CE-26 From childhood to adulthood: identifying latent classes of disease activity trajectories in childhood-onset systemic lupus erythematosus patients
Bibliographic record
Abstract
Background Although SLE patients are thought to follow different patterns of disease courses, no information is available about the longitudinal disease activity or the number of possible different disease courses. This study sought to: 1) Assess for distinguishable differences in disease activity trajectories in childhood-onset SLE (cSLE) patients; 2) Identify factors predictive of membership in different classes and 3) Assess if different disease activity trajectories are associated with different damage trajectories. Methods Single-centre longitudinal inception cohort of cSLE patients (onset < 18 years) diagnosed and followed from Jan 1985 to Sep 2011. Paediatric data was obtained from our institutional cSLE database and adult data from the Toronto Lupus database or from rheumatologists’ offices. Longitudinal disease trajectory was constructed using data from every clinic visit in the 1st 10 years after diagnosis. Longitudinal SLE activity is a latent construct that is imperfectly measured with SLE disease activity index 2000 (SLEDAI2K) and prednisone exposure. SLEDAI2K and prednisone use were then jointly modelled in a Bayesian growth mixture model (GMM). Baseline factors were tested for prediction of class membership. Results 473 patients were included. 82% were female, median age of diagnosis was 14.1 years. There were 11992 visits, 2666 patient years. 67% of the population had transferred to adult care. Mean population SLEDAI2K and prednisone trajectories of cSLE patients showed rapid decline to low activity levels within 2 years after diagnosis. Joint GMM showed 5 latent classes in this cohort of cSLE patients. Class 1 patients (6%) have chronic moderate-high disease activity, class 2 (12%) had moderate initial disease activity and continued moderate long-term prednisone use, class 3 (17%) had initial high disease activity but achieved long-term remission, class 4 (19%) had high initial disease activity but relapsed later, class 5 (45%) had chronic low-grade disease activity. Across all classes, there was chronic use of prednisone (at least 5–10 mg/day) among cSLE patients in the first 10 years after diagnosis. Baseline major organ involvement, ethnicity, age at diagnosis and the number of baseline ACR criteria predicted probability of membership in different classes. Class 1 was associated with the most average damage accrual while class 5 was not associated with significant average damage accrual even after 10 years. Conclusions cSLE patients could be sub-classified into 5 distinct classes of disease activity trajectories. Baseline and demographic factors predicted membership in the distinct disease classes. Different disease classes were associated with different patterns of damage trajectories.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".