A systematic review of the prevalence of Morquio A syndrome: challenges for study reporting in rare diseases
Bibliographic record
Abstract
BACKGROUND: Morquio A (MPS IVA) is a rare disease characterised by a deficiency of N-acetylgalactosamine-6 sulfatase (GALNS) and presenting with short stature, abnormal gait, cervical spine instability and shortened lifespan. PURPOSE: To prepare a systematic review of the prevalence of Morquio A in multiple countries and suggest recommendations for reporting rare diseases. METHODS: Medline, Medline In-Process, Medline Daily Update, Embase, Cochrane Database of Systematic Reviews, Cochrane Central Register of Controlled Trials, Database of Abstracts of Reviews of Effects, Health Technology Assessment Database and PROSPERO were searched from inception to October 2013 to identify relevant information on the epidemiology of Morquio A. Forty Patient Organisation Representatives (POR) and Key Opinion Leaders (KOL) across 24 countries were contacted for data. Observational studies were included and case reports were excluded. Searches were performed without date or language restriction. Two researchers independently screened and extracted data. Quality of study reporting was assessed using a checklist adapted from STROBE (STrengthening the Reporting of OBservational studies in Epidemiology). Point or birth prevalence was stratified according to diagnostic method and discussed narratively. RESULTS: In total 9,074 records were retrieved from searching and 25 studies were included for data extraction. Twenty out of 40 KOL and POR responded (50%) and 9 provided data (23%). Point prevalence of Morquio A was 1 per 926,000 in Australia, 1 per 1,872,000 in Malaysia and 1 per 599,000 in UK and Morquio (unclassified) was 1 per 323, 000 in Denmark. Birth prevalence of Morquio A (using recommended diagnostic methods) ranged from 1 per 71,000 in UAE to 1 per 500,000 in Japan. All results were compromised by poor study reporting and internal validity. CONCLUSIONS: The review highlighted that there is a misunderstanding of the definitions for prevalence and incidence in the field; that studies were poorly reported (diagnostic methods and patient characteristics) and that no suitable quality assessment tool exists. Overestimation and underestimation of prevalence data can occur. Bespoke reporting guidelines and a quality assessment tool specifically for prevalence of rare diseases are recommended.
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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 | 0.113 | 0.361 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.016 | 0.011 |
| Bibliometrics | 0.026 | 0.024 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".