Newborn screening in metachromatic leukodystrophy – European consensus-based recommendations on clinical management
Bibliographic record
Abstract
INTRODUCTION: Metachromatic leukodystrophy (MLD) is a rare autosomal recessive lysosomal storage disorder resulting from arylsulfatase A enzyme deficiency, leading to toxic sulfatide accumulation. As a result affected individuals exhibit progressive neurodegeneration. Treatments such as hematopoietic stem cell transplantation (HSCT) and gene therapy are effective when administered pre-symptomatically. Newborn screening (NBS) for MLD has recently been shown to be technically feasible and is indicated because of available treatment options. However, there is a lack of guidance on how to monitor and manage identified cases. This study aims to establish consensus among international experts in MLD and patient advocates on clinical management for NBS-identified MLD cases. METHODS: A real-time Delphi procedure using eDELPHI software with 22 experts in MLD was performed. Questions, based on a literature review and workshops, were answered during a seven-week period. Three levels of consensus were defined: A) 100%, B) 75-99%, and C) 50-74% or >75% but >25% neutral votes. Recommendations were categorized by agreement level, from strongly recommended to suggested. Patient advocates participated in discussions and were involved in the final consensus. RESULTS: The study presents 57 statements guiding clinical management of NBS-identified MLD patients. Key recommendations include timely communication by MLD experts with identified families, treating early-onset MLD with gene therapy and late-onset MLD with HSCT, as well as pre-treatment monitoring schemes. Specific knowledge gaps were identified, urging prioritized research for future evidence-based guidelines. DISCUSSION: Consensus-based recommendations for NBS in MLD will enhance harmonized management and facilitate integration in national screening programs. Structured data collection and monitoring of screening programs are crucial for evidence generation and future guideline development. Involving patient representatives in the development of recommendations seems essential for NBS programs.
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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 | 0.106 | 0.107 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.005 | 0.007 |
| Research integrity | 0.007 | 0.003 |
| 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".