Twin concordance and sibling recurrence rates in multiple sclerosis
Bibliographic record
Abstract
Size and ascertainment constraints often limit twin studies to concordance comparisons between identical and fraternal twins. Here we report the final results of a longitudinal, population-based study of twins with multiple sclerosis (MS) in Canada. Bias was demonstrably minimized, and an estimated 75% of all Canadian MS twin pairs were ascertained, giving a sample sufficiently large (n = 370) to permit additional informative comparisons. Twinning was not found to affect prevalence, and twins with MS did not differ from nontwins for DR15 allele frequency nor for MS risk to their siblings. Probandwise concordance rates of 25.3% (SE +/- 4.4) for monozygotic (MZ), 5.4% (+/-2.8) for dizygotic (DZ), and 2.9% (+/-0.6) for their nontwin siblings were found. MZ twin concordance was in excess of DZ twin concordance. The excess concordance in MZ was derived primarily from like-sexed female pairs with a probandwise concordance rate of 34 of 100 (34 +/- 5.7%) compared with 3 of 79 (3.8 +/- 2.8%) for female DZ pairs. We did not demonstrate an MZ/DZ difference in males, although the sample size was small. We observed a 2-fold increase in risk to DZ twins over nontwin siblings of twins, but the difference was not significant.
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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 | 0.006 | 0.036 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".