Documentation of capecitabine usage as a third-line chemotherapy option for metastatic breast cancer patients
Bibliographic record
Abstract
Objective. To document options metastatic breast cancer (MBC) patients chose for third-line chemo-therapy within the Alberta Cancer Board (ACB) between December 1995 to April 2000. To record the early market experience with capecitabine use in MBC. Methods. Treatment of MBC with a marketed taxane between December 1995 and April 2000 was reviewed. Patients were included if they were within treatment guidelines of the Alberta Cancer Board Outpatient Cancer Drug Benefit Program, and excluded if they were currently on a taxane, treated outside guidelines, or died before receiving a third-line agent. Pre- and postcapecitabine availability cohorts were used to compare prescribing patterns. Results. Before the availability of capecitabine, vinorelbine was the most prescribed third-line chemotherapy (18.8%). After its availability, cape-citabine was the most prescribed third-line chemo-therapy (44.9%). Patients experienced, in order of decreasing frequency, hand-foot syndrome, diarrhea, and nausea as side effects of capecitabine. The majority of dose changes to capecitabine were side effect-related. The first dose was decreased on average by 24.2%, and the sum of the first and second dose adjustments averaged 44.2%. For patients who have discontinued capecitabine, 66.7% were due to disease-related reasons. Conclusion. At the ACB, capecitabine is the current primary choice of third-line chemotherapy. During early experience with its usage, capecitabine was well tolerated and toxicity was adequately managed by dose adjustments. J Oncol Pharm Practice (2001) 6, 138-145.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".