The association of health care contact days with economic measures in the CCTG LY.12 trial
Bibliographic record
Abstract
BACKGROUND: Given the intensive resources required to conduct economic analyses in clinical trials, a key need is identifying scalable measures of costs. Contact days-days with health care contact outside the home-may represent such a practical measure. METHODS: We conducted a secondary analysis of a trial that evaluated two pre-transplant chemotherapy regimens for lymphoma. We used trial resource use and patient-reported data to calculate contact days, direct costs, and indirect costs such as lost productivity. We assessed the association between the number of contact days and cost outcomes using linear regression models and Pearson correlation coefficients. RESULTS: Contact days were moderately correlated with direct costs (r = .47, $762/ contact day, P < .0001), and strongly correlated with direct costs in the DHAP arm (r = 0.60, $727/ contact day, P < .0001). Contact days were very weakly correlated with pooled indirect costs (r 0.19, $60/ contact day, P = .0003). Among the 3 indirect cost outcomes, the relationship was strongest with paid caregiving hours (r = 0.33, 1.8 hours/ contact day, P < .0001) and weakest for unpaid hours provided by informal care partners (r = .06, .7 hours/ contact day, P = .247). Results were robust when zeroing out costs of hospitalization in the arm receiving inpatient chemotherapy and when evaluating indirect costs among patients working full-time. CONCLUSIONS: Contact days have the potential as a surrogate measure of direct health system costs, which deserves further exploration. The weak correlation with indirect cost outcomes suggests that the extent of true patient and care partner burdens extends beyond just the number of contact days.Trial registration: ClinicalTrials.gov Identifier: NCT00078949.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".