Characteristics of Early Paget's Disease in SQSTM1 Mutation Carriers: Baseline Analysis of the ZiPP Study Cohort
Bibliographic record
Abstract
Mutations in SQSTM1 are strongly associated with Paget's disease of bone (PDB), but little is known about the clinical characteristics of those with early disease. Radionuclide bone scans, biochemical markers of bone turnover, and clinical characteristics were analyzed in SQSTM1 mutation carriers who took part in the Zoledronic acid in the Prevention of Paget's disease (ZiPP) study. We studied 222 individuals, of whom 54.9% were female, with mean ± SE age of 50.1 ± 0.6 years. Twelve SQSTM1 mutations were observed, including p.Pro392Leu, which was present in 141 of 222 (63.5%) subjects. Bone scan examination revealed evidence of PDB in 20 subjects (9.0%), ten of whom (50%) had a single affected site. Participants with lesions were older than those without lesions but the difference was not significant (53.6 ± 9.1 versus 49.8 ± 8.9; p = .07). The mean age of participants with lesions was not significantly different from the age at which their parents were diagnosed with PDB (55 years versus 59 years, p = .17). All individuals with lesions were asymptomatic. Serum concentrations of total alkaline phosphatase (ALP) normalized to the upper limit of normal in each center were higher in those with lesions (0.75 ± 0.69 versus 0.42 ± 0.29 arbitary units; p < .0001). Similar findings were observed for other biochemical markers of bone turnover, but the sensitivity of ALP and other markers in detecting lesions was poor. Asymptomatic PDB is present in about 9% of SQSTM1 mutation carriers by the fifth decade. Further follow-up of this cohort will provide important information on the natural history of early PDB and its response to treatment. © 2020 The Authors. Journal of Bone and Mineral Research published by American Society for Bone and Mineral Research.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".