Primary Lateral Sclerosis Natural History Study: <scp>Primary Lateral Sclerosis Functional Rating Scale</scp> and Other Outcomes Assessment
Bibliographic record
Abstract
OBJECTIVE: The primary lateral sclerosis (PLS) consensus diagnostic criteria and functional rating scale (PLSFRS) were recently established to facilitate and optimize future PLS clinical trials. We examined the trajectory of the PLSFRS and other functional outcome measures and biomarkers in the PLS Natural History Study (PLS NHS) to understand their performance in this prospective cohort. METHODS: The PLS NHS is a prospective, longitudinal, multicenter study of people living with PLS in different diagnostic categories: early (disease duration <2 years); probable (2-4 years); and definite PLS (4-15 years). PLSFRS scores and other functional outcome measures were collected at baseline, 3-, 6-, 9-, and 12-month follow-up visits. Baseline characteristics were compared between the groups. The slopes of the PLSFRS and other functional outcome measures over 12 months were examined in the overall cohort and subgroups using linear mixed-effect models. The associations between baseline characteristics and the rate of PLSFRS decline were analyzed with linear regression models. RESULTS: A total of 76 participants were included: early (n = 6); probable (n = 26); and definite (n = 44) PLS. Baseline PLSFRS total scores were highest in the early PLS group, followed by the probable and definite PLS groups. In the overall cohort, the PLSFRS total score declined by 0.33 points/month (95% confidence interval [0.27-0.39], adjusted p < 0.05). The rate of decline was steepest in the early PLS group, followed by the probable and definite PLS groups. Baseline neurofilament light chain level was associated with the rate of PLSFRS decline over 1 year (p = 0.001). INTERPRETATION: In PLS, the rate of functional decline, as measured by the PLSFRS total score, is faster during the early phase of the disease. Neurofilament light might serve as a prognostic biomarker in PLS. ANN NEUROL 2026;99:418-428.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".