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July 01, 2021
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Five 'distinct disease activity trajectories' identified in RA treated with tofacitinib

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Researchers have identified five distinct phenotypic subgroups based on disease trajectory among methotrexate-naïve patients with rheumatoid arthritis receiving tofacitinib, according to data published in Arthritis Care & Research.

These data, the researchers wrote, demonstrate heterogeneity among patients who are usually analyzed as a single population, with significant differences observed between the trajectory groups in some baseline variables, including sex, disease activity measures and patient-reported outcomes.

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Researchers have identified distinct phenotypic subgroups based on disease trajectory among methotrexate-naïve patients with RA receiving tofacitinib, according to data. Source: Adobe Stock

“Patients with rheumatoid arthritis exhibit wide variations in disease characteristics, sociodemographic factors, treatment adherence, and health status, which can affect response to treatment,” Vivian P. Bykerk, MD, BSc, FRCPC, of Weill Cornell Medical College, in New York, and colleagues wrote.

“Group-based trajectory modeling is one method to identify groups of patients according to their predicted response to treatment over time, that may be influenced by baseline characteristics,” they added. “Understanding patient characteristics associated with distinct disease activity trajectories may make it possible to predict responses to specific treatments at an early stage.”

Vivian P. Bykerk

To identify distinct disease activity trajectories among methotrexate-naïve patients with RA who are receiving tofacitinib (Xeljanz, Pfizer), Bykerk and colleagues conducted a post hoc analysis of the ORAL Start trial. According to the researchers, ORAL Start was a 24-month, randomized, double-blind, phase 3 study of tofacitinib, in doses of 5 mg and 10 mg twice daily, in methotrexate-naïve adults with active RA. The study completed in 2013.

For their own analysis, the Bykerk and colleagues included data from 346 methotrexate-naïve participants. They used changes in Disease Activity Score in 28 joints, erythrocyte sedimentation rate (DAS28-4[ESR]), from baseline to month 24, in group-based trajectory modeling to identify distinct disease activity trajectories. In addition, the researchers compared patient and disease characteristics, changes in radiographic progression and patient reported outcomes, and safety up to month 24 among the trajectory groups.

According to the researchers, there were five distinct disease trajectories. Starting from DAS28-4(ESR)-defined high disease activity, 28 participants progressed to remission at month 24, while 107 moved rapidly to low disease activity, 98 progressed to moderate disease activity, 46 progressed gradually to low disease activity, and 67 remained in high disease activity.

The groups who progressed to remission and rapid low disease activity generally demonstrated lower disease activity and more favorable patient-reported outcomes at baseline, compared with the other groups. Improvements in radiographic progression and patient-reported outcomes during the 24-month period were “generally consistent” with DAS28-4(ESR)-predicted disease activity trajectories, the researchers wrote. Meanwhile, adverse event rates were comparable across all five groups.

“This post hoc analysis identified phenotypic subgroups with distinct disease activity trajectories in [methotrexate]-naïve patients treated with tofacitinib, reflecting heterogeneity in patients normally analyzed as a single group,” Bykerk and colleagues wrote. “More thorough exploration of the heterogeneity of any given patient population, in terms of a pre-planned cluster analysis subsequent to the presentation of clinical trial outcomes, may help practitioners identify which patients are more likely to respond to treatment, and provide a means of matching the right patient with the right treatment.”

“Identification of distinct latent trajectory groups of patients enrolled in clinical trials could provide a better understanding of the characteristics of particular patient cohorts, further insight into the impact of treatments under investigation, inform on future trial development, and, ultimately, optimize outcomes,” they added. “Future analyses to investigate potential effect modifiers that may predispose a patient to a specific response trajectory are warranted.”