Clinical Utility of Antipeptidyl Arginine Deiminase Type 4 Antibodies
Bibliographic record
Abstract
Rheumatoid factor (RF) and anticitrullinated protein antibodies (ACPA) are important biomarkers in the diagnosis of rheumatoid arthritis (RA) but leave a gap of > 50% seronegative in early RA1. In addition, there is marked clinical heterogeneity in the seropositive group, precluding the use of RF and ACPA alone as prognostic biomarkers. These characteristics drive the demand for novel diagnostic and prognostic markers in RA1. In this context, we read the recent paper by Guderud, et al on the clinical utility of antipeptidyl arginine deiminase type 4 (anti-PAD4) antibodies with great interest2. The authors studied anti-PAD4 antibodies in 745 patients with RA using a dissociation-enhanced lanthanide fluorescence immunoassay (DELFIA) and found 26% to be positive. In addition, the study also investigated the genotype of PADI4 using TaqMan assays in 945 patients and 1118 controls. Based on the results, the authors concluded that anti-PAD4 antibodies are not useful clinical biomarkers in RA. Unfortunately, there are some significant questions and concerns regarding this conclusion. Importantly, the authors did not … Address correspondence to M. Mahler, Inova Diagnostics, 9900 Old Grove Road, San Diego, California 32131-1638, USA. E-mail: mmahler{at}inovadx.com or m.mahler.job{at}web.de
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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 | 0.004 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".