Modelling long-term outcomes for patients with systemic lupus erythematosus.

BACKGROUND

New treatments for systemic lupus erythematosus (SLE) aim to improve tolerability and disease activity control over standard of care (SoC) treatment. SoC typically includes daily glucocorticoid (GC) which carries a risk of organ damage over time. This study sought to develop natural history models to identify predictors of long-term outcomes with current SoC SLE treatment.

METHODS

Generalized linear and parametric accelerated failure time survival models (GLM) and parametric accelerated failure time (AFT) survival models were designed to identify predictors of disease activity, flare rate, GC use, organ damage, and mortality beyond the first year of treatment in patients with SLE. Models were run using a longitudinal retrospective analysis of prospectively collected Toronto Lupus Cohort (TLC) study data, collected between 1997 and 2020. Covariates of clinical and statistical significance were selected by bivariate- then multi-variate regression to find the model of best fit.

FINDINGS

Of the 1255 subjects included, 89 % were female 89 % and 65 % Caucasian. Mean follow-up was 10·5 years. At first visit, 51 % of patients had moderate-to-severe disease activity (SLEDAI-2 K score ≥ 6). Mean organ damage scores gradually increased over the years following diagnosis. Median survival of the cohort was ∼35 years from study entry. In the GLM models, SLEDAI-2 K yearly average, and average GC dose were key for predicting change in SLEDAI-2 K, GC use/ dose, and flare (any/rate). Together, adjusted mean SLEDAI-2 K and GC dose were shown to be predictors of mortality and damage in at least 9 of 12 organ systems considered.

INTERPRETATION

These comprehensive, longitudinal, predictive models show that disease activity and GC use are significant predictors of organ damage and mortality in a patient population with predominantly moderate to severe SLE. This deepens understanding of SLE natural history and underscores the need for new treatment approaches that reduce disease activity and GC use with an aim to improve long-term SLE outcomes.

FUNDING

This study was funded by AstraZeneca.

Informations de copyright

Copyright © 2024. Published by Elsevier Inc.

Déclaration de conflit d'intérêts

Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: ZT, DB, JS are employees of University Health Network which received funds from AstraZeneca for this work (JS was an employee of the University Health Network at the time of this work). ZT received consulting/speaker's fees from AstraZeneca and GSK. SK, AP and SC are all employees of, and own stock in, AstraZeneca. AJ, JG, and EDH are employees of, and RO is a consultant for, Medical Decision Modeling which received funds from AstraZeneca for this work.