A systematic review and meta‐analysis of clinical variables used in Huntington disease research
Bibliographic record
Abstract
Treatment effect in Huntington disease (HD) clinical trials has relied on primary outcome measures such as total motor score or functional rating scales. However, these measures have limited sensitivity, particularly in pre- to early stages of the disease. We performed a systematic review of HD clinical studies to identify endpoints that correlate with disease severity. Using standard HD keywords and terms, we identified 749 published studies from 1993 to 2011 based on the availability of demographic, biochemical, and clinical measures. The average and variability of each measure was abstracted and stratified according to pre-far, pre-close, early, mild, moderate, and severe HD stages. A fixed-effect meta-analysis on selected variables was conducted at various disease stages. A total of 1,801 different clinical variables and treatment outcomes were identified. Unified Huntington Disease Rating Scale (UHDRS) Motor, UHDRS Independence, and Trail B showed a trend toward separation between HD stages. Other measures, such as UHDRS Apathy, Verbal Fluency, and Symbol Digit, could only distinguish between pre- and early stages of disease and later stages, whereas other measures showed little correlation with increasing HD stages. Using cross-sectional data from published HD clinical trials, we have identified potential endpoints that could be used to track HD disease progression and treatment effect. Longitudinal studies, such as TRACK-HD, are critical for assessing the value of potential markers of disease progression for use in future HD therapeutic trials. A list of variables, references used in this meta-analysis, and database is available at http://www.cmmt.ubc.ca/research/investigators/leavitt/publications.
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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.008 | 0.002 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".