Lupus & antiphospholipid syndrome
Predictors of British Isles Lupus Assessment Group-based outcomes in patients with systemic lupus erythematosus: Analysis from the Systemic Lupus International Collaborating Clinics Inception Cohort
Authors' conclusion
Baseline predictors of response in SLE can help identify patients in clinic who are less likely to respond to standard therapy.
Study context
- Population
- Patients with SLE in the SLICC international inception cohort
- Participants
- 1,492 vs 924
- Exposure
- Inception enrolment vs Active disease
- Inception enrolmentn = 1,492
- Active diseasen = 924
- Outcome
- Predictors of BILAG-based outcomes: MCR (reduction to classic BILAG C in all domains, steroid dose ≤7.5 mg and SLEDAI ≤ 4) and Improvement (≤1B score in previously active organs; no new BILAG A/B; stable or reduced steroid dose; no increase in SLEDAI)
- Follow-up
- 12 months
Methodological detailsprediction model development, international, univariate and multivariate logistic regression with Least Absolute Shrinkage and Selection Operator (LASSO), cross-validation in randomly split samples
- Prediction model development
- International
- Univariate and multivariate logistic regression with LASSO
- Cross-validation in randomly split samples
Main finding
As reported in the abstract
Prediction model performance for MCR (ROC AUC)
| Group | ROC AUC |
|---|---|
| Inception enrolment | .777 |
| Active disease | .732 |
ROC AUC
Inception enrolment.777
Active disease.732
Observational data: associations, not effects.
Further findings
| Outcome | Active disease |
|---|---|
| Prediction model performance for Improvement (ROC AUC) · 12 months | |
| ROC AUC | .574 |
Prediction model performance for Improvement (ROC AUC) · 12 months
- Models for Improvement performed poorly
Original publication
Predictors of British Isles Lupus Assessment Group-based outcomes in patients with systemic lupus erythematosus: Analysis from the Systemic Lupus International Collaborating Clinics Inception Cohort. Lupus. Published 18 July 2023. doi:10.
Composed by AI from the published abstract and checked against it. How Briefs are made →