Research ArticleArticle

Healthcare Resource Use and Direct Costs in Patients with Ankylosing Spondylitis and Psoriatic Arthritis in a Large US Cohort

Jeffrey D. Greenberg, Jacqueline B. Palmer, Yunfeng Li, Vivian Herrera, Yuen Tsang and Minlei Liao
The Journal of Rheumatology January 2016, 43 (1) 88-96; DOI: https://doi.org/10.3899/jrheum.150540

Abstract

Objective. Direct costs of ankylosing spondylitis (AS) and psoriatic arthritis (PsA) have not been well characterized in the United States. This study assessed healthcare resource use and direct cost of AS and PsA, and identified predictors of all-cause medical and pharmacy costs.

Methods. Adults aged ≥ 18 with a diagnosis of AS and PsA were identified in the MarketScan databases between October 1, 2011, and September 30, 2012. Patients were continuously enrolled with medical and pharmacy benefits for 12 months before and after the index date (first diagnosis). Baseline demographics and comorbidities were identified. Direct costs included hospitalizations, emergency room and office visits, and pharmacy costs. Multivariable regression was used to determine whether baseline covariates were associated with direct costs.

Results. Patients with AS were younger and mostly men compared with patients with PsA. Hypertension and hyperlipidemia were the most common comorbidities in both cohorts. A higher percentage of patients with PsA used biologics and nonbiologic disease-modifying drugs (61.1% and 52.4%, respectively) compared with patients with AS (52.5% and 21.8%, respectively). Office visits were the most commonly used resource by patients with AS and PsA (∼11 visits). Annual direct medical costs [all US dollars, mean (SD)] for patients with AS and PsA were $6514 ($32,982) and $5108 ($22,258), respectively. Prescription drug costs were higher for patients with PsA [$14,174 ($15,821)] compared with patients with AS [$11,214 ($14,249)]. Multivariable regression analysis showed higher all-cause direct costs were associated with biologic use, age, and increased comorbidities in patients with AS or PsA (all p < 0.05).

Conclusion. Biologic use, age, and comorbidities were major determinants of all-cause direct costs in patients with AS and PsA.

Key Indexing Terms:

Ankylosing spondylitis (AS) and psoriatic arthritis (PsA) are part of a family of related inflammatory diseases called spondyloarthritis (SpA) that affect the spine, and in some cases, the peripheral joints and extraarticular regions1,2,3,4. In the United States, AS is the most common SpA condition, affecting between 0.1% and 0.5% of the population while PsA is estimated at 0.1%5. In addition to arthritic symptoms, patients with AS and PsA often have several comorbid conditions, including metabolic syndrome, cardiovascular (CV) disease, obesity, Type 2 diabetes, hypertriglyceridemia, and cerebrovascular disease6,7,8,9. Several treatment options are currently available to manage symptoms and disease progression in patients with AS and PsA, including nonbiologic disease-modifying antirheumatic drugs (nbDMARD) and biologic agents (e.g., tumor necrosis factor-α inhibitors)10,11,12,13,14.

A clear understanding of the financial burden related to the provision of patient care is challenged by the paucity of published economic data in the United States15,16,17,18. To date, few US studies have assessed healthcare use and direct costs of AS or PsA15,16,17. Studies conducted in the mid- to late 1990s estimated that the direct costs (medical and treatment costs, US dollars) per patient with PsA were $3638; for AS, these costs ranged from $2674 to $457115,16. In 1997, the overall direct costs for patients with PsA exceeded $10 million18. The majority of these costs were attributed to pharmacy costs, functional disabilities, and comorbidities15,16,17.

As physicians and payers examine the cost-effectiveness and assess the growing treatment options associated with AS and PsA, a more accurate understanding of the healthcare resource use and costs is needed because most US studies were published more than 12 years ago15,16. In the last 10 years, only 1 US study examined healthcare use in AS and none addressed PsA in a broad general population of patients with commercial healthcare or private Medicare supplemental coverage16. Similarly, only a limited number of US studies reviewed direct costs in patients with PsA or AS15,16,17. Biologics became available after 2002, which significantly influences the inferences drawn from studies performed before their widespread use15,16. The development of newer biologic agents has contributed to the treatment resources for patients with AS and PsA19. However, only limited data exist on the effect of these new medications on overall medical costs17, and the effect of comorbidities on overall medical costs of AS and PsA is poorly understood.

Using a retrospective administrative claims database, our present study was designed to enhance the understanding of the current economic effect on these patient populations in the United States. To our knowledge, this is the first published study within the last decade to evaluate the healthcare resource use and all-cause direct costs associated with AS and PsA. Our objective was to fill the current US knowledge gap descriptively and to report the healthcare resource use and direct costs and predictors of costs for patients with AS and PsA from a payer perspective.

MATERIALS AND METHODS

Data source

We conducted a retrospective observational claims analysis to assess healthcare use and direct costs associated with AS and PsA using administrative data derived from 2 Truven Health Analytics MarketScan Research databases: the Commercial Claims and Encounters Database, and the Medicare Supplemental and Coordination of Benefits Database. These represent the health services of dependents and retired workers in the United States with primary or Medicare supplemental coverage through private employer-sponsored insured health plans. Healthcare is provided under a variety of fee-for-service (FFS), point-of-service (POS), or capitated health plans. Types of health plans included health maintenance organization (HMO) and POS or comprehensive plans20. Detailed cost, use, and outcomes data for healthcare services performed in both inpatient and outpatient settings were collected. Unique enrollee identifiers link medical claims to outpatient prescription drug claims and person-level enrollment data. Database constructs included information on patient demographics (age, sex, employment status, geographic location), healthcare use, costs (payment), and comprehensive prescription drug data20. All study data were accessed in compliance with the Health Insurance Portability and Accountability Act of 1996. Because MarketScan databases contain deidentified patient data, informed consent or institutional review board approval were not required.

Sample selection and patient population

A diagnosis of AS or PsA was identified using the International Classification of Diseases, 9th ed, Clinical Modification (ICD-9-CM) codes 720.0 (AS) and 696.0 (PsA)21. The study period was from October 1, 2010, to September 30, 2013. Patients with AS or PsA aged ≥ 18 years with at least 2 inpatient and/or outpatient ICD-9-CM claims for AS or PsA between October 1, 2011, and September 30, 2012 (identification period) were included in the analysis (Figure 1). Claims had to be on different dates during the identification period. The index date was defined as the first reported ICD-9-CM claim with any diagnosis of AS or PsA during the identification period. One index date per patient was designated for each condition. Patients were required to be continuously enrolled with medical and pharmacy benefits in the 12 months before and after the index date. Patients with a non–rule-out rheumatoid arthritis diagnosis (ICD-9 code, 714.x) 12 months before and after the index date were excluded to reduce the potential for misdiagnosis. Demographic and clinical characteristics were obtained during the preindex period (i.e., the fixed 12-mo period before the patient identification period). All-cause direct costs and healthcare resource use were estimated during the 12-month followup period following the index date.

Figure 1.
Figure 1.

Patient selection flowchart. Patients with ≥ 2 claims for AS or PsA diagnoses identified between October 1, 2011, and September 30, 2012. The index date was the date of the first diagnosis during the identification period. One index date per patient was designated for AS and PsA. For example, a patient included in the PsA cohort could have 2 of the same diagnosis claims (e.g., the AS cohort had to have 2 ICD-9-CM claims of AS). Data source: MarketScan Commercial and Medicare Supplemental databases, 2010-2013 (http://truvenhealth.com/your-healthcare-focus/analytic-research/marketscan-research-databases). AS: ankylosing spondylitis; PsA: psoriatic arthritis; RA: rheumatoid arthritis; ICD-9-CM: International Classification of Diseases, 9th ed, Clinical Modification.

Explanatory variables

Demographic categorical variables included sex, geographic region (Northeast, North Central, South, West), and insurance type (HMO and POS capitation, FFS). Age was molded as a categorical variable to allow for a nonlinear relationship between age and cost and was represented as age 18–34, 35–44, 45–54, 55–64, and ≥ 65 years. Clinical variables evaluated during the preindex period included a measure of comorbidities. The Elixhauser Comorbidity Index (ECI) score was used to measure the burden of comorbid conditions not directly related to AS or PsA. ECI distinguishes 30 comorbid conditions identified using ICD-9-CM codes from complications by considering only secondary diagnoses unrelated to the primary diagnosis22. The mean ECI score for each condition and the proportion of patients reporting 0, 1, 2, 3, or 4+ comorbidities were determined. In addition, selected AS- and PsA-related comorbidities (i.e., Type 2 diabetes, hypertension, hyperlipidemia, and ischemic heart disease) were measured based on the Chronic Conditions Warehouse (CCW) algorithm23.

Outcome measures

The study outcome measures were all-cause healthcare resource use and direct costs reported during the 12-month followup period. Healthcare resource use included hospitalization (inpatient visits), office, and emergency room (ER) visits, and biologic and nbDMARD use among users with at least 1 resource use. Direct costs included plan-paid medical expenditures for hospitalization (inpatient), office, and ER visits, and prescription costs for biologics and nbDMARD. Capitated costs with a value of 0 or 1 for managed care payers were assigned a value using the FFS median cost. All costs were adjusted to 2013 US dollars using the Consumer Price Index. Biologic drugs considered in the analysis were infliximab24, adalimumab25, golimumab26, etanercept27, certolizumab28, rituximab29, tocilizumab30, abatacept31, and ustekinumab32. nbDMARD included were hydroxychloroquine sulfate33, leflunomide34, methotrexate35, sulfasalazine36, azathioprine37, penicillamine38, and cyclosporine39.

Statistical analysis

Descriptive summary statistics were performed for all demographics and disease characteristics; these included count and percentages for categorical variables and mean and SD for continuous variables. Mean (SD) and median (interquartile range) were reported for all-cause healthcare use and direct costs. A multivariable generalized linear model (GLM) with γ distribution and log link function was used to identify potential predictors associated with direct costs40, which included medical and pharmacy costs. The explanatory variables in the multivariable GLM included age, sex, region, insurance plan, ECI score, and baseline biologic use.

The same patient selection process as described in Figure 1 was applied to the multivariable analysis for the definitions of AS and PsA. Patients with missing region (n = 42 for AS, < 1%; n = 125 for PsA, < 1%), missing insurance type (n = 157 for AS, < 3%; n = 425 for PsA, < 4%), or zero outcome (n = 11 for AS, < 1%; n = 5 for PsA, < 1%) were excluded from the multivariate analysis. Coefficient estimates were the exponentials of the original estimates. A coefficient of > 1.0 indicates higher cost and < 1.0 indicates lower costs for a given variable compared with the specified reference. The coefficient indicates cost increases or decreases in a continuous manner compared with the reference group. Standard error and confidence limits were adjusted accordingly. The prespecified significance level for statistical comparisons was p < 0.05. All statistical analyses were performed using SAS software version 9.3 (SAS Institute Inc.).

RESULTS

Patient selection

Patients with at least 2 ICD-9-CM claims for an AS or PsA diagnosis were identified in the MarketScan Research database between October 1, 2011, and September 30, 2012. The patient selection process and the number of patients with AS (n = 4288) and PsA (n = 10,832) after applying the inclusion and exclusion criteria are illustrated in Figure 1.

Baseline patient characteristics

Baseline demographics and disease characteristics are presented in Table 1. The mean (SD) age of patients with PsA was 51.9 years (11.8) and for AS was 49.1 years (13.4). The AS cohort had a greater percentage of men than women (64.3%). In the PsA cohort, the distribution of men and women was about 50%. Patients with AS had a slightly greater number of comorbidities (mean ECI score of 1.9) compared with patients with PsA (mean ECI score of 1.2). The percentage of patients with AS with an ECI score ≥ 2 was 48.9% compared with 31.7% for the PsA cohort. The AS cohort had the highest percentage of patients with an ECI score of ≥ 4 (13.2% for AS vs 7.4% for PsA). The distribution of the evaluated comorbid conditions was similar across both cohorts; hypertension was the most common comorbidity identified using the CCW chronic condition codes, followed by hyperlipidemia, Type 2 diabetes, and ischemic heart disease (Table 1).

View this table:
Table 1.

Baseline demographic and disease characteristics of patients with AS and PsA. Values are n (%) unless otherwise specified.

All-cause healthcare resource use: 12-month followup

Unadjusted all-cause healthcare resource use for patients with AS and PsA in the 12-month followup period is summarized in Table 2. Patients with PsA had a lower percentage of hospitalizations (9.4%) compared with patients with AS (11.1%). About 1 in 5 patients with AS or PsA visited the ER during the followup year (22.0% and 20.4%, respectively). Office visits were the most commonly used healthcare resource for both patient groups. More than half of all patients used biologics (52.5% and 61.1%, respectively), and the use of nbDMARD was lower in patients with AS (21.8%) than in those with PsA (52.4%).

View this table:
Table 2.

All-cause healthcare resource use for patients with AS and PsA: 12-month followup.

Patients in both cohorts who used at least 1 healthcare resource per year had few inpatient/outpatient visits during the followup period (Table 2), and had about 1 hospitalization and 11 office visits per year: 6.6 (9.6) and 10.8 (7.7) for AS and 5.5 (7.1) and 10.7 (7.0) for PsA, respectively. The percentage of patients with AS and PsA who used biologics was similar (52.5% and 61.1%, respectively). The mean number of biologic prescriptions used per year was also similar for patients with AS [7.2 (SD 3.8)] and PsA [7.3 (SD 3.8)]. A lower percentage of patients with AS (21.8%) used nbDMARD than patients with PsA (52.4%). The mean number of nbDMARD prescriptions per year was lower in patients with AS [5.3 (SD 4.2)] than in patients with PsA [6.5 (SD 4.6)].

All-cause direct costs: 12-month followup

The unadjusted annual all-cause direct costs for AS and PsA during the 12-month followup period are summarized in Table 3 and Figure 2. Patients with PsA had an unadjusted mean (SD) medical cost of $5108 ($22,258), which was lower than for patients with AS [$6514 ($32,982); Figure 2]. Hospitalization costs were at least 2-fold higher than office and ER visits for both cohorts. PsA was associated with a lower mean (SD) hospitalization compared with AS [$3064 ($17,444) vs $4185 ($26,503)], and office [$1458 ($2097) vs $1571 ($2242)] and ER visit costs [$586 ($2717) vs $758 ($4237)].

Figure 2.
Figure 2.

Mean all-cause direct costs during the 12-month followup period. Medical costs were calculated as hospitalization costs plus emergency room and office visit costs in US dollars. Prescription drug costs were calculated as biologics plus oral drug costs in US dollars. AS: ankylosing spondylitis; PsA: psoriatic arthritis.

View this table:
Table 3.

Unadjusted all-cause direct costs for patients with AS and PsA: 12-month followup.

Unadjusted mean (SD) prescription drug costs were higher in patients with PsA [$14,174 ($15,821)] compared with patients with AS [$11,214 ($14,249)] during the 12-month followup (Figure 2). Costs for biologics were responsible for most of the prescription drug totals. Patients with PsA incurred higher mean (SD) costs associated with biologics compared with AS [$14,061 ($15,593) vs $11,162 ($14,021)]. The cost of nbDMARD was less than $150 for both cohorts.

All-cause direct costs of AS and PsA

A multivariable analysis was performed to determine whether baseline covariates were associated with all-cause direct costs (medical and pharmacy costs) for AS and PsA during the 12-month followup period. The adjusted coefficient estimate and significance values for each cost predictor are presented in Table 4. After controlling for baseline characteristics, patients with AS aged 18–64 years had 18–30% higher directs costs compared with patients with AS ≥ 65 years (p < 0.05; Table 4). Patients with PsA aged 18–34, 45–54, and 55–64 years had 9–18% higher direct costs than patients with PsA aged ≥ 65 years (p < 0.05). However, patients with PsA aged 35–44 years had similar direct costs to those aged ≥ 65 years. No differences were observed between men compared with women in regard to direct costs in either group. Patients with an ECI score of ≥ 4 had direct costs twice as high for both AS (coefficient estimate 2.12, 95% CI 1.81–2.48) and PsA (1.95, 95% CI 1.78–2.13) compared with patients with an ECI score of 0 (all p < 0.001). The mean direct costs were about 3 times as high among patients with baseline biologic use compared with those without biologic use for both cohorts (2.82, 95% CI 2.61–3.05 for patients with AS; 3.12, 95% CI 2.98–3.25 for patients with PsA; both p < 0.001).

View this table:
Table 4.

Predictors of all-cause direct costs after adjusting for baseline characteristics*. Direct costs were calculated as the sum of all-cause medical and pharmacy costs. Outcomes were predicted using a generalized linear model with γ distribution and log link function.

DISCUSSION

To our knowledge, ours is the first study within the past 10 years to describe the all-cause healthcare resource use and direct costs incurred by patients with AS and PsA. In both cohorts, the most commonly used healthcare resource per year was office visits (11 office visits per yr), and the use of biologics was greater than nbDMARD in both cohorts. Use of biologics was similar in patients with PsA and AS. The use of nbDMARD was lower in patients with AS than those with PsA, possibly indicating the limited oral treatment options available for this condition. Patients with PsA had lower direct medical costs ($5108) than those with AS ($6514), and prescription drug costs were about $2000 higher for patients with PsA ($14,174). In the multivariable analysis, use of biologics was the major driver for the high prescription drug cost. Higher all-cause direct costs were associated with younger age and higher number of comorbidities.

To our knowledge, in the United States to date, all-cause healthcare resource use has only been investigated in 1 prior study for AS and in no studies for PsA in a broad population of insured patients, similar to that of our study. Ward performed a prospective longitudinal study that evaluated the total direct costs of AS and characterized the predictors of high total costs in patients with AS (n = 241)16. They found that, for patients with AS, healthcare use was low after the 1-year followup: 3% of patients had a hospitalization, an average of 7 office visits (i.e., rheumatology visits, other doctor visits, chiropractor visits, and physical/occupational therapy visits), and no ER visits16. Similar to the Ward study, our study showed that office visits were the most common resource used by patients with AS, with an average of 11 per year16. Our study found a slightly higher proportion of patients with AS having hospitalizations (11%), and of those, the average number of hospitalizations was ∼7. The reason for these differences is not entirely clear, but may reflect differences between patient populations, comorbidities, types of health insurance, AS disease severity, and changes in healthcare practices since 20027,8,9. The study by Singh and Strand evaluated the healthcare use of veterans with AS and PsA in the Veterans Integrated Service Network-13 using a postal survey41. However, comparing the findings of the 2 studies with ours is challenging because of the differences in populations analyzed and methodology.

Several studies assessed the all-cause direct costs for AS and PsA15,16. Williams and Meyers estimated the direct costs using claims data (MedStat MarketScan database) for 1999 to 2000. The average annual per patient cost for medical resources and prescription drugs was $4500 for patients with AS and $3600 for patients with PsA15. Ward also evaluated total direct cost for AS using patient-reported information gathered through a questionnaire16. Researchers found that the average annual direct cost for patients with AS was $2700, including inpatient/outpatient visits, medications, assistive devices, travel to visits, and diagnostic testing. Considering both medical and pharmacy costs, the direct costs in our study were estimated to be $17,728 for patients with AS and $19,282 for patients with PsA. Even after adjusting for inflation, the direct costs for AS and PsA reported in the previous studies15,16 were considerably lower than in our study. One explanation for these differences is how these conditions are now treated and possibly the addition of biologic use in the last decade42,43. Study design variables likely affected the findings.

A longitudinal study by Zhu, et al17 examined medication use and healthcare costs in patients with PsA who had initiated treatment with a biologic, either as monotherapy or adjunctive therapy with a conventional nbDMARD using the Truven Health Analytics MarketScan database. Investigators determined that the total all-cause and PsA disease-specific direct costs (i.e., inpatient, outpatient, ER, and pharmacy costs that contained a PsA diagnosis code) were $26,535 and $17,764, respectively17. In our study, total all-cause cost for PsA was $19,282. The difference between our findings and those of Zhu, et al may reflect differences in the population because they used a biologic-naive group (excluding patients with biologic claims within 6 mos). Compared with the studies by Williams and Meyers15 and Ward16, the costs for PsA and AS in our study and those in Zhu, et al17 suggest that the overall direct cost of managing and treating patients with AS or PsA has markedly increased since 2002.

Similar to our study, previous studies have found that pharmacy cost was 1 of the largest contributors to expenses in patients with AS or PsA. Ward noted that medication costs accounted for the greatest proportion of direct costs in patients with AS (42%)16. Zhu, et al reported that pharmacy costs in patients with PsA receiving biologic therapy accounted for 54% of total all-cause expenditures17. The results of these 2 studies are consistent with our observation that pharmacy costs made up > 50% of the medical plus prescription cost in patients with AS or PsA. Zhu, et al found that all-cause and PsA-specific 1-year pharmacy costs were $14,315 and $11,981, respectively17. We found that pharmacy costs (biologic and nbDMARD) in the 1-year followup period were $14,174 for the PsA cohort. The difference in values between the studies may reflect differences in study design and the pharmacy costs that were included in the analyses. For example, Zhu, et al evaluated costs for all medications, including drugs administered during inpatient and outpatient visits, as well as medications with an associated PsA code for their evaluation of PsA-associated costs17. In our study, we included only costs of biologics and nbDMARD.

The primary driver of higher direct costs for AS and PsA patients in our study was baseline biologic use; other drivers were age and the number of comorbidities, as reflected by the ECI score. The number of comorbid conditions was not associated with high total costs, which may reflect the different methods used to evaluate the presence of comorbidities (i.e., ECI score vs patient questionnaire). Additional studies are necessary to assess the effect of comorbid conditions on the all-cause healthcare costs of AS and PsA. Despite the high costs associated with biologics, they are effective and recommended for certain patients with PsA or AS whose first-line therapy fails44,45. Our findings also suggest the need for patients treated with biologics to be carefully managed to maximize the benefit of these therapies relative to the costs.

AS and PsA are associated with a number of comorbid conditions, which along with the primary disease, can greatly affect a patient’s quality of life (QoL)44,46. The main treatment goals are to maximize QoL and physical function by not only controlling the signs and symptoms of the disease, but by minimizing comorbidities43. Some comorbidities may be related to the inflammation associated with these diseases; inflammatory joint disease is known to be involved in CV and non-CV morbidity in patients with PsA47. Other factors, such as CV risk factors, higher ratio of total cholesterol to high-density lipoprotein cholesterol, and smoking, may influence the presence of comorbidities48.

Our study had a few shortcomings that should be acknowledged. Our study population was restricted to individuals with commercial healthcare coverage or private Medicare supplemental coverage and may not be generalizable to all patients with AS or PsA within the United States21. Patients with AS or PsA who have severe functional impairment and are not able to work may not have been represented, leading to an underestimation of costs. Because we used a retrospective approach, our study was limited to patients who were diagnosed clinically; however, patients with undiagnosed AS or PsA may have sought medical attention and incurred additional healthcare resource use and costs. Diagnoses recorded on claims may be coded incorrectly or not coded at all, thereby potentially introducing measurement error in ICD-9-CM–based variables. Administrative claims data were not collected for research purposes, and the diagnostic coding on administrative claims was recorded by physicians to support reimbursement. Thus, data may not be detailed enough to provide a clinically precise description of patients. Therefore, the effect of disease severity and other descriptive variables (e.g., smoking status) on costs and cost drivers was not assessed. Our multivariate analysis revealed a multicollinearity issue between ECI and AS- and PsA-related comorbidities because of the ECI containing AS- and PsA-associated comorbidities. Consequently, we chose not to evaluate the individual AS- and PsA-related comorbidities in the multivariable analysis in our study because they do not reflect the overall comorbidity burden for these 2 diseases. Instead, we used the ECI and CCW to provide a more comprehensive evaluation of the comorbidity burden.

With regard to adjusting for baseline characteristics, our adjustments may not fully account for all comorbidities present in patients with AS or PsA, or the relationship between comorbid conditions within the same patient. Another study is required to assess the economic burden of comorbidities related to AS and PsA. We also did not evaluate the cost of the use of nonsteroidal antiinflammatory drugs (NSAID), analgesics, or physical therapy visits. NSAID are recommended as first-line therapy for patients with both AS and PsA10,49,50,51,52 and are commonly used to treat both diseases. However, there was no cost or use information in the databases used in our study for NSAID because most are over-the-counter medications. Because the preferred societal perspective of cost is most comprehensive, a limitation of our study is that only costs from the payer’s perspective were included. We did not account for indirect costs of the disease such as work productivity. Future studies should be designed to assess the effect of these variables on the direct costs of AS and PsA.

Our findings contribute to the literature on the economic burden associated with the classically defined SpA conditions of AS or PsA. We evaluated the all-cause direct costs and predictors of higher costs for AS and PsA. The most influential predictors of direct costs were the use of biologics, age, and the presence of comorbid conditions. The significant effect that biologics had on overall direct costs indicates the need to better understand the relationships among treatment outcomes, use of medical resources, and real-world biologic use. Future studies should focus on examining the effect of these relationships on disease symptoms, patient QoL, and total healthcare costs.

Acknowledgment

The authors acknowledge individuals who contributed and provided assistance during the development of this manuscript. Michelle A. Adams, BSJ, MA, and Elizabeth Goodwin, PhD, are Write All Inc. consultants who provided medical writing and editorial assistance for this manuscript. Special thanks are also given to Melody Tran, PharmD, for her critical evaluation and editorial assistance. She is a postdoctoral student from Scott and White Health Plan and the University of Texas at Austin who is currently completing her Health Economics and Outcomes Research fellowship at Novartis Pharmaceuticals Corp.

Footnotes

  • Funding provided by Novartis Pharmaceuticals Corp. Dr. Greenberg has received consulting fees from Novartis. Drs. Palmer, Li, and Herrera are employees of Novartis. Y. Tsang is a Novartis Outcomes Research Fellow at Novartis and a student at the Department of Pharmaceutical Health Services Research, University of Maryland School of Pharmacy. M. Liao is a senior analyst at KMK Consulting Inc. and works as a consultant for Novartis.

  • Accepted for publication September 23, 2015.

REFERENCES

  1. 1.↵
    1. American College of Rheumatology
    . Spondyloarthritis (spondyloarthropathies). [Internet. Accessed October 20, 2015.] Available from: www.rchsd.org/documents/2014/02/spondyloarthritis.pdf
  2. 2.↵
    1. Sieper J,
    2. Rudwaleit M,
    3. Baraliakos X,
    4. Brandt J,
    5. Braun J,
    6. Burgos-Vargas R,
    7. et al.
    The Assessment of SpondyloArthritis international Society (ASAS) handbook: a guide to assess spondyloarthritis. Ann Rheum Dis 2009;68 Suppl 2:ii1–44.
    OpenUrlAbstract/FREE Full Text
  3. 3.↵
    1. Rudwaleit M,
    2. van der Heijde D,
    3. Landewé R,
    4. Listing J,
    5. Akkoc N,
    6. Brandt J,
    7. et al.
    The development of Assessment of SpondyloArthritis international Society classification criteria for axial spondyloarthritis (part II): validation and final selection. Ann Rheum Dis 2009;68:777–83.
    OpenUrlAbstract/FREE Full Text
  4. 4.↵
    1. Rudwaleit M,
    2. van der Heijde D,
    3. Landewé R,
    4. Akkoc N,
    5. Brandt J,
    6. Chou CT,
    7. et al.
    The Assessment of SpondyloArthritis international Society classification criteria for peripheral spondyloarthritis and for spondyloarthritis in general. Ann Rheum Dis 2011;70:25–31.
    OpenUrlAbstract/FREE Full Text
  5. 5.↵
    1. Helmick CG,
    2. Felson DT,
    3. Lawrence RC,
    4. Gabriel S,
    5. Hirsch R,
    6. Kwoh CK,
    7. et al;
    8. National Arthritis Data Workgroup
    . Estimates of the prevalence of arthritis and other rheumatic conditions in the United States. Part I. Arthritis Rheum 2008;58:15–25.
    OpenUrlCrossRefPubMed
  6. 6.↵
    1. Labitigan M,
    2. Bahce-Altuntas A,
    3. Kremer JM,
    4. Reed G,
    5. Greenberg JD,
    6. Jordan N,
    7. et al.
    Higher rates and clustering of abnormal lipids, obesity, and diabetes mellitus in psoriatic arthritis compared with rheumatoid arthritis. Arthritis Care Res 2014;66:600–7.
    OpenUrlCrossRef
  7. 7.↵
    1. Han C,
    2. Robinson DW Jr,
    3. Hackett MV,
    4. Paramore LC,
    5. Fraeman KH,
    6. Bala MV
    . Cardiovascular disease and risk factors in patients with rheumatoid arthritis, psoriatic arthritis, and ankylosing spondylitis. J Rheumatol 2006;33:2167–72.
    OpenUrlAbstract/FREE Full Text
  8. 8.↵
    1. Gladman DD,
    2. Ang M,
    3. Su L,
    4. Tom BD,
    5. Schentag CT,
    6. Farewell VT
    . Cardiovascular morbidity in psoriatic arthritis. Ann Rheum Dis 2009;68:1131–5.
    OpenUrlAbstract/FREE Full Text
  9. 9.↵
    1. Szabo SM,
    2. Levy AR,
    3. Rao SR,
    4. Kirbach SE,
    5. Lacaille D,
    6. Cifaldi M,
    7. et al.
    Increased risk of cardiovascular and cerebrovascular diseases in individuals with ankylosing spondylitis: a population-based study. Arthritis Rheum 2011;63:3294–304.
    OpenUrlCrossRefPubMed
  10. 10.↵
    1. Braun J,
    2. van den Berg R,
    3. Baraliakos X,
    4. Boehm H,
    5. Burgos-Vargas R,
    6. Collantes-Estevez E,
    7. et al.
    2010 update of the ASAS/EULAR recommendations for the management of ankylosing spondylitis. Ann Rheum Dis 2011;70:896–904.
    OpenUrlAbstract/FREE Full Text
  11. 11.↵
    1. van der Heijde D,
    2. Sieper J,
    3. Maksymowych WP,
    4. Dougados M,
    5. Burgos-Vargas R,
    6. Landewé R,
    7. et al;
    8. Assessment of SpondyloArthritis international Society
    . 2010 Update of the international ASAS recommendations for the use of anti-TNF agents in patients with axial spondyloarthritis. Ann Rheum Dis 2011;70:905–8.
    OpenUrlAbstract/FREE Full Text
  12. 12.↵
    1. van der Horst-Bruinsma IE,
    2. Nurmohamed MT,
    3. Landewé RB
    . Comorbidities in patients with spondyloarthritis. Rheum Dis Clin North Am 2012;38:523–38.
    OpenUrlCrossRefPubMed
  13. 13.↵
    1. McLeod C,
    2. Bagust A,
    3. Boland A,
    4. Dagenais P,
    5. Dickson R,
    6. Dundar Y,
    7. et al.
    Adalimumab, etanercept and infliximab for the treatment of ankylosing spondylitis: a systematic review and economic evaluation. Health Technol Assess 2007;11:1–158, iii–iv.
    OpenUrlCrossRefPubMed
  14. 14.↵
    1. Inman RD,
    2. Davis JC Jr,
    3. Heijde Dv,
    4. Diekman L,
    5. Sieper J,
    6. Kim SI,
    7. et al.
    Efficacy and safety of golimumab in patients with ankylosing spondylitis: results of a randomized, double-blind, placebo-controlled, phase III trial. Arthritis Rheum 2008;58:3402–12.
    OpenUrlCrossRefPubMed
  15. 15.↵
    1. Williams JP,
    2. Meyers JA
    . Immune-mediated inflammatory disorders (I.M.I.D.s): the economic and clinical costs. Am J Manag Care 2002;8 Suppl:S664–81.
    OpenUrlPubMed
  16. 16.↵
    1. Ward MM
    . Functional disability predicts total costs in patients with ankylosing spondylitis. Arthritis Rheum 2002;46:223–31.
    OpenUrlCrossRefPubMed
  17. 17.↵
    1. Zhu B,
    2. Edson-Heredia E,
    3. Gatz JL,
    4. Guo J,
    5. Shuler CL
    . Treatment patterns and health care costs for patients with psoriatic arthritis on biologic therapy: a retrospective cohort study. Clin Ther 2013;35:1376–85.
    OpenUrlCrossRefPubMed
  18. 18.↵
    1. Javitz HS,
    2. Ward MM,
    3. Farber E,
    4. Nail L,
    5. Vallow SG
    . The direct cost of care for psoriasis and psoriatic arthritis in the United States. J Am Acad Dermatol 2002;46:850–60.
    OpenUrlCrossRefPubMed
  19. 19.↵
    1. Keith MP
    . Overview of drug therapy for spondyloarthritis. Rheumatol Curr Res 2013;3:2.
    OpenUrl
  20. 20.↵
    1. Truven Health Analytics
    . Homepage. [Internet. Accessed October 20, 2015.] Available from: truvenhealth.com
  21. 21.↵
    1. Centers for Disease Control and Prevention
    . International classification of diseases, ninth revision, clinical modification (ICD-9-CM). [Internet. Accessed October 20, 2015.] Available from: www.cdc.gov/nchs/icd/icd9cm.htm
  22. 22.↵
    1. Elixhauser A,
    2. Steiner C,
    3. Harris DR,
    4. Coffey RM
    . Comorbidity measures for use with administrative data. Med Care 1998;36:8–27.
    OpenUrlCrossRefPubMed
  23. 23.↵
    1. Chronic Conditions Data Warehouse
    . Condition categories. [Internet. Accessed October 20, 2015.] Available from: www.ccwdata.org/web/guest/condition-categories
  24. 24.↵
    1. Remicade
    . Remicade (infliximab) prescribing information. [Internet. Accessed October 20, 2015.] Available from: www.remicade.com/shared/product/remicade/prescribing-information.pdf
  25. 25.↵
    1. Abbvie
    . Humira (adalimumab) prescribing information. [Internet. Accessed October 20, 2015.] Available from: www.rxabbvie.com/pdf/humira.pdf
  26. 26.↵
    1. Simponi
    . SIMPONI (golimumab) prescribing information. [Internet. Accessed October 20, 2015.] Available from: www.simponi.com/shared/product/simponi/prescribing-information.pdf
  27. 27.↵
    1. Enbrel
    . Enbrel (etanercept) prescribing information. [Internet. Accessed October 20, 2015.] Available from: www.enbrel.com/prescribing-information.jspx
  28. 28.↵
    1. CIMZIA
    . CIMZIA (certolizumab pegol) prescribing information. [Internet. Accessed October 20, 2015.] Available from: www.cimzia.com/assets/pdf/Prescribing_Information.pdf
  29. 29.↵
    1. Genentech
    . Rituxan (rituximab) prescribing information. [Internet. Accessed October 20, 2015.] Available from: www.gene.com/download/pdf/rituxan_prescribing.pdf
  30. 30.↵
    1. Genentech
    . Actemra (tocilizumab) prescribing information. [Internet. Accessed October 20, 2015.] Available from: www.gene.com/download/pdf/actemra_prescribing.pdf
  31. 31.↵
    1. Bristol-Myers Squibb
    . Orencia (abatacept) prescribing information. [Internet. Accessed October 20, 2015.] Available from: packageinserts.bms.com/pi/pi_orencia.pdf
  32. 32.↵
    1. Stelara
    . Stelara (ustekinumab) prescribing information. [Internet. Accessed October 20, 2015.] Available from: www.stelarainfo.com/pdf/PrescribingInformation.pdf
  33. 33.↵
    1. WebMD
    . Quineprox (hydroxychloroquine sulfate) prescribing information. [Internet. Accessed October 20, 2015.] Available from: www.webmd.com/drugs/2/drug-1085/quineprox+oral/details
  34. 34.↵
    Sanofi. Arava (leflunomide) prescribing information. [Internet. Accessed October 20, 2015.] Available from: products.sanofi.us/arava/arava.html
  35. 35.↵
    1. RxList
    . Trexall (methotrexate) prescribing information. [Internet. Accessed October 20, 2015.] Available from: www.rxlist.com/trexall-drug.htm
  36. 36.↵
    1. Pfizer
    . Azulfidine (sulfasalazine) prescribing information. [Internet. Accessed October 20, 2015.] Available from: www.pfizer.com/products/product-detail/azulfidine
  37. 37.↵
    1. RxList
    . Imuran (azathioprine) prescribing information. [Internet. Accessed October 20, 2015.] Available from: www.rxlist.com/imuran-drug/indications-dosage.htm
  38. 38.↵
    1. Valeant
    . Cuprimine (penicillamine) prescribing information. [Internet. Accessed October 20, 2015.] Available from: www.valeant.com/Portals/25/Pdf/PI/Cuprimine-PI.pdf
  39. 39.↵
    1. Novartis Pharmaceuticals
    . Sandimmune (cyclosporine) prescribing information. [Internet. Accessed October 20, 2015.] Available from: www.pharma.us.novartis.com/product/pi/pdf/sandimmune.pdf
  40. 40.↵
    1. Moran JL,
    2. Solomon PJ,
    3. Peisach AR,
    4. Martin J
    . New models for old questions: generalized linear models for cost prediction. J Eval Clin Pract 2007;13:381–9.
    OpenUrlCrossRefPubMed
  41. 41.
    1. Singh JA,
    2. Strand V
    . Health care utilization in patients with spondyloarthropathies. Rheumatology 2009;48:272–6.
    OpenUrlAbstract/FREE Full Text
  42. 42.↵
    1. Bruner V,
    2. Atteno M,
    3. Spanò A,
    4. Scarpa R,
    5. Peluso R
    . Biological therapies for spondyloarthritis. Ther Adv Musculoskelet Dis 2014;6:92–101.
    OpenUrlAbstract/FREE Full Text
  43. 43.↵
    1. Braun J,
    2. Baraliakos X
    . Treatment of ankylosing spondylitis and other spondyloarthritides. Curr Opin Rheumatol 2009;21:324–34.
    OpenUrlCrossRefPubMed
  44. 44.↵
    1. Toussirot E,
    2. Wendling D
    . Current guidelines for the drug treatment of ankylosing spondylitis. Drugs 1998;56:225–40.
    OpenUrlCrossRefPubMed
  45. 45.↵
    1. Smolen JS,
    2. Braun J,
    3. Dougados M,
    4. Emery P,
    5. Fitzgerald O,
    6. Helliwell P,
    7. et al.
    Treating spondyloarthritis, including ankylosing spondylitis and psoriatic arthritis, to target: recommendations of an international task force. Ann Rheum Dis 2014;73:6–16.
    OpenUrlAbstract/FREE Full Text
  46. 46.↵
    1. Husted JA,
    2. Thavaneswaran A,
    3. Chandran V,
    4. Eder L,
    5. Rosen CF,
    6. Cook RJ,
    7. et al.
    Cardiovascular and other comorbidities in patients with psoriatic arthritis: a comparison with patients with psoriasis. Arthritis Care Res 2011;63:1729–35.
    OpenUrl
  47. 47.↵
    1. Papagoras C,
    2. Markatseli TE,
    3. Saougou I,
    4. Alamanos Y,
    5. Zikou AK,
    6. Voulgari PV,
    7. et al.
    Cardiovascular risk profile in patients with spondyloarthritis. Joint Bone Spine 2014;81:57–63.
    OpenUrlCrossRefPubMed
  48. 48.↵
    1. Peters MJ,
    2. Symmons DP,
    3. McCarey D,
    4. Dijkmans BA,
    5. Nicola P,
    6. Kvien TK,
    7. et al.
    EULAR evidence-based recommendations for cardiovascular risk management in patients with rheumatoid arthritis and other forms of inflammatory arthritis. Ann Rheum Dis 2010;69:325–31.
    OpenUrlAbstract/FREE Full Text
  49. 49.↵
    1. Ritchlin CT,
    2. Kavanaugh A,
    3. Gladman DD,
    4. Mease PJ,
    5. Helliwell P,
    6. Boehncke WH,
    7. et al;
    8. Group for Research and Assessment of Psoriasis and Psoriatic Arthritis (GRAPPA)
    . Treatment recommendations for psoriatic arthritis. Ann Rheum Dis 2009;68:1387–94.
    OpenUrlAbstract/FREE Full Text
  50. 50.↵
    1. Day MS,
    2. Nam D,
    3. Goodman S,
    4. Su EP,
    5. Figgie M
    . Psoriatic arthritis. J Am Acad Orthop Surg 2012;20:28–37.
    OpenUrlAbstract/FREE Full Text
  51. 51.↵
    1. American Academy of Dermatology Work Group,
    2. Menter A,
    3. Korman NJ,
    4. Elmets CA,
    5. Feldman SR,
    6. Gelfand JM,
    7. et al.
    Guidelines of care for the management of psoriasis and psoriatic arthritis: section 6. Guidelines of care for the treatment of psoriasis and psoriatic arthritis: case-based presentations and evidence-based conclusions. J Am Acad Dermatol 2011;65:137–74.
    OpenUrlCrossRefPubMed
  52. 52.↵
    1. Gossec L,
    2. Smolen JS,
    3. Gaujoux-Viala C,
    4. Ash Z,
    5. Marzo-Ortega H,
    6. van der Heijde D,
    7. et al;
    8. European League Against Rheumatism
    . European League Against Rheumatism recommendations for the management of psoriatic arthritis with pharmacological therapies. Ann Rheum Dis 2012;71:4–12.
    OpenUrlAbstract/FREE Full Text
Back to top

In this issue

Print
Download PDF
Article Alerts
Email Article
Citation Tools

 Request Permissions

Bookmark this article

Jump to section

Keywords

ANKYLOSING SPONDYLITIS
PSORIATIC ARTHRITIS
OBSERVATIONAL STUDY
MEDICAL CARE COSTS
PRESCRIPTION DRUGS
COST ANALYSIS

Keywords