Abstract P2-13-08: Comparison of Compliance to Anti Estrogen Therapy in Patients with Early Breast Cancer followed at Tertiary Centers versus Through Family Physicians and Primary Surgeons: A Practice Review
Bibliographic record
Abstract
Abstract Background: Poor adherence or non-compliance to pharmacologic therapies in chronic diseases is a major clinical problem. Adherence to adjuvant anti-estrogen therapies among patients with early breast cancer (EBC) is variable as reported in different clinical trials. Cancer centres, at present, frequently refer patients with EBC on adjuvant anti-estrogen therapy back to their surgeons and family doctors for follow up. In order to find any difference in compliance for such patients, we reviewed patients followed by their primary surgeons and family doctors (peripheral cohort) for adherence and compared them to patients regularly followed in the cancer center (central cohort). Patients and Methods: Women with EBC receiving anti-estrogen therapy were identified from breast cancer database at London Regional Cancer Program LRCP). A standardized telephone interview was conducted with patients. We assumed that adherence in the central cohort will be 20% higher than the peripheral cohort. Patient are considered adherent if they took more than 80%, Non-adherent if they took less than 50% and semi-adherent if they took 50–80% of the prescribed medication. Results: We recruited a total of 160 patients (80 patients in each cohort). Seventy seven (96.3%) patients in central cohort were compliant and 76 (95%) patients were compliant in the peripheral cohort. The HR was 0.7 (p >.999) Conclusion: From our retrospective review, we did not observe any significant difference in the adherence to adjuvant anti-estrogen therapy in patients with EBC. The present process of discharging such patients to surgeons and family physicians for follow up does not seem to affect their compliance. Citation Information: Cancer Res 2012;72(24 Suppl):Abstract nr P2-13-08.
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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 | 0.005 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".