Elevation of Serum Immunoglobulin Free Light Chains During the Preclinical Period of Rheumatoid Arthritis
Bibliographic record
Abstract
OBJECTIVE: Immunoglobulin free light chains (FLC) represent biomarkers of B cell activity in rheumatoid arthritis (RA) and are associated with all-cause mortality in the general population. Our objective was to evaluate the relationships of serum FLC to preclinical disease, RA characteristics, and mortality in RA compared to non-RA subjects. METHODS: A population-based study in Olmsted County, Minnesota, USA, was performed by crosslinking a large cohort in the general population having available serum FLC measurements with established RA incidence and prevalence cohorts. Serum κ, λ, and total FLC and their trends relative to RA incidence were compared between RA and non-RA subjects. Regression models were used to determine the associations between FLC, disease characteristics, and mortality, testing for differential effects of FLC on mortality in RA. RESULTS: Among 16,609 subjects, 270 fulfilled the criteria for RA at the time of FLC measurement. Mean total FLC were significantly higher in RA compared to non-RA subjects (4.2 vs 3.3 mg/dl, p < 0.001). FLC became elevated 3-5 years before the clinical onset of RA and remained elevated during followup. Polyclonal FLC were found to predict higher mortality in persons with RA, though elevation to the highest decile had a relatively lower effect on mortality in RA compared to non-RA subjects. CONCLUSION: Elevation of serum FLC precedes the development of RA and may be useful in monitoring B cell activity and disease progression. FLC are associated with mortality among patients with RA as well as the general population.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".