CAG‐repeat length and the age of onset in Huntington disease (HD): A review and validation study of statistical approaches
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
CAG-repeat length in the gene for HD is inversely correlated with age of onset (AOO). A number of statistical models elucidating the relationship between CAG length and AOO have recently been published. In the present article, we review the published formulae, summarize essential differences in participant sources, statistical methodologies, and predictive results. We argue that unrepresentative sampling and failure to use appropriate survival analysis methodology may have substantially biased much of the literature. We also explain why the survival analysis perspective is necessary if any such model is to undergo prospective validation. We use prospective diagnostic data from the PREDICT-HD longitudinal study of CAG-expanded participants to test conditional predictions derived from two survival models of AOO of HD. A prior model of the relationship of CAG and AOO originally published by Langbehn et al. yields reasonably accurate predictions, while a similar model by Gutierrez and MacDonald substantially overestimates diagnosis risk for all but the highest risk participants in this sample. The Langbehn et al. model appears accurate enough to have substantial utility in various research contexts. We also emphasize remaining caveats, many of which are relevant for any direct application to genetic counseling.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it