A Neuroinflammatory Biomarker Profile Associated with Neuropathic Pain in Hansen's Disease: A Systematic Review and Meta-Analysis of S100B, TNF-α, and IL-6
Bibliographic record
Abstract
Background: Neuropathic pain (NP) is a severe, chronic complication of Hansen's disease (HD), persisting after antimicrobial therapy and profoundly diminishing quality of life. Its pathophysiology is driven by persistent, complex neuroinflammatory processes within the peripheral nervous system. Circulating biomarkers, especially the glial-derived protein S100B, offer a potential objective window into this underlying pathology. This study aimed to meta-analyze the association between circulating S100B, TNF-α, and IL-6 and the presence of NP in patients with HD. Methods: A systematic search of PubMed, Scopus, and Web of Science databases was conducted for observational studies published between January 2015 and December 2025 that compared biomarker levels in HD patients with and without NP, diagnosed using validated screening instruments. Data from eligible studies were extracted independently, and methodological quality was assessed using the Newcastle-Ottawa Scale. A random-effects meta-analysis was performed to compute the pooled standardized mean difference (SMD) with 95% confidence intervals (CIs) for each biomarker. Results: Seven studies, comprising 812 patients (405 with NP, 407 without NP), met the inclusion criteria. The meta-analysis revealed that serum S100B levels were significantly elevated in HD patients with NP compared to those without (SMD = 1.28, 95% CI [0.95, 1.61], p < 0.001). This finding was accompanied by very high statistical heterogeneity (I² = 78%). Concurrently, the analysis demonstrated significantly higher circulating levels of TNF-α (SMD = 0.89, 95% CI [0.62, 1.16]) and IL-6 (SMD = 0.75, 95% CI [0.48, 1.02]) in the NP group. Conclusion: This meta-analysis establishes a strong statistical association between a distinct neuroinflammatory biomarker profile—characterized by elevated circulating S100B, TNF-α, and IL-6—and the presence of neuropathic pain in Hansen's disease. S100B, as a marker of Schwann cell distress, is a particularly relevant component of this profile. These findings underscore the pivotal role of neuroinflammation in HD-related NP, although the high heterogeneity and non-specific nature of these systemic markers necessitate a cautious interpretation regarding their immediate clinical applicability.
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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 | 0.012 | 0.026 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.040 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".