Smoking and multiple sclerosis: A systematic review and meta-analysis using the Bradford Hill criteria for causation
Bibliographic record
Abstract
BACKGROUND: Despite being one of the most common neurological disorders globally, the cause(s) of multiple sclerosis (MS) remain unknown. Cigarette smoking has been studied with regards to both the development and progression of MS. The Bradford Hill criteria for causation can contribute to a more comprehensive evaluation of a potentially causal risk factor-disease outcome relationship. The objective of this systematic review and meta-analysis was to assess the relationship between smoking and both MS risk and MS progression, subsequently applying Hill's criteria to further evaluate the likelihood of causal associations. METHODS: The Medline, EMBASE, CINAHL, PsycInfo, and Cochrane Library databases were searched for relevant studies up until July 28, 2015. A random-effects meta-analysis was conducted for three outcomes: MS risk, conversion from clinically isolated syndrome (CIS) to clinically definite multiple sclerosis (CDMS), and progression from relapsing-remitting multiple sclerosis (RRMS) to secondary-progressive multiple sclerosis (SPMS). Dose-response relationships and risk factor interactions, and discussions of mechanisms and analogous associations were noted. Hill's criteria were applied to assess causality of the relationships between smoking and each outcome. The effect of second-hand smoke exposure was also briefly reviewed. RESULTS: Smoking had a statistically significant association with both MS risk (conservative: OR/RR 1.54, 95% CI [1.46-1.63]) and SPMS risk (HR 1.80, 95% CI [1.04-3.10]), but the association with progression from CIS to CDMS was non-significant (HR 1.13, 95% CI [0.73-1.76]). Using Hill's criteria, there was strong evidence of a causal role of smoking in MS risk, but only moderate evidence of a causal association between smoking and MS progression. Heterogeneity in study designs and target populations, inconsistent results, and an overall scarcity of studies point to the need for more research on second-hand smoke exposure in relation to MS prior to conducting a detailed meta-analysis. CONCLUSION: This first review to supplement systematic review and meta-analytic methods with Hill's criteria to analyze the smoking-MS association provides evidence supporting the causal involvement of smoking in the development and progression of MS. Smoking prevention and cessation programs and policies should consider MS as an additional health risk when aiming to reduce smoking prevalence in the population.
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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 | 0.025 | 0.059 |
| Meta-epidemiology (narrow) | 0.004 | 0.003 |
| Meta-epidemiology (broad) | 0.030 | 0.064 |
| Bibliometrics | 0.010 | 0.011 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 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".