Fontana · Journal of neurology 2021 · systematic review and dose-response meta-analysis · n=39 studies

Time-trend evolution and determinants of sex ratio in Amyotrophic Lateral Sclerosis: a dose-response meta-analysis.

Cited 31 times in the scientific literature.

Level 3 - non-randomized controlled study

Systematic review and meta-analysis of observational population-based studies

PubMed 33630135 · doi:10.1007/s00415-021-10464-2 · record verified 2026-08-28

What was done

A systematic review and meta-analysis evaluated the male-to-female sex ratio (SR) in amyotrophic lateral sclerosis (ALS) across high-quality population-based studies of European ancestral populations. Investigators extracted three sex-ratio metrics: total case counts (SR number), crude incidence (SR crude incidence), and standardized incidence (SR standardized incidence). Standard meta-analysis, dose-response meta-analysis by population age, and meta-regression were conducted across 39 included studies identified from 3,254 initial records.

What was found

ALS cases and incidence remained consistently higher in males than females: - Overall pooled male-to-female SR for case numbers: 1.28 (95% CI 1.23 to 1.32). - Overall pooled male-to-female SR for crude incidence: 1.33 (95% CI 1.29 to 1.38). - Overall pooled male-to-female SR for standardized incidence: 1.35 (95% CI 1.31 to 1.40). - Dose-response analysis revealed that SR case numbers decreased progressively with advancing age, whereas SR crude incidence exhibited a U-shaped curve relative to age.

Why it matters

These findings confirm persistent male predominance in ALS incidence and demonstrate that apparent historical convergences toward an equal sex ratio are modulated by population age structure.

Limits

The analysis was limited entirely to populations of European ancestral origin, preventing generalization to other ancestral or geographic groups. The abstract does not provide total participant counts across the 39 studies, and age effects were assessed at the aggregate study level rather than using individual patient data.

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