Abstract P3-12-11: Provincial variation in utilization of adjuvant chemotherapy regimens in early stage breast cancer: Data from the cancer care Ontario new drug funding program (NDFP)
Bibliographic record
Abstract
Abstract Objectives: Recent improvements in breast cancer mortality are partly due to increased utilization of appropriate systemic therapy in early stage disease. The objectives of this study were to 1. review utilization of the most effective adjuvant breast cancer regimens across Ontario, 2. identify regions where there are variations from best practices. Methods: We used data from the Ontario NDFP to determine the utilization of 8 drug regimens approved for early stage breast cancer in each of the 14 provincial local health integration networks (LHINs). The NDFP funds the use of new and expensive cancer drugs; over 90% of all cancer treatments are funded through this mechanism. In Ontario, there were an estimated 9000 new cases of breast cancer in 2011. The analysis was restricted to patients with early stage, Her2 negative breast cancer treated in 2011-12. Data were obtained from individual cancer clinics in each LHIN. We estimate that data collection was >95% complete for these regimens. Results: 3375 women were treated with an NDFP regimen. Across the province, the most commonly used regimen was FEC-D (43%), followed by TC (23%) and ddACT (21%). The remaining regimens (AC-Docetaxel, ACT q 3 wks, CEF, FEC and AC-weekly P) were used in less than 5% of cases. However, there was important regional variation. In LHIN A, ACT q 3 wks was used in 42% of cases, and no patients received FEC-D. In LHIN P, TC was used in 40% of cases. In LHIN R, only 6% of patients received FEC-D, whereas 63% received ddACT. Utilization of Adjuvant Chemo Regimens n = 3375 AC-DocetaxelddACT q2wksACT q3wksAC-weekly PCEF/FECTCFEC-DLHIN K212004109241LHIN J3417101545212LHIN Q12000640104LHIN D1530732568165LHIN V57120031027LHIN R5188390104018LHIN P2246184111115LHIN B35311182795LHIN C0588002326LHIN A0132581120LHIN H2410189109LHIN T510425466038LHIN M1011318319175263LHIN S1715004728Total (%)128 (4)708 (21)156 (5)37 (1)139 (4)766 (23)1441 (43) Conclusion: The ACT q3 wks and TC regimens are widely used. This is of concern as they are likely less effective than FEC-D or ddACT. Factors such as tumour stage, geographic distance from treatment centre and private insurance coverage for supportive care medications may also affect choice of regimen. Consensus guidelines for the adjuvant systemic therapy of breast cancer in Ontario are being developed, along with a knowledge translation strategy to disseminate the results. Citation Information: Cancer Res 2013;73(24 Suppl): Abstract nr P3-12-11.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.001 | 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".