Primary Care Continuity and Wait Times to Receiving Breast Cancer Chemotherapy: A Population-Based Retrospective Cohort Study Using CanIMPACT Data
Bibliographic record
Abstract
(1) Background: Wait times to chemotherapy are associated with morbidity and mortality in breast cancer patients; however, it is unclear how primary care physician (PCP) continuity impacts these wait times, or whether this association is different in immigrants, who experience cancer care inequities. We assessed the association between PCP continuity and the contact-to-chemotherapy interval (wait time from when a patient first presents to healthcare to the first day of receiving breast cancer chemotherapy), with a specific look at the immigrant population. (2) Methods: Population-based, retrospective cohort study of women who were diagnosed with stage I-III breast cancer in Ontario who received surgery and adjuvant chemotherapy. We used quantile regression at the median and 90th percentile to quantify the effect of PCP continuity on the contact-to-chemotherapy interval, performing a separate analysis on the immigrant population. (3) Results: Among 12,781 breast cancer patients, including 1706 immigrants, the median contact-to-chemotherapy interval (126 days) was 3.21 days shorter (95% confidence interval (CI) 0.47-5.96) in symptom-detected patients with low PCP continuity, 10.68 days shorter (95% CI 5.36-16.00) in symptom-detected patients with no baseline PCP visits and 17.43 days longer (95% CI 0.90-34.76) in screen-detected immigrants with low PCP continuity compared to the same groups with high PCP continuity. (4) Conclusions: Higher PCP continuity was not associated with a change in the contact-to-chemotherapy interval for most of our study population, but was associated with a marginally longer interval in our symptom-detected population and a shorter contact-to-chemotherapy interval in screen-detected immigrants. This highlights the importance of PCP continuity among immigrants with positive screening results. Additionally, having no PCP visits at baseline was associated with a shorter contact-to-chemotherapy interval in symptom-detected 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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".