Establishing the Incidence and Prevalence of Multiple Sclerosis in Saskatchewan
Bibliographic record
Abstract
OBJECTIVE: To validate a case definition of multiple sclerosis (MS) using health administrative data and to provide the first province-wide estimates of MS incidence and prevalence for Saskatchewan, Canada. METHODS: We used population-based health administrative data between January 1, 1996 and December 31, 2015 to identify individuals with MS using two potential case definitions: (1) ≥3 hospital, physician, or prescription claims (Marrie definition); (2) ≥1 hospitalization or ≥5 physician claims within 2 years (Canadian Chronic Disease Surveillance System [CCDSS] definition). We validated the case definitions using diagnoses from medical records (n=400) as the gold standard. RESULTS: The Marrie definition had a sensitivity of 99.5% (95% confidence interval [CI] 92.3-99.2), specificity of 98.5% (95% CI 97.3-100.0), positive predictive value (PPV) of 99.5% (95% CI 97.2-100.0), and negative predictive value (NPV) of 97.5% (95% CI 94.4-99.2). The CCDSS definition had a sensitivity of 91.0% (95% CI 81.2-94.6), specificity of 99.0% (95% CI 96.4-99.9), PPV of 98.9% (95% CI 96.1-99.9), and NPV of 91.7% (95% CI 87.2-95.0). Using the more sensitive Marrie definition, the average annual adjusted incidence per 100,000 between 2001 and 2013 was 16.5 (95% CI 15.8-17.2), and the age- and sex-standardized prevalence of MS in Saskatchewan in 2013 was 313.6 per 100,000 (95% CI 303.0-324.3). Over the study period, incidence remained stable while prevalence increased slightly. CONCLUSION: We confirm Saskatchewan has one of the highest rates of MS in the world. Similar to other regions in Canada, incidence has remained stable while prevalence has gradually increased.
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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 | 0.007 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.018 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 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 itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
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".