A Multicenter, Feasibility Study Exploring Self-Administration of Chemotherapy in the Home Environment: The EASE Study
Bibliographic record
Abstract
BACKGROUND: Numerous studies have investigated the feasibility of home administration of bortezomib by nurses for the management of multiple myeloma. However, the impact of patient self-administration remains largely unexplored. OBJECTIVE: The objective of this study was to evaluate the impact and feasibility of patient self-administration of subcutaneous bortezomib. METHODS: This prospective feasibility study aimed to assess the efficacy and safety of this intervention as well as quantify the impact on patients and their caregivers. Patient and caregiver satisfaction were assessed using validated questionnaires at monthly intervals. An analysis of both direct system and indirect patient costs was also conducted. RESULTS: Thirty-four patients received 1194 doses of bortezomib for self-administration over the study period. Patient self-administration was determined to have minimal impact of treatment efficacy, and with only 8 grade 3 higher adverse events occurring, there was no effect on safety since none were due to patient self-administration. Patient satisfaction with the intervention was highly rated with 99% of responses indicating that the patient would choose this clinic again. Caregiver quality of life remained stable for the duration of the intervention. Institutional cost savings totaled an estimated $CAD 1 800 000 over the trial period, while patients collectively saved an estimated $CAD 23 000. CONCLUSION AND RELEVANCE: Patient self-administration of bortezomib is efficacious, safe, cost effective, and was well received by both patients and caregivers.
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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 | 0.008 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.003 | 0.001 |
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".