Colorectal cancer diagnostic pathways in Ontario
Bibliographic record
Abstract
Purpose: The purpose of this study was to differentiate diagnostic pathways in colorectal cancer in Ontario through the development of a pathway categorization scheme, and evaluate the patient-, disease-, system-related characteristics of patients and the length of the diagnostic interval across the diagnostic pathway categories. Methods: This was a cross-sectional study using an existing cohort at ICES. The study population included patients who were diagnosed with colorectal cancer in Ontario between 2009 and 2012. Cluster analysis used eleven variables that were related to patient presentation, patient visit pattern, patient symptom pattern and referral process to characterize and categorize diagnostic pathways. Chi-square test and One-way ANOVA were used to assess the association between the examined factors (age, sex, material deprivation quintile, comorbidities, and stage) and the diagnostic pathway categorization scheme. Unadjusted quantile regression was used to assess the association between the diagnostic interval length and the diagnostic pathway categorization scheme. Results: Six distinct diagnostic pathways were identified: asymptomatic pathway (N=4,494), colonoscopy pathway (N=10,066), the imaging and colonoscopy pathway (N=3,427), imaging alone pathway (N=2,238), the imaging and emergency presentation pathway (N=2,849) and no pre-diagnostic workup pathway (N=887). Patients who went through a pathway that was more adherent to diagnostic pathway guidelines (eg. asymptomatic pathway) were more likely to be younger, healthier and living in less deprived areas, and they tended to be diagnosed at an early stage with a short diagnostic interval. Patients who were female, older, living in more deprived areas and with more comorbid disease were more likely to go through pathways that were divergent from those guidelines. The length of the diagnostic interval was correlated to the number of colorectal cancer diagnosis-related visits occurring during the interval. All examined factors and the diagnostic interval were significantly associated with the pathway categorization (p<0.0001). Conclusions: This study demonstrated substantial variations in colorectal cancer diagnostic pathways in Ontario. Interventions should be designed to provide individualized and more effective diagnostic services to patients.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 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) | 0.003 | 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".