Systematic analysis of chemotherapy agents for home-based administration.
Bibliographic record
Abstract
e14012 Background: Improvement in supportive care medications, feasibility of outpatient management, and regulatory changes have led to a dramatic shift in the primary location of chemotherapy delivery from the inpatient setting to outpatient infusion centers. Over the last decade, centers in Europe and Canada have taken the next logical step – home based chemotherapy infusion. To our knowledge there is no systematic large scale initiative that has transitioned chemotherapy to the home in the United States. In order to implement a home based chemotherapy infusion program, we systematically scored anti-neoplastic agents for ease of administration. Methods: We reviewed all anti-neoplastic agents administered at our infusion center. Characteristics of each medication that could be a barrier to home infusion were identified. These included route and duration of administration, vesicant status, emetogenic potential, and duration of stability at room temperature. Scoring was determined by a multi-disciplinary team of pharmacists and oncologists (see Table). Higher scores indicated greater potential for home administration. Results: We reviewed 100 medications. The highest possible score was 8; the lowest possible score was -4. Agents ranged with scores from 8 (fulvestrant) to -1 (dactinomycin), with a median score of 4. The mode score was 3 (24 medications). The largest factor lowering the ease of administration score was stability at room temperature; score of -2 and -1 in 19 and 18 medications respectively. Conclusions: It is feasible to administer the majority of our chemotherapeutic agents in the home setting. The biggest barrier to administration at home is stability of medications at room temperature. This issue can be addressed by transporting and storing the medication in a refrigerated container. Expectedly, injectable drugs and medications with short infusion times that are stable at room temperature would be the easiest to administer in the home. Further analysis in ongoing to assess the financial feasibility and establishment of our home based program. [Table: see text]
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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 | 0.017 | 0.075 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.018 | 0.015 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".