Patient and community preferences for treatments and health states in multiple sclerosis
Bibliographic record
Abstract
OBJECTIVE: To examine preferences for treatments and health states for patients with relapsing-remitting MS and members of the community. METHODS: A survey was developed to evaluate health-related quality-of-life measures (utilities) for three treatments and six MS health states using a utility-elicitation software package, U-Titer II. Sixty-two MS patients at two large teaching hospitals in Boston, MA, and 67 members of the general community in San Diego, CA, completed the health-related quality-of-life survey using a computer. RESULTS: Assessment of quality of life decreased as disability level of MS health states increased for both respondent groups. Respondents rated less-disabled health states relatively highly (> 0.94 for patients and > 0.89 for community respondents). Quality-of-life measures for treatments in mean utilities ranged from 0.80 to 0.96. Patients assigned higher utilities for both MS health states and treatment states than community respondents; the ratings became more disparate as health states worsened. CONCLUSIONS: On average, respondents assigned utilities to currently available treatments for MS that are comparable to those of mild to moderate stages of the disease itself. These results underscore the importance of including preferences for health states and treatment alternatives in the decision to initiate treatment for individual patients or in the evaluation of effectiveness or cost-effectiveness of these treatments in patients with MS.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".