Predictive validity of NEDA in the 16- and 21-year follow-up from the pivotal trial of interferon beta-1b
Bibliographic record
Abstract
BACKGROUND: Long-term follow-up from the randomized trial of interferon beta-1b (IFNB-1b) permitted the assessment of different definitions of no evidence of disease activity (NEDA) for predicting long-term outcome in multiple sclerosis (MS). OBJECTIVE: To examine the predictive validity of different NEDA definitions. METHODS: Predictive validity for negative disability outcomes (NDOs) at 16 years and survival at 21 years post-randomization were assessed. NEDA in the first 2 years was defined as follows: clinical NEDA: no relapses or Expanded Disability Status Scale (EDSS) progression from baseline to Year 2; NEDA-3a: no relapses, no confirmed ⩾1-point EDSS progression, and no new T2-active lesions; NEDA-3b: no relapses, no EDSS progression, and no increase in T2 burden of disease (T2-BOD); and NEDA-4: no relapses, no EDSS progression, and no increase in T2-BOD or atrophy. NDOs were defined as death, need for wheelchair, EDSS ⩾6, or progressive MS. RESULTS: A total of 245 and 371 patients were evaluated at 16 and 21 years, respectively. Clinical NEDA predicted NDOs ( p = 0.0029), as did baseline EDSS ( p < 0.0001), baseline T2-BOD ( p < 0.0001), and change in T2-BOD ( p = 0.0033). IFNB-1b treatment ( p = 0.0251), relapse rate in the 2 years before study start ( p = 0.0260), T2-BOD at baseline ( p = 0.0014), and change in T2-BOD ( p = 0.0129) predicted survival at 21 years. CONCLUSION: Clinical NEDA predicted long-term disability outcome. By contrast, definitions of NEDA that included on-therapy changes in magnetic resonance imaging variables did not increase the predictive validity.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".