Multiple sclerosis incidence: A systematic review of change over time by geographical region
Bibliographic record
Abstract
BACKGROUND: The incidence of multiple sclerosis (MS) has reportedly increased over time; however, change in MS incidence has not been rigorously assessed globally. METHODS: We followed the guidelines for the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) statement. Two independent reviewers systematically searched Scopus, PubMed and Web of Science for peer-reviewed publications in English from 1 January 1985 to 24 September 2020 reporting MS incidence for at least two contiguous five-year periods with clearly-defined case ascertainment. The outcome was change in MS incidence rate according to geographical region. RESULTS: We identified 64 papers providing 65 regional estimates (including three paediatric-onset MS) across 24 countries covering ∼3% of the world's population (in 2000/1 or closest available total population for the entire country), with quality (adapted Newcastle-Ottawa Scale) ranging from sufficient to good. Studies were mainly from Italy (n=14 including San Marino), Norway (n=10) or Canada (n=9), with no studies in the Africa or South-East Asia regions. Of the 62 whole-of-population estimates, MS incidence rates: significantly increased in 38 (61%), significantly decreased in 13 (21%) and remained stable in 11 (18%). In the paediatric-onset studies, MS incidence was stable in two (67%) and increased in one (33%). Many estimates derived from only selected (often small) regions of a country. For 42 (68%) of the whole-of-population estimates (and two of the paediatric-onset estimates) a consistent case definition or diagnostic criteria over the entire study period was explicitly reported. Across the n=9 whole-of-population estimates based on a consistent case definition for the duration of the study period, and including a substantial proportion of the population of a country (≥one-third), incidence rates were stable in n=3, increased in n=3 and decreased in n=3. Studies using a consistent case definition covered ∼2.7% of the global population; incidence rates were stable in 0.9% of the global population, decreased in studies covering 1%, and increased in those covering 0.8% of the global population. CONCLUSION: The studies reporting change in MS incidence rate over time were limited by world region and the proportion of the global population covered. Although by number of studies, the predominant pattern was increasing MS incidence, in studies where a consistent case definition was used across the duration of the study and with high population coverage, no predominant pattern of MS incidence was evident.
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 | 0.012 | 0.045 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.015 | 0.016 |
| Bibliometrics | 0.012 | 0.018 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".