Serum Biomarkers in Bullous Pemphigoid: A Systematic Review
Bibliographic record
Abstract
Introduction: Bullous pemphigoid (BP) is the most common type of subepidermal blistering disease, usually observed in the elderly population, with a mean age of presentation between 66 and 83 years. BP is a psychosocially ladened disease, with many patients experiencing negative body image, social isolation, and depression. The identification and validation of biomarkers in BP may further the understanding of disease pathogenesis, provide objective measures in assessing efficacy in clinical trials, and identify new targets for targeted therapy. Methods/Results: Two databases (Medline and Embase) were searched from database inception to September 2023. All published articles reporting on biomarker levels of BP patients in serum compared to healthy controls were included. A total of 877 unique articles were identified, resulting in the inclusion of 62 case-control studies reporting on a total of 1837 patients and 140 unique biomarkers. Biomarkers were categorized into T-cell mediated, B-cell mediated, innate immune system, and coagulation cascade pathway. The most notable biomarkers identified include increases in anti-BP180/230 immunoglobulin (Ig)G/E, total IgE, TNF-α, B-cell activating factor, interleukin-31, eosinophil cationic protein, MMP-9, and coagulation cascade biomarker levels. The results of this review provide the greatest support for a role of anti-BP180/230 autoantibodies, T h 2 cells, eosinophils, and the coagulation cascade in the pathogenesis of BP. Conclusions: The pathogenesis of BP has an underlying autoimmune etiology centred around the production of autoantibodies against BP180/230, but increased T h 2, eosinophil and coagulation cascade activity may be contributory.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.012 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".