Changes in Neurologic Disability and Health-Related Quality of Life Utility Over 8 Years in Patients with Multiple Sclerosis (P1.389)
Bibliographic record
Abstract
Background: Understanding the effectiveness and cost-effectiveness of MS treatments requires better evidence of the relation between changes in neurological disability and changes on utility measures of patient-reported health-related quality of life (HRQoL). The Expanded Disability Status Scale (EDSS) remains the primary measure of MS-related neurologic disability. The Health Utilities Index Mark III (HUI3) is a validated HRQoL utility measure for MS patients. Objective: To evaluate the impact of changes in EDSS on the HUI3 in a representative clinic-attending MS sample over 8 years. Methods: From 2006-2014, the EDSS and HUI3 were collected for 2,036 patients attending the Dalhousie MS Research Unit; the sole MS care clinic and provider of disease-modifying therapies in Nova Scotia, Canada. A series of multilevel growth curve models examined changes in HUI3 in relation to changes in EDSS, controlling for sex, age, and education. EDSS scores were examined in raw form and with various EDSS endpoints. Relapsing-remitting (RRMS) and secondary-progressive (SPMS) patients were modeled separately. Results: We examined 11098 visits. At baseline assessment, 77[percnt] of the sample was female; average age was 46 years. On average, HUI3 declined 0.3[percnt] in RRMS patients and 0.6[percnt] in SPMS per year. Baseline EDSS and age were associated with lower HUI3 (p < 0.001). Within-person increases in EDSS by 1 point were associated with significant decreases in HUI3 (RRMS: 2.2[percnt], SPMS: 7.6[percnt]). Separate models examining EDSS endpoints indicated that reaching specific disability endpoints had a large impact on HUI3. For example, for RRMS patients, reaching EDSS 6 during the period of observation was associated with a 20[percnt] decline in HUI3; for SPMS this decline was 14[percnt]. Conclusions: Our findings illustrate that if MS treatments can delay disability progression they have the potential to substantially impact HRQoL utility. Such data are necessary for comparative cost-effectiveness analyses and resource allocation policies.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".