Prevalence of Screening in Patients Newly Diagnosed with Colorectal Cancer in Ontario
Bibliographic record
Abstract
OBJECTIVES: The primary objective was to determine the proportion of individuals with a new diagnosis of colorectal cancer (CRC) in Ontario in whom the cancer was screen detected. The secondary objectives were to determine the cancer stage at diagnosis and the indications for the procedure in patients who received their first colonoscopy. PATIENTS AND METHODS: Individuals admitted to a hospital with a new diagnosis of CRC were randomly selected after stratifying by hospital type (teaching or community). The Canadian Institute for Health Information's Discharge Abstract Database was used to identify individuals with a first diagnosis of CRC during calendar year (CY) 2000, and Ontario Health Insurance Plan data were used to identify people 50 to 74 years of age who had their first colonoscopy during CY 2000. Up to 20 individuals were selected for each group (CRC or colonoscopy) in each of seven randomly selected community hospitals and three randomly selected teaching hospitals. Data were abstracted from the hospital charts. RESULTS: The hospital charts of 152 patients with a new diagnosis of CRC were examined. Of the 133 patients in whom screening status could be determined, eight had screen-detected cancers (6.0%). Of the 99 patients (65% of the sample) in whom stage could be determined, 43 (43.4%) had advanced disease (tumour-node-metastasis stage III or IV) at diagnosis. The hospital charts of 184 patients who underwent their first colonoscopy were examined. Of the 175 patients in whom the indication for colonoscopy could be determined, 45 underwent the procedure for screening purposes, 10 were for diagnostic workup of anemia and 120 for evaluation of symptoms. CONCLUSIONS: The low proportion (6%) of screen-detected CRC and the high proportion of patients (43.4%) with advanced disease at diagnosis reflect the lack of an organized screening program.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".