Time to treatment of prostate cancer through the Calgary Prostate Institute rapid access clinic.
Bibliographic record
Abstract
PURPOSE: To determine the wait time between initial referral, biopsy, diagnosis and individual treatment modalities of prostate cancer treatment through the Calgary Prostate Institute rapid access clinic (RAC) and compare to historical data estimates in Alberta and to suggested standards. Biopsy rate, rate of confirmed prostate cancer and the distribution of treatment modality for patients seen through the RAC is included. MATERIALS AND METHODS: A non-consented, retrospective chart review of 1103 patients from the Calgary Health Region referred to the RAC between September 2005 and August 2006 was completed. RESULTS: Patients experienced a median wait time of 21 days between referral from their family doctor and prostate biopsy. A total of 31.4% of patients referred to the clinic were requested to have a prostate biopsy performed and 50.8% of biopsies resulted in confirmed prostate cancer requiring treatment. Median wait time between diagnosis and treatment for all treatment types was 52.0 days with a 90th percentile of 146.2 days. Median wait time between referral and treatment for all treatment modalities was 101 days with a 90th percentile of 187.2 days. CONCLUSION: Calgary rapid access clinic reduces wait time between referral and biopsy by 78%. Stratifying across treatment type indicates that watchful waiting is the shortest time duration and radiation with hormone therapy is the longest.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".