Association of No Evidence of Disease Activity With No Long-term Disability Progression in Multiple Sclerosis
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: We conducted a systematic review and meta-analysis to evaluate the relationship between no evidence of disease activity (NEDA) and no long-term disability progression on low- and high-efficacy therapy in relapsing-remitting multiple sclerosis (RRMS). METHODS: MEDLINE, Embase, and the Cochrane Database were searched from January 1, 2006, to January 26, 2021. We selected studies that evaluated NEDA-3 (no relapse, new MRI lesion, or confirmed disability progression) at 1 or 2 years and had a minimum of 4 years of follow-up for determination of disability progression. Data were extracted by 2 independent reviewers and were meta-analyzed with a random-effects model. Primary outcome of no disability progression was defined as no confirmed progression on the Expanded Disability Status Scale during follow-up. We assessed the odds ratio (OR) for no disability progression with NEDA vs evidence of disease activity (EDA). Positive predictive value (PPV) of NEDA for no disability progression was summarized for studies with prevalence of no progression >80% vs ≤80% separately. RESULTS: = 86%) for high-efficacy therapy. Among studies with prevalence of no progression at follow-up >80%, the pooled PPV for low efficacy therapy was 91% (95% CI 89%-93%) and for high-efficacy therapy was 92% (95% CI 88%-94%). Among studies with prevalence of no progression ≤80%, the pooled PPV for low-efficacy therapy was 81% (95% CI 75%-86%) and for high-efficacy therapy was 86% (95% CI 80%-90%). DISCUSSION: NEDA-3 is associated with no long-term disability progression in RRMS on both low- and high-efficacy therapies. Further studies of early composite outcome measures incorporating easily measurable biomarkers and longer follow-up may help to improve the prognostic value of NEDA-3 in RRMS. TRIAL REGISTRATION INFORMATION: International Prospective Register of Systematic Reviews Identifier: CRD42020189316.
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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 | 0.052 | 0.106 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.017 | 0.043 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".