Delayed Disease Onset Report in <scp>UK</scp> Biobank: Implications for Prodromal Studies in Parkinson's Disease
Bibliographic record
Abstract
BACKGROUND: UK Biobank (UKBB) provides extensive genetic, imaging, and health data for ~500,000 participants, enabling studies of prodromal phases of diseases like Parkinson's disease (PD). However, during analysis, we became concerned about the accuracy of diagnosis timing. OBJECTIVE: To evaluate the accuracy of PD diagnosis timing in UKBB. METHODS: We examined PD diagnosis timing using hospital, primary care, death records, and self-reported data. We assessed discrepancies between sources and identified co-occurring diagnoses recorded on the same date as PD. RESULTS: Among 3979 PD cases, 97% of the 786 participants with both self-reported and electronic health records (EHRs) reported their diagnosis earlier than recorded in the EHR, with a typical delay of 5 to 7 years. Multiple codiagnoses were often logged on the same date, suggesting retrospective or batch data entry. CONCLUSIONS: Substantial delays in PD documentation may misclassify already diagnosed individuals as prodromal. This introduces significant bias into studies of early disease markers and distorts the timing between risk factors and clinical onset. © 2025 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".