Agreement Between the DAS28-CRP Assessed with 3 and 4 Variables in Patients with Rheumatoid Arthritis Treated with Biological Agents in the Daily Clinic
Bibliographic record
Abstract
OBJECTIVE: The Disease Activity Score-28-C-reactive Protein 4 [DAS28-CRP(4)] composite measure for rheumatoid arthritis (RA) is based on 4 variables: tender and swollen joint counts, CRP, and patient global assessment. DAS28-CRP(3) includes only 3 variables, because patient global assessment has been omitted. Thresholds for low and high disease activity are the same for the 2 scores. The objective of our study was to compare the 2 DAS scores and their responses on the individual patient level. METHODS: Baseline and 12-week disease activity data from 239 patients with RA treated with a biological agent were extracted from the Danish registry for biological treatment (DANBIO). Cohen's effect sizes (ES) and disease activity levels according to the DAS thresholds were assessed. The Bland-Altman method was used to examine the bias between the DAS scores and the 95% limits of agreement (LoA). RESULTS: Baseline values for DAS28-CRP(4) and DAS28-CRP(3) were 4.8 ± 1.2 and 4.6 ± 1.1, respectively. At 12 weeks, DAS28-CRP(4) had improved by -1.39 ± 1.34 (p < 0.0001). At that timepoint the bias of DAS28-CRP(3) was -0.07 (LoA -0.69, 0.55) (p < 0.0001). The bias of the DAS28-CRP(3) response was +0.21 (LoA -0.49, 0.91) (p < 0.0001). ES for DAS28-CRP(4) was 1.2 ± 1.1 versus 1.1 ± 1.1 for DAS28-CRP(3) (p < 0.0001). Compared to DAS28-CRP(4), DAS28-CRP(3) categorized 33% fewer patients as having a high level of disease activity, 8% fewer patients as good responders, and 12% more patients as nonresponders. CONCLUSION: Mean values of DAS28-CRP(4) and DAS28-CRP(3) agreed well, but in the individual patient the difference between the scores and their responses may be substantial.
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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 | 0.019 | 0.031 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".