A systematic review on the birth prevalence of metachromatic leukodystrophy
Bibliographic record
Abstract
BACKGROUND: Metachromatic leukodystrophy (MLD) is an autosomal recessive lysosomal storage disease caused by deficiency in arylsulfatase A (ASA) activity arising primarily from ASA gene (ARSA) variants. Late-infantile, juvenile and adult clinical subtypes are defined by symptom onset at ≤ 2.5, > 2.5 to < 16 and ≥ 16 years, respectively. Epidemiological data were sought to address knowledge gaps and to inform decisions regarding the clinical development of an investigational drug. METHODS: To synthesize all available estimates of MLD incidence and birth prevalence worldwide and in selected countries, Ovid MEDLINE and Embase were searched systematically (March 11, 2022) using a population, intervention, comparator, outcome, time and setting framework, complemented by pragmatic searching to reduce publication bias. Where possible, results were stratified by clinical subtype. Data were extracted from non-interventional studies (clinical trials, non-clinical studies and case reports were excluded; reviews were used for snowballing only). RESULTS: Of the 31 studies included, 14 reported birth prevalence (13 countries in Asia-Pacific, Europe, the Middle East, North America and South America), one reported prevalence and none reported incidence. Birth prevalence per 100,000 live births ranged from 0.16 (Japan) to 1.85 (Portugal). In the three European studies with estimates stratified by clinical subtypes, birth prevalence was highest for late-infantile cases (0.31-1.12 per 100,000 live births). The distribution of clinical subtypes reported in cases diagnosed over various time periods in 17 studies varied substantially, but late-infantile and juvenile MLD accounted for at least two-thirds of cases in most studies. CONCLUSIONS: This review provides a foundation for further analysis of the regional epidemiology of MLD. Data gaps indicate the need for better global coverage, increased use of epidemiological measures (e.g. prevalence estimates) and more stratification of outcomes by clinical and genetic disease subtype.
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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 | 0.007 | 0.036 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.007 |
| Bibliometrics | 0.018 | 0.018 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".