Health state preferences associated with subcutaneous injections and intravenous infusions for treatment of bone metastases.
Bibliographic record
Abstract
e16528 Background: Although cost utility models are often used to estimate the value of treatments for metastatic cancer, limited information is available on the utility of common treatment modalities. Bisphosphonate treatment for bone metastases (BM) is frequently administered via intravenous (IV) infusion, while a recently approved treatment to prevent skeletal-related events (SREs) of BM is administered as a subcutaneous (SC) injection. This study estimated the impact of these treatment modalities on health state (HS) preference. Methods: Participants from the UK general population completed time trade-off interviews to assess the utility of HS vignettes. Respondents first rated a HS representing cancer with BM. Subsequent HSs added descriptions of treatment modalities (ie, injection or infusion) to this basic HS. To represent a range of possible treatment experiences, the two treatment modalities were presented with and without chemotherapy (chemotx), and infusion characteristics were varied by duration (30 minutes or 2 hours) and renal monitoring. Results: A total of 121 participants completed the interviews (47.9% male, 76.9% white). Cancer with BM had a mean utility of 0.40 on a standard utility scale (1 = full health; 0 = death). Adding an injection resulted in a mean utility decrease (ie, disutility) of -0.004. The 30 minute and 2 hour infusions had mean disutilities of -0.02 and -0.04, respectively. Mean disutility of the 30 minute infusion was greater with renal monitoring (-0.05 with same-day blood draw; -0.07 with blood draw 2 days prior). Chemotx was associated with substantial disutility (-0.17). For the HS of BM with chemotx, the mean disutilities of injection, 30 minute infusion, and 2 hour infusion, were -0.02, -0.03, and -0.04, respectively. Disutility associated with injection was significantly smaller than the disutility of both the 30 minute and 2 hour infusions (p < 0.05), regardless of chemotx status. Conclusions: Respondents perceived an inconvenience with each type of BM treatment, but injections were preferred over infusions. The resulting utilities may be used in cost utility models examining the value of treatments for the prevention of SREs in patients with BM.
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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 | 0.004 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".