Novel methodology to discern predictors of remission and patterns of disease activity over time using rheumatoid arthritis clinical trials data

Abstract

ObjectivesTo identify predictors of remission and disease activity patterns in patients with rheumatoid arthritis (RA) using individual participant data (IPD) from clinical trials.MethodsPhase II and III clinical trials completed between 2002 and 2012 were identified by systematic literature review and contact with UK market authorisation holders. Anonymised baseline and follow-up IPD from non-biological arms were amalgamated. Multiple imputation was used to handle missing outcome and covariate information. Random effects logistic regression was used to identify predictors of remission, measured by the Disease Activity Score 28 (DAS28) at 6 months. Novel latent class mixed models characterised DAS28 over time.ResultsIPD of 3290 participants from 18 trials were included. Of these participants, 92% received methotrexate (MTX). Remission rates were estimated at 8.4%(95%CI 7.4%to9.5%) overall, 17%(95%CI 14.8%to19.4%) for MTX-naïve patients with early RA and 3.2% (95% CI 2.4% to 4.3%) for those with prior MTX exposure at entry. In prior MTX-exposed patients, lower baseline DAS28 and MTX reinitiation were associated with remission. In MTX-naïve patients, being young, white, male, with better functional and mental health, lower baseline DAS28 and receiving concomitant glucocorticoids were associated with remission. Three DAS28 trajectory subpopulations were identified in MTX-naïve and MTX-exposed patients. A number of variables were associated with subpopulation membership and DAS28 levels within subpopulations.Conclusions Predictors of remission differed between MTX-naïve and prior MTX-exposed patients at entry. Latent class mixed models supported differential non-biological therapy response, with three distinct trajectories observed in both MTX-naïve and MTX-exposed patients. Findings should be useful when designing future RA trials and interpreting results of biomarker studies.

Characterization of disease course and remission in early seropositive rheumatoid arthritis: results from the TACERA longitudinal cohort study

“…In work that we have done in RA-MAP using individual participant data from multiple clinical trials, we were also able to identify three distinct latent DAS28-ESR trajectories in both baseline methotrexate-naïve treated patients and methotrexate-exposed patients. 29 The baseline methotrexate-naïve patients in the trials reflected a relatively early in disease population which is more comparable to our TACERA cohort. It thus was reassuring that similar latent trajectory classes were identified from TACERA using both DAS28-CRP and SDAI.…”

“…To identify baseline predictors of 6-month clinical remission, a two-stage approach was adopted. In the first stage, variables, previously identified from the RA literature [25][26][27][28][29][30] as potential predictors of remission, were univariately screened (using univariate logistic regression models with a conservative screen positive p value threshold of p < 0.2). Those screened positive in the first stage were taken forward to the second stage and included in multivariate logistic regression models that additionally included baseline prescribing of (or baseline intention to prescribe and then administered within 3 months) RA medication.…”

Disease activity trajectories for early and established rheumatoid arthritis: Real-world data from a rheumatoid arthritis cohort

“…The RA-Map consortium in another study, conducted in the UK found three DAS28 trajectory classes among 3290 patients from non-biologic arms of phase II and III clinical trials between 2002 and 2012. Latent class mixed model identified differential non–biologic response with three trajectory subpopulations in both MTX-naïve and MTX-exposed patients [ 12 ].…”

Distinct patterns of disease activity over time in patients with active SLE revealed using latent class trajectory models

“…This study is the first to apply latent trajectory modelling to patients with SLE in a clinical trial setting. Patients with active SLE displayed discrete trajectories of disease Disease activity trajectories have been observed in patients with RA in both clinical trials [8] and observational cohorts [8,11,12]. The number and shape of latent class trajectories is dependent on the data and outcome measures used [9].…”

“…This approach offers the opportunity to identify unobserved groups of patients (latent classes) who display similar changes in disease activity over time. In RA, latent class models have been applied to both clinical trial data [8] and observational cohorts [9][10][11][12]. A number of these studies have identified 3 main classes with respect to disease activity; typically, a group that improves rapidly, one that shows little or no improvement and a group that either improves slowly or has an intermediate response [8,11,12].…”