An international case control study of risk factors for multiple sclerosis.
Bibliographic record
Abstract
Background: Recent research has raised the level of confidence in a limited number of putative environmental risk factors for multiple sclerosis (MS). While some risk factors found in early case-control studies have been confirmed in more rigorous prospective studies, these studies have not had the statistical power to examine interactions amongst these risk factors. Objective: To examine the independent and joint role of Epstein-Barr virus infection, vitamin D through diet and sunlight exposure, and smoking on the risk of MS. Methods: A case-control study that will include more than 3000 MS cases and 15,000 population controls from Norway, Italy, Sweden, Serbia and Canada is underway. A standardized questionnaire with common content for all countries that is flexible enough to accommodate the variability in risk factor distributions (for example, diet) in the different countries has been developed. Results: The questionnaire has been piloted in Norway, Serbia, Sweden and Italy on a combined total of 80 MS patients and 177 healthy subjects. Preliminary results indicate that both groups found the questions easy to understand. Findings from this pilot will be used to improve the questionnaire, reducing misclassification of exposures. Conclusions: This casecontrol study is an important step forward in MS epidemiological research and is the first of a new generation of MS etiological research focusing on selected risk factors that are individually supported in the literature and incorporating a conceptual model of their interaction. The conduct of the study in both high-risk and medium-risk countries using a common methodology is novel. The questionnaire developed in this study could be eventually adopted by researchers in other countries allowing comparison (and pooling) of data with this international initiative.
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 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 | 0.007 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".