Patterns of diagnosis for colorectal cancer (CRC): Screening detected versus symptomatic presentation
Bibliographic record
Abstract
1023 Background: Colorectal cancer (CRC) is a leading cause of cancer death in North America; studies have shown that screening improves survival. Conducted in British Columbia, Canada, this study was conducted to identify the proportion of screening-eligible patients with sporadic CRC who are detected by screening tests versus symptomatic presentation,and to compare baseline patient and tumor characteristics of these two groups. Methods: This retrospective cohort study identified 571 cases via the BC Cancer Registry of patients age 50 years and older presenting with first diagnosis of invasive CRC between Nov. 2002 and Apr. 2003. Patients with non-adenocarcinoma histology, HNPCC or FAP were not included. Self completed questionnaires were mailed to all patients to capture: prior screening history, screening versus symptomatic presentation, and demographic information. All respondents charts were then reviewed to corroborate screening information, and to obtain pathological information including TNM stage, grade and site (proximal versus distal colon versus rectal). Results: Of 212 eligible respondents (37% response), only 14 of 212 (6.6%) patients with a new CRC were detected via screening versus 198 of 212 (93.4%) presenting with symptoms. Respondents were average age at diagnosis 69 years, 59% male, 91% Caucasian, 37%rectal, and 18% M1 at diagnosis. No significant differences in the age, gender, ethnicity, socioeconomic status, tumour stage and site were detected between the screened versus symptomatic groups. Only 33 of 212 patients (15.6%) reported ever having a screening test. 19 of 198 cancers (9.6%) were diagnosed by symptomatic presentation despite a compliant screening history. Conclusion: Despite universal health-care access in British Columbia, only 7% of patients with a new diagnosis of CRC were detected via a screening test. Furthermore, only 15% of screening-eligible respondents have ever been screened. There were no differences in patient demographics or stage of disease at presentation but numbers in the screening cohort were limited. Significant effort is required to increase knowledge and compliance for CRC screening. No significant financial relationships to disclose.
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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 | 0.000 |
| 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 | 0.000 |
| 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".