Wait Times from Presentation to Treatment for Colorectal Cancer: A Population-Based Study
Bibliographic record
Abstract
BACKGROUND: The wait time from cancer diagnosis to treatment has been a recent focus of cancer care in Canada. OBJECTIVE: To examine the trends in wait times from patient presentation to treatment (overall health system wait time [OWT]) for colorectal cancer (CRC). METHODS: Patients with colorectal adenocarcinomas, diagnosed between 2001 and 2005, and their first definitive treatments were identified from the population-based Manitoba Cancer Registry (Winnipeg, Manitoba). By linkage to Manitoba Health and Healthy Living's administrative databases, a patient's first gastrointestinal investigation (abdominal radiological imaging, lower gastrointestinal endoscopy or fecal occult blood test) before CRC diagnosis was identified. The index contact with the health care system was estimated from the date of the visit with the physician who ordered the first gastroenterological investigation. The OWT was defined as the time from the index contact to the first treatment, while diagnostic delay was defined as the time from the index contact to the diagnosis of CRC. Multivariate Cox regression analysis was performed to determine independent predictors of OWT. RESULTS: The OWT was estimated for 2552 cases of CRC over the five years that were examined. The median OWT increased from 61 days in 2001 to 95 days in 2005 (P<0.001). Most of the increase was in diagnostic wait times (median of 44 days in 2001 versus 64 days in 2005 [P<0.001]). Year of diagnosis, older age, urban residence and diagnosis at a teaching facility were independent predictors of OWT. CONCLUSIONS: The OWT from presentation to treatment of CRC in Manitoba steadily increased between 2001 and 2005, mostly due to diagnostic delays.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".