Prevalence of Monoclonal Gammopathy Among Patients with Psoriatic Arthritis
Bibliographic record
Abstract
OBJECTIVE: The occurrence of monoclonal gammopathy is common in chronic inflammatory disorders such as chronic infections and autoimmune disorders. There is limited information about the prevalence of monoclonal gammopathy in psoriatic arthritis (PsA). We investigated the prevalence, type, and associated features of monoclonal gammopathy in patients with PsA. METHODS: We performed a cross-sectional analysis of patients followed from 2008 to 2011 at the University of Toronto PsA clinic. The presence of monoclonal gammopathy was defined as the occurrence of a discrete band in the gammaglobulin region on at least 2 separate serum protein electrophoresis tests performed 6 months apart. Comparisons between patients with and those without monoclonal gammopathy were performed using t tests for continuous variables and chi-square tests for categorical variables. RESULTS: Of the 361 patients with PsA, 35 (9.7%) had evidence of monoclonal gammopathy in at least 2 separate blood tests. Seven (24%) of the 29 patients who were tested for Bence Jones protein were found to be positive. One patient was diagnosed as having multiple myeloma. Patients with monoclonal gammopathy were older (p = 0.001), had a longer duration of psoriasis (p = 0.02) and PsA (p = 0.006), were less likely to use disease-modifying antirheumatic drugs (p = 0.05), and had higher sedimentation rate (p = 0.01) and lower hemoglobin levels (p = 0.02). Patients with monoclonal gammopathy also trended toward having more active disease, with a higher active joint count (p = 0.07). CONCLUSION: Monoclonal gammopathy occurs in patients with PsA more commonly than in the general population. Its prevalence is associated with measures of disease activity and duration.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".