Diagnostic delay is common among patients with hypophosphatasia: initial findings from a longitudinal, prospective, global registry
Bibliographic record
Abstract
BACKGROUND: Hypophosphatasia (HPP) is a rare, systemic disease caused by mutation(s) within the ALPL gene encoding tissue-nonspecific alkaline phosphatase (ALP). HPP has a heterogeneous presentation, which coupled with its rarity, often leads to missed/delayed diagnosis and an incomplete understanding of its natural history. To better understand the epidemiology and clinical course of HPP, including timing of diagnosis after first reported manifestation, we present baseline data for patients enrolled in the Global HPP Registry. METHODS: Data were analyzed from patients with an HPP diagnosis confirmed by low serum ALP activity and/or an ALPL pathogenic variant, regardless of prior or current treatment, according to age at enrollment (children: < 18 y; adult: ≥18 y). All analyses were descriptive. RESULTS: Of 269 patients from 11 countries enrolled January 2015-September 2017, 121 (45.0%) were children and 148 (55.0%) were adults. The majority of children and adults were female (61.2 and 73.0%, respectively) and white (57.7 and 90.0%, respectively). Children had a median (min, max) age at earliest reported HPP manifestation of 7.2 months (- 2.3 mo, 16.0 y), which was > 12 months before diagnosis at age 20.4 months (- 0.2 mo, 16.0 y). In adults, the earliest reported manifestation occurred at a median (min, max) age of 37.6 years (0.2 y, 75.2 y), which preceded age at diagnosis (47.5 years [0.2 y, 75.2 y]) by ~ 10 years. Premature loss of deciduous teeth (48.2%, age ≥ 6 mo), bone deformity (32.5%), and failure to thrive (26.7%) were most commonly reported in the HPP-related disease history of children. Pain (74.5%), orthopedic procedures and therapies (44.6%), and recurrent and poorly healing fractures (36.5%) were most commonly reported in the HPP-related disease history of adults. CONCLUSIONS: The Global HPP Registry represents the largest observational study of patients with HPP, capturing real world data. This analysis shows that diagnostic delay is common, reflecting limited awareness of HPP, and that HPP is associated with systemic manifestations across all ages. Many patients diagnosed in adulthood had HPP manifestations in childhood, highlighting the importance of taking thorough medical histories to ensure timely diagnosis. TRIAL REGISTRATION: Clinicaltrials.gov : NCT02306720 , December 2014; ENCePP.eu: EUPAS13526 , May 2016 (retrospectively registered).
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".