Four Anti-dsDNA Antibody Assays in Relation to Systemic Lupus Erythematosus Disease Specificity and Activity
Bibliographic record
Abstract
OBJECTIVE: Analysis of antibodies against dsDNA is an important diagnostic tool for systemic lupus erythematosus (SLE), and changes in anti-dsDNA antibody levels are also used to assess disease activity. Herein, 4 assays were compared with regard to SLE specificity, sensitivity, and association with disease activity variables. METHODS: Cross-sectional sera from 178 patients with SLE, of which 11 were followed consecutively, from a regional Swedish SLE register were analyzed for immunoglobulin G (IgG) anti-dsDNA by bead-based multiplex assay (FIDIS; Theradig), fluoroenzyme-immunoassay (EliA; Phadia/Thermo Fisher Scientific), Crithidia luciliae immunofluorescence test (CLIFT; ImmunoConcepts), and line blot (EUROLINE; Euroimmun). All patients with SLE fulfilled the 1982 American College of Rheumatology and/or the 2012 Systemic Lupus International Collaborating Clinics (SLICC-12) classification criteria. Healthy individuals (n = 100), patients with rheumatoid arthritis (n = 95), and patients with primary Sjögren syndrome (n = 54) served as controls. RESULTS: CLIFT had the highest SLE specificity (98%) whereas EliA had the highest sensitivity (35%). When cutoff levels for FIDIS, EliA, and EUROLINE were adjusted according to SLICC-12 (i.e., double the reference limit when using ELISA), the specificity and sensitivity of FIDIS was comparable to CLIFT. FIDIS and CLIFT also showed the highest concordance (84%). FIDIS performed best regarding association with disease activity in cross-sectional and consecutive samples. Fisher's exact test revealed striking differences between methods regarding associations with certain disease phenotypes. CONCLUSION: CLIFT remains a good choice for diagnostic purposes, but FIDIS performs equally well when the cutoff is adjusted according to SLICC-12. Based on results from cross-sectional and consecutive analyses, FIDIS can also be recommended to monitor disease activity.
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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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| 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".