Sex differences in biomarkers and biologic mechanisms in psoriatic diseases and spondyloarthritis
Bibliographic record
Abstract
Psoriasis and spondyloarthritis (SpA), including psoriatic arthritis (PsA), are immune-mediated inflammatory conditions that affect the skin and musculoskeletal system. Males and female patients with psoriatic disease and SpA exhibit differences in clinical presentation, disease progression, and treatment response. The underlying biological mechanisms driving these sex differences remain poorly understood. This review explores the current evidence on sex-related differences in biomarkers and biological pathways in psoriasis, PsA, and SpA. While no conclusive sex-specific biomarkers have been validated, this review highlights several sex-related differences in biomarkers and biological pathways, including differences in bone turnover markers, IL-23/IL-17 pathway activity, pro-inflammatory cytokines, and cardio-metabolic profiles that may partially contribute to the clinical differences observed between male and female patients. Sex hormones may contribute to the altered bone metabolism and immune regulation in females. To effectively identify and validate sex-specific biomarkers, there is a need to prioritize sex as a biological variable in future research. Adopting such an approach should enhance more personalized therapeutic strategies and improve management for male and female patients with psoriatic disease and SpA.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".