Ambulatory Toxicity Management (AToM) in patients receiving adjuvant or neo-adjuvant chemotherapy for early stage breast cancer - a pragmatic cluster randomized trial protocol
Bibliographic record
Abstract
BACKGROUND: Population-based studies suggest that emergency department visits and hospitalizations are common among patients receiving chemotherapy and that rates in routine practice are higher than expected from clinical trials. Chemotherapy-related toxicities are often predictable and, consequently, acute care visits may be preventable with adequate treatment planning and support between visits to the cancer centre. We will evaluate the impact of proactive telephone-based toxicity management on emergency department visits and hospitalizations in women with early stage breast cancer receiving chemotherapy. METHODS: In this pragmatic covariate constraint-based cluster randomized trial, 20 centres in Ontario, Canada are randomly allocated to either proactive telephone toxicity management (intervention) or routine care (control). The primary outcome is the cluster-level mean number of ED + H visits per patient evaluated using Ontario administrative healthcare data. Participants are all patients with early stage (I-III) breast cancer commencing adjuvant or neo-adjuvant chemotherapy at participating institutions during the intervention period. At least 25 patients at each centre participate in a patient reported outcomes sub-study involving the collection of standardized questionnaires to measure: severity of treatment toxicities, self-care, self-efficacy, quality of life, and coordination of care. Patients participating in the patient reported outcomes (PRO) sub-study are asked to provide written consent to link their PRO data to administrative data. Unit costs will be applied to each per person resource utilized, and a total cost per population and patient will be generated. An incremental cost-effectiveness analysis will be undertaken to compare the incremental costs and outcomes between the intervention and control groups from the health system perspective. DISCUSSION: This study evaluates the effectiveness of a proactive toxicity management intervention in a routine care setting. The use of administrative healthcare data to evaluate the primary outcome enables an evaluation in a real world setting and at a much larger scale than previous studies. TRIAL REGISTRATION: Clinicaltrials.gov , NCT02485678. Registered 30 June 2015.
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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 | 0.017 |
| Meta-epidemiology (narrow) | 0.005 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.004 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.036 | 0.003 |
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".