title: Predictors of treatment initiation with tumor necrosis factor-α inhibitors in patients with rheumatoid arthritis.
abstract: BACKGROUND
  Introduction of biologic disease-modifying antirheumatic drugs (DMARDs) has revolutionized treatment in patients with rheumatoid arthritis (RA). However, due to substantially higher costs of biologics compared with nonbiologics, patients with less insurance generosity may have difficulty affording these agents, which may lead to potential access disparities.
  
  
  OBJECTIVE
  To identify factors affecting treatment initiation with tumor necrosis factor (TNF)-α inhibitor biologics in patients with RA.
  
  
  METHODS
  Health insurance claims data derived from Truven's MarketScan Commercial Claims and Encounters and Medicare Supplemental and Coordination of Benefits (2007-2010) were used to conduct a retrospective cohort study. Two separate cohorts of RA patients were identified: (1) monotherapy nonbiologic DMARD users and (2) combination therapy nonbiologic DMARD users. The primary outcome was TNF-α inhibitor initiation 12 months following an index inpatient or outpatient RA visit during 2008-2009. Predictors were measured 12 months pre-index and grouped into predisposing, enabling, or need factors based on Andersen's Behavior Model. Predisposing variables included age, sex, and geographic location; enabling variables included insurance-related factors such as capitation, payer type, and insurance generosity, which was defined using cost-sharing information from prescriptions filled by the patients in the previous year; and need variables included disease-related factors such as severity of RA, use of pain control medications, and presence of other comorbidities. Hierarchical logistic regression models were used to derive estimates of the impact of individual predictors.
  
  
  RESULTS
  Initiation of TNF-α inhibitors was observed in 10.31% of the monotherapy nonbiologic DMARD users (1,922 of 18,641) and 13.09% of combination nonbiologic DMARD users (983 of 7,508). Among monotherapy nonbiologic DMARD users, initiation with TNF-α inhibitors was associated with the predisposing factors of age (OR = 0.98, 95% CI = 0.97-0.98 for each year increase) and geographic region (Midwest vs. South OR = 0.83, 95% CI = 0.73-0.93; Northeast vs. South OR = 0.77, 95% CI = 0.64-0.92; and West vs. South OR = 0.86, 95% CI = 0.74-0.99); enabling factors of visit to rheumatologists (1 visit vs. no visit OR = 1.22, 95% CI = 1.01-1.46), health insurance type (commercial vs. Medicare supplemental OR = 0.79, 95% CI = 0.66-0.95), and drug benefit generosity (above average vs. poor OR = 1.16, 95% CI = 1.01-1.34 and most generous vs. poor OR = 1.21, 95% CI = 1.05-1.40); and need factors of RA severity (OR = 1.19, 95% CI = 1.14-1.23 for each unit increase in a claims-based RA severity index [CIRAS]), pre-index pain reliever use (steroids OR = 1.81, 95% CI = 1.62-2.02; nonselective nonsteroidal anti-inflammatory drugs [NSAID] OR = 1.17, 95% CI = 1.05-1.31; COX-2 inhibitors OR = 1.22, 95% CI = 1.05-1.41), and comorbidities (OR = 0.94, 95% CI = 0.90-0.99 for each unit increase in a comorbidity index). Treatment initiation with TNF-α inhibitors among patients with combination therapy nonbiologic DMARDs use at baseline was associated with age (OR = 0.98, 95% CI = 0.97-0.99 for each year increase) and region (Midwest vs. South OR = 0.81, 95% CI = 0.68-0.96). Stronger associations with some of the need factors were observed (CIRAS OR = 1.28, 95% CI = 1.21-1.35 for each unit increase, steroids use OR = 2.05, 95% CI = 1.73-2.42, and nonselective NSAID use OR = 1.36, 95% CI = 1.17-1.58) in these patients compared with the monotherapy nonbiologic DMARD users. However, unlike the monotherapy DMARD user group, the enabling factors of health insurance type and drug benefit generosity were not found to be associated with TNF-α inhibitor initiation among nonbiologic DMARD combination therapy users.
  
  
  CONCLUSIONS
  Potential disparities in the initiation of TNF-α inhibitors among RA patients on monotherapy DMARDs at baseline were noted among older patients, patients in certain geographic region of the United States, and patients with less generous prescription drug benefits. Although future research should examine the impact of these disparities on health outcomes, payers should be aware of the potential for undertreatment among these groups of RA patients when making formulary decisions.
authors.affiliation: University of North Carolina Eshelman School of Pharmacy, CB 7573 Kerr Hall, Rm. 2201, Chapel Hill, NC 27599-7573. jffarley@email.unc.edu.
authors.forename: Rishi J
authors.initials: RJ
authors.lastname: Desai
authors.forename: Jaya K
authors.initials: JK
authors.lastname: Rao
authors.forename: Richard A
authors.initials: RA
authors.lastname: Hansen
authors.forename: Gang
authors.initials: G
authors.lastname: Fang
authors.forename: Matthew L
authors.initials: ML
authors.lastname: Maciejewski
authors.forename: Joel F
authors.initials: JF
authors.lastname: Farley
mesh_terms: D000328:Adult; D000367:Age Factors; D000368:Aged; D000894:Anti-Inflammatory Agents, Non-Steroidal / Q000627:therapeutic use; D018501:Antirheumatic Agents / Q000008:administration & dosage / Q000627:therapeutic use*; D001172:Arthritis, Rheumatoid / Q000188:drug therapy*; D004359:Drug Therapy, Combination; D004363:Drug Utilization; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D012111:Residence Characteristics; D012189:Retrospective Studies; D012720:Severity of Illness Index; D012737:Sex Factors; D014409:Tumor Necrosis Factor-alpha / Q000037:antagonists & inhibitors*; D014481:United States
chemical_list: D000894:Anti-Inflammatory Agents, Non-Steroidal; D018501:Antirheumatic Agents; D014409:Tumor Necrosis Factor-alpha