Utility of Huntington's Disease Assessments by Disease Stage: Floor/Ceiling Effects
Bibliographic record
Abstract
Introduction: An understanding of the clinimetric properties of clinical assessments, including their constraints, is critical to sound clinical study and trial design. Utilizing data from Enroll-HD—a global, prospective HD observational study and clinical research platform—we examined several well-established HD clinical assessments across all stages of disease for evidence of instrument constraints, specifically floor/ceiling effects, to inform selection of appropriate instruments for use in future studies/trials and identify gaps in instrument utility over the life-course of the disease. Material and Methods: Analyzing publicly available data from 6,614 HD gene-expansion carriers (HDGECs), we grouped participants into deciles based on baseline CAP score, which ranged from 26 to 229. We used descriptive statistics to characterize data distribution for 25 outcome measures (encompassing motor, function, cognition, and psychiatric/behavioral domains) in each CAP decile. A skewness statistic threshold of ±2 was defined a priori to indicate floor/ceiling effects. Results: We found evidence of floor/ceiling effects in the early premanifest stages of disease for most motor and function assessments (e.g., TMS, TFC) and select cognitive tasks (MMSE, Trail Making tests). Other cognitive assessments, and the HADS-SIS scales, performed well ubiquitously, with no evidence of floor/ceiling effects at any disease stage. Floor/ceiling effects were evident at every disease stage for certain assessments, including PBA-s measures. Ceiling effects were apparent for DCL from onset stages onwards, as expected. Discussion: Developing instruments sensitive to subtle differences in performance at the earlier stages of the disease spectrum, particularly in motor and function domains, is warranted.
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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 | 0.111 | 0.134 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| 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".