Do Poor Prognostic Factors in Rheumatoid Arthritis Affect Treatment Choices and Outcomes? Analysis of a US Rheumatoid Arthritis Registry

J Rheumatol. 2018 Oct;45(10):1353-1360. doi: 10.3899/jrheum.171050. Epub 2018 Jul 1.

Abstract

Objective: To characterize patients with rheumatoid arthritis (RA) by number of poor prognostic factors (PPF: functional limitation, extraarticular disease, seropositivity, erosions) and evaluate treatment acceleration, clinical outcomes, and work status over 12 months by number of PPF.

Methods: Using the Corrona RA registry (January 2005-December 2015), biologic-naive patients with diagnosed RA having 12-month (± 3 mos) followup were identified and categorized by PPF (0-1, 2, ≥ 3). Changes in medication, Clinical Disease Activity Index (CDAI), and work status (baseline-12 mos) were evaluated using linear and logistic regression models.

Results: There were 3458 patients who met the selection criteria: 1489 (43.1%), 1214 (35.1%), and 755 (21.8%) had 0-1, 2, or ≥ 3 PPF, respectively. At baseline, patients with ≥ 3 PPF were older, and had longer RA duration and higher CDAI versus those with 0-1 PPF. In 0-1, 2, and ≥ 3 PPF groups, respectively, 20.9%, 23.2%, and 26.5% of patients received ≥ 1 biologic (p = 0.011). Biologic/targeted synthetic disease-modifying antirheumatic drug (tsDMARD) use was similar in patients with/without PPF (p = 0.57). After adjusting for baseline CDAI, mean (standard error) change in CDAI was -4.95 (0.24), -4.53 (0.27), and -2.52 (0.34) for 0-1, 2, and ≥ 3 PPF groups, respectively. More patients were working at baseline but not at 12-month followup in 2 (13.9%) and ≥ 3 (12.5%) versus 0-1 (7.3%) PPF group.

Conclusion: Despite high disease activity and worse clinical outcomes, number of PPF did not significantly predict biologic/tsDMARD use. This may warrant reconsideration of the importance of PPF in treat-to-target approaches.

Keywords: COHORT STUDIES; PATIENT OUTCOME ASSESSMENT; PROGNOSIS; RHEUMATOID ARTHRITIS.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Aged
  • Aged, 80 and over
  • Antirheumatic Agents / therapeutic use*
  • Arthritis, Rheumatoid / drug therapy*
  • Biological Products / therapeutic use*
  • Disease Progression
  • Female
  • Follow-Up Studies
  • Humans
  • Linear Models
  • Logistic Models
  • Male
  • Middle Aged
  • Prognosis
  • Registries
  • Severity of Illness Index
  • Treatment Outcome
  • United States

Substances

  • Antirheumatic Agents
  • Biological Products