Dataset Information

Trajectory of intensive treat-to-target disease modifying drug regimen in an observational study of an early rheumatoid arthritis cohort.

ABSTRACT:

Objectives

Studies of early rheumatoid arthritis (RA) cohorts have analysed treatment response and prognostic factors at fixed time points. However, in treat-to-target protocols, therapeutic decision-making is dynamic and responsive to disease activity over time. To determine when a minimal residual disease response target should be expected, our primary objective was to identify the time-dependent therapeutic response to combination disease modifying antirheumatic drugs (DMARDs) for 12 months. Our secondary objective determined factors affecting this response trajectory.

Design

Observational cohort.

Setting

Treat-to-target early RA clinic in Australian tertiary referral hospital.

Participants

We enrolled consecutive patients attending an early arthritis clinic with symptom duration less than 12 months, who were diagnosed with RA for the first time between 2004 and 2008. 101 met these eligibility criteria and data were available at baseline through 12 months.

Interventions

intensive DMARDs according to a treat-to-target protocol.

Primary and secondary outcome measures

We measured disease activity scores (DAS) at each visit, then analysed therapeutic response and associated factors in a time-dependent fashion over 12 months.

Results

The median DAS4vESR of 4.46 at baseline decreased 12 weeks later by 24%, while the proportion with DAS4v???2.6 increased (p<0.01). DAS4v continued to decrease over 52 weeks. DAS4v reduction of at least -0.45 at 4 weeks was predictive of DAS4v at 28 and 52 weeks. Female gender, current smoking, primary education and an interaction between baseline weight and C reactive protein (CRP) negatively impacted DAS4v reduction over 4 and 52 weeks. Time-varying effects of blood pressure, neutrophils, erythrocyte sedimentation rate and CRP also significantly influenced DAS4v over 52 weeks.

Conclusions

Time-dependent data suggest that the largest reduction of DAS4v to combination DMARDs occurs in the first month of therapy, and this predicts subsequent response. Variables known to impact long-term treatment response in RA also impacted early DAS4v response to combination DMARDs.

SUBMITTER: White D

PROVIDER: S-EPMC3731780 | biostudies-literature | 2013 Jul

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Trajectory of intensive treat-to-target disease modifying drug regimen in an observational study of an early rheumatoid arthritis cohort.

White Douglas D Pahau Helen H Duggan Emily E Paul Sanjoy S Thomas Ranjeny R

BMJ open 20130731 7

<h4>Objectives</h4>Studies of early rheumatoid arthritis (RA) cohorts have analysed treatment response and prognostic factors at fixed time points. However, in treat-to-target protocols, therapeutic decision-making is dynamic and responsive to disease activity over time. To determine when a minimal residual disease response target should be expected, our primary objective was to identify the time-dependent therapeutic response to combination disease modifying antirheumatic drugs (DMARDs) for 12 ...[more]

PMID: 23903812

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Project description:IntroductionSome patients with rheumatoid arthritis (RA) using tumor necrosis factor inhibitors (TNFi) experience inefficacy or lack of tolerability and hence switch to another TNFi (cycling) or to a therapy with another mode of action (switching). This study examined patient characteristics, prescribing patterns and treatment practice for RA in the United States.MethodsData were from the Adelphi Disease Specific Programme (Q2-Q3 2016). Rheumatologists completed a survey and patient record forms for adult patients with RA who had received ≥ 1 targeted therapy. Patients were grouped by class of first-used targeted therapy, and monotherapy vs. combination therapy. TNFi patients who received ≥ 1 targeted therapy were classified as cyclers or switchers. Univariate analyses compared patient characteristics and physician factors across the analysis groups.ResultsOverall, 631 patients received ≥ 1 targeted therapy; 535 were prescribed a TNFi as first targeted therapy, 53 a nonTNFi biologic disease-modifying antirheumatic drug (bDMARD), and 43 tofacitinib. Of 577 patients with known conventional synthetic (cs) DMARD status, 18.7% were prescribed monotherapy and 81.3% combination therapy. Combination therapy patients received significantly more concomitant medications prior to initiation of first targeted therapy than monotherapy patients (P < 0.05). The top reason for physicians to prescribe first use targeted therapy was strong overall efficacy (79.9%). Of 163 patients who progressed to second targeted therapy, 60.7% were cyclers. A lower proportion of cyclers persisted on their first use targeted therapy versus switchers (P = 0.03). The main reason physicians gave for switching patients at this stage was worsening condition (46.6%).ConclusionsMost patients were prescribed a TNFi as their first targeted therapy; over half then cycled to another TNFi. This suggests other factors may influence second use targeted treatment choice and highlights the need for greater understanding of outcomes associated with subsequent treatment choices and potential benefits of switching.

Project description:BackgroundAdjusting medication of patients with rheumatoid arthritis (RA) until predefined disease activity targets are met, i.e. Treat-to-Target (T2T), is the currently recommended treatment approach. However, not much is known about long-term cost-effectiveness of different T2T strategies.We model the 5-year costs and effects of a step-up approach (MTX mono - > MTX + csDMARD combination - > Adalimumab - > second anti-TNF) and an initial combination therapy approach (MTX + csDMARD - > MTX + csDMARD higher dose - > anti-TNFs) from the healthcare and societal perspectives, by adapting a previously validated Markov model.MethodsWe constructed a Markov model in which 3-monthly transitions between DAS28-defined health states of remission (≤2.6), low (2.6 < DAS28 ≤ 3.2), moderate (3.2 < DAS28 ≤ 5.1), and high disease activity (DAS28 > 5.1) were simulated. Modelled patients proceeded to subsequent treatments in case of non-remission at each (3-month) cycle start. In case of remission for two consecutive cycles medication was tapered, until medication-free remission was achieved. Transition probabilities for individual treatment steps were estimated using data of Dutch Rheumatology Monitoring registry Remission Induction Cohort I (step-up) and II (initial combination). Expected costs, utility, and ICER after 5 years were compared between the two strategies. To account for parameter uncertainty, probabilistic sensitivity analysis was employed through Gamma, Normal, and Dirichlet distributions. All utilities, costs, and transition probabilities were replaced by fitted distributions.ResultsOver a 5-year timespan, initial combination therapy was less costly and more effective than step-up therapy. Initial combination therapy accrued €16,226.3 and 3.552 QALY vs €20,183.3 and 3.517 QALYs for step-up therapy. This resulted in a negative ICER, indicating that initial combination therapy was both less costly and more effective in terms of utility gained. This can be explained by higher (±5%) remission percentages in initial combination strategy at all time points. More patients in remission generates less healthcare and productivity loss costs and higher utility. Additionally, higher remission percentages caused less bDMARD use in the initial combination strategy, lowering overall costs.ConclusionInitial combination therapy was found favourable over step-up therapy in the treatment of Rheumatoid Arthritis, when considering cost-effectiveness. Initial combination therapy resulted in more utility at a lower cost over 5 years.

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Project description:ObjectiveTo understand medication, lifestyle, and clinical care changes of persons with rheumatoid arthritis (RA) during the first months (March 2020 through May 2020) of the COVID-19 pandemic in the US.MethodsData were collected from adults with RA participating in FORWARD, The National Databank for Rheumatic Diseases observational registry, who answered COVID-19 web-based surveys in May 2020 and previously provided baseline characteristics and medication use prior to the US COVID-19 pandemic. We compared medication changes by disease-modifying antirheumatic drug (DMARD) exposure in logistic models that were adjusted for age, sex, comorbidities including pulmonary and cardiovascular diseases, education level, health insurance status, RA disease activity, fatigue, and polysymptomatic distress.ResultsOf 734 respondents, 221 (30%) reported medication changes. Among respondents who experienced a medication change, i.e., "medication changers/changers," glucocorticoids (GCs) were more commonly used compared to respondents who did not experience a medication change ("non-changers") (33% versus 18%). Non-hydroxychloroquine conventional DMARDs were less commonly used in changers compared to non-changers pre-COVID-19 (49% versus 62%), and changers reported more economic hardship during the COVID-19 pandemic compared to non-changers (23% versus 15%). While JAK inhibitor use was associated with the likelihood of a medication change, with an odds ratio (OR) of 1.9 (95% confidence interval [95% CI] 1.0, 3.4), only pre-COVID GC use remained a strong predictor for medication change in multivariable models (OR 3.0 [95% CI 1.9, 4.9]). Change in care was observed to have a significant association with pulmonary disease (OR 2.9 [95% CI 1.3, 6.5]), worse RA disease activity (OR 1.1 [95% CI 1.0, 1.1]), and GC use (OR 1.6 [95% CI 1.0, 2.5]). While the incidence of medication changes was the same before and after the American College of Rheumatology (ACR) guidance for the management of rheumatic disease in adult patients during the COVID-19 pandemic were first published in April 2020, self-imposed changes in medication were approximately twice as likely before publication of the guidelines, and physician-guided changes were more likely after publication.ConclusionPersons with RA in the US made substantial medication changes during the first three months of the COVID-19 pandemic, and changes among persons with RA after publication of the ACR guidance in April 2020 were made with increased physician guidance.

Dataset Information

Trajectory of intensive treat-to-target disease modifying drug regimen in an observational study of an early rheumatoid arthritis cohort.

Objectives

Design

Setting

Participants

Interventions

Primary and secondary outcome measures

Results

Conclusions

Publications

Trajectory of intensive treat-to-target disease modifying drug regimen in an observational study of an early rheumatoid arthritis cohort.

Similar Datasets

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