Diagnostic and Prognostic Value of Antibodies and Soluble Biomarkers in Undifferentiated Peripheral Inflammatory Arthritis: A Systematic Review
Bibliographic record
Abstract
OBJECTIVE: When patients present with undifferentiated peripheral inflammatory arthritis (UPIA), early diagnosis and evaluation of prognostic factors are decisive steps for therapeutic success. We reviewed published evidence on the diagnostic and prognostic performance of autoantibodies and soluble biomarkers in UPIA. METHODS: We conducted a systematic literature search covering studies published until January 2009. Additionally, we screened conference abstracts presented at European League Against Rheumatism and American College of Rheumatology meetings in 2007 and 2008. RESULTS: We included 52 full-text articles and 12 abstracts. The association of anti-cyclic citrullinated peptide antibody (anti-CCP) and rheumatoid factor (RF) with diagnosis of rheumatoid arthritis at followup is compelling, supported by positive likelihood ratios (LR+) ranging between 1.2 and 20.5 for anti-CCP and 1.1 to 13.5 for RF. The same applies to radiographic outcome. For antikeratin antibodies (AKA) and antiperinuclear factor, existing evidence suggests diagnostic usefulness; AKA also showed prognostic value. Diagnostic and prognostic evidence for other autoantibodies and for bone and cartilage biomarkers was scarce, negative, or controversial. CONCLUSION: Among serological tests, unanimous evidence of substantial diagnostic value exists only for anti-CCP and RF, but is scarce for other markers.
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 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 | 0.005 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.004 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".