F09 Progression of motor symptoms prior to diagnosis in HD-gene carriers
Bibliographic record
Abstract
Background Identifying sensitive, specific, and reliable indicators of disease progression in Huntington9s disease (HD) is key to selecting the appropriate population for clinical trials that assess novel treatments that may slow or delay the onset of HD9s debilitating symptoms. The PREDICT-HD study is an NIH and CHDI-funded study that began in 2001, with the goal of documenting the neurobiological and neurobehavioral changes that occur in HD-gene carriers in the period leading up to the diagnosis of HD. The PREDICT-HD study provides a rich source of data that can be mined to identify HD-gene carriers who show rapid progression in the early stages of the disease, prior to diagnosis based on their motor symptoms. Aims To identify a population of PREDICT-HD participants who show rapid progression in motor symptoms over the course of the first four years of the PREDICT-HD study, and to determine if there are specific measures that classify participants a priori. Methods The change in the Unified Huntington9s Disease Rating Scale (UHDRS) Total Motor score between Baseline and Year 4 was calculated for all PREDICT-HD participants who had completed four annual visits. A model was generated to distinguish rapid progressors from gene-carriers not showing progression utilizing the baseline motor, cognitive, and imaging data from PREDICT-HD participants. Results Examination of the inter-quartile ranges of change-from-baseline total motor scores showed that PREDICT-HD participants in the top (fourth) quartile had a change in score of approximately 14 points; the average change in the third quartile was only 5 points. The classification model that was developed included disease burden score, striatal volume, motor and cognitive variables. The model was 82.4% accurate in identifying HD-gene carriers in PREDICT-HD who showed rapid progression in their UHDRS motor scores; the model was 91.9% accurate in identifying HD-gene carriers in PREDICT-HD who did not show a substantial increase in their motor scores. Conclusions There is a population of HD-gene carriers in the PREDICT-HD study that show a rapid progression in their motor symptoms as assessed by the UHDRS Motor Subscale. We have developed a model that is highly accurate in identifying these patients. This model needs to be further refined and validated. This model may be useful in identifying HD-gene carriers for recruitment in therapeutic clinical trials.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.004 | 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".