Differences in breast cancer diagnosis by patient presentation in Ontario: a retrospective cohort study
Bibliographic record
Abstract
BACKGROUND: In Ontario, patients with breast cancer typically receive their diagnoses through the Ontario Breast Screening Program (OBSP) after an abnormal screen, through screening initiated by a primary care provider or other referring physician, or through follow-up of symptoms by patients' primary care providers. We sought to explore the association of the route to diagnosis (screening within or outside the OBSP or via symptomatic presentation) with use of OBSP-affiliated breast assessment sites (O-BAS), wait times until diagnosis or treatment, health care use and overall survival for patients with breast cancer. METHODS: In this retrospective cohort study, we used the Ontario Cancer Registry to identify adults (aged 18-105 yr) who received a diagnosis of breast cancer from 2013 to 2017. We excluded patients if they were not Ontario residents or had missing age or sex, or who died before diagnosis. We used logistic regression to evaluate factors associated with categorical variables (whether patients were or were not referred to an OBAS, whether patients were screened or symptomatic) and Cox proportional hazards regression to identify factors associated with all-cause mortality. RESULTS: Of 51 460 patients with breast cancer, 42 598 (83%) received their diagnoses at an O-BAS. Patients whose cancer was first detected through the OBSP were more likely than symptomatic patients to be given a diagnosis at an O-BAS (adjusted odds ratio 1.68, 95% confidence interval [CI] 1.57 to 1.80). Patients screened by the OBSP were given their diagnoses 1 month earlier than symptomatic patients, but diagnosis at an O-BAS did not affect the time until either diagnosis or treatment. Patients referred to an O-BAS had significantly better overall survival than those who were not referred (adjusted hazard ratio 0.73, 95% CI 0.66 to 0.80). INTERPRETATION: Patients screened through the OBSP were given their diagnoses earlier than symptomatic patients and were more likely to be referred to an O-BAS, which was associated with better survival. Our findings suggest that individuals with signs and symptoms of breast cancer would benefit from similar referral processes, oversight and standards to those used by the OBSP.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.003 | 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 teacher head, 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".