compared to 39% patients seen in the TS (p<0.0001). Cancer patients had a shorter time from presentation to surgery in the RABC (64 vs 92 days, p=0.009). Conclusion The establishment of the RABC has significantly reduced the time to surgical consultation, time to breast cancer surgery, and duplication of investigations for patients with benign and malignant breast complaints. It is feasible to introduce a EUSOMA-based breast clinic in the Canadian Health Care System and improvements in diagnostic wait times are seen. We recommend the expansion of coordinated care to other sites.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".