Effectiveness and Costs of TNF-Alpha Blocker Use for Patients with Rheumatoid Arthritis

March/April 2013 Vol 6, No 2 - Clinical
Kavita Nair, PhD
Vahram Ghushchyan, PhD
Ahmad Naim, MD
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Abstract

Background: Rheumatoid arthritis (RA) is ranked among the highest of all chronic diseases in terms of its adverse impact on health-related quality of life, limitations in physical function, increased pain and fatigue, and diminished work performance and attendance compared with other debilitating chronic conditions.

Objective: To compare healthcare expenditures, utilization, and productivity-related outcomes for patients with RA using tumor necrosis factor (TNF)-alpha blockers compared with patients with mild, moderate, or severe RA who are not using these medications.

Design and Methods: Patients with RA were identified from the 1998-2007 Medical Expen­d­iture Panel Survey database, using International Classification of Diseases, Ninth Revision, Clinical Modification codes (714.xx); the patients were classified as (1) TNF-alpha blocker users, identified on the basis of pharmacy or intravenous therapy utilization, or (2) TNF-alpha blocker nonusers (but could be using other RA-related medications). Patients who were not using TNF-alpha blockers were subclassified as having mild, moderate, or severe RA; nonusers were not subclassified by disease severity. An algorithm was created for this study that combined and ranked 5 patient-reported health-related outcomes used to classify RA severity in the TNF-alpha blocker nonusers group. The main outcome measures included healthcare expenditures, medical service utilization, and work-related productivity for patients with RA.

Results: A total of 1152 patients were included in this study. TNF-alpha blocker users (N = 65) were found to have lower odds of being unemployed compared with nonusers who had moderate (N = 159) or severe (N = 208) RA, using patients with mild RA as the reference group (N = 720; P <.01 for both comparisons). Only significant results were included in this study. There were no differences between patients with mild RA who were TNF-alpha blocker users versus nonusers with regard to all-cause emergency department visits, hospitalizations, and average length of hospital stay. The medical, prescription, and total healthcare costs were higher for TNF-alpha blocker users than for patients with mild RA who did not use these agents. Patients with moderate or severe RA who did not use TNF-alpha blockers also had higher incremental annual medical expenditures ($1088 and $1640, respectively) than nonusers with mild RA; these incremental cost differences were lower than the difference in users of TNF-alpha blockers ($2096).

Conclusions: Based on this study, the use of TNF-alpha blocker treatment had a positive impact on employment status and was associated with fewer hospitalizations compared with other RA medications and compared with patients who did not use TNF-alpha blockers in patients with moderate or severe RA. The determination of RA severity may be biased, because it was based on patient self-reports and not on provider assessments; however, self-reporting is a common, validated method of assessing RA severity.

Am Health Drug Benefits.
2013;6(2):126-136

Dr Nair is Associate Professor, Skaggs School of Pharmacy and Pharmaceutical Sciences, Center for Pharmaceutical Outcomes Research, University of Colorado Anschutz Medical Campus; Dr Ghushchyan is Assistant Research Professor, Center for Pharmaceutical Outcomes Research, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of Colorado Anschutz Medical Campus; Dr Naim is Associate Director, Health Economics and Outcomes Research, Janssen Scientific Affairs, Johnson & Johnson, Horsham, PA, and Adjunct Assistant Professor of Quality Assurance/Regulatory Affairs, School of Pharmacy, Temple University, Philadelphia, PA.

Rheumatoid arthritis (RA) is a chronic autoimmune disease that causes pain, stiffness, swelling, and loss of function in the joints; it occurs when the patient’s immune system attacks healthy tissue. RA is ranked among the highest of all chronic diseases for its adverse impact on health-related quality of life (QOL), limitations in physical function, increased pain and fatigue, and diminished work performance and attendance.1

Roughly 1.3 million adults in the United States have RA, representing approximately 1% of the population.2,3 Worldwide, approximately 0.5% of the adult population is affected by RA.3 Without optimal treatment, approximately 30% of patients with RA become permanently work disabled within 2 to 3 years of diagnosis.4 Predictors of poor outcomes in the initial stages of RA include a relatively low functional score early in the disease progression, lower socioeconomic status, lower education level, strong family history of the disease, and early involvement of multiple joints.4

The 2008 American College of Rheumatology (ACR) recommendation for first-line pharmacologic treatment of RA is the use of nonbiologic disease-modifying antirheumatic drugs (DMARDs), which have been found to slow the progression of joint destruction when used over the long-term.5 If patients fail to respond to nonbiologic DMARDs, the ACR’s current recommendation is to administer biologic DMARDs, or tumor necrosis factor (TNF)-alpha blockers, to patients with moderate disease activity and poor prognosis, as well as to patients with high disease activity and to patients with RA of intermediate or long duration.5 TNF-alpha blockers target specific components of the immune system, instead of broadly affecting many areas of the immune system, and they intercept TNF in the joints, potentially eliciting rapid improvement of symptoms. These medications are frequently used along with other medications for the treatment of RA. Adalimumab, etanercept, and infliximab are the primary biologic drugs (and TNF-alpha blockers) recommended in the 2008 ACR guidelines.

Aggressive RA treatment with TNF-alpha blockers has been shown to help prevent long-term disability from RA, to improve QOL, and to decrease fatigue, even among patients with mild RA.6-8 The safety and effectiveness of TNF-alpha blockers for the treatment of RA are monitored through the examination of various observational cohorts and registries that have been created to complement information obtained from randomized controlled trials.9 Drug resistance and high cost are major concerns associated with the use of TNF-alpha blocker medications.10

The severity of RA can vary; it is therefore important to classify disease severity (which is assessed in several ways) to help monitor the progression of the disease and to assess the effectiveness of medications and interventions that are designed to treat the disease.11 Accepted methods for determining RA severity are based on the 2010 ACR standards and involve clinical assessment (ie, history, physical examination), laboratory tests (eg, erythrocyte sedimentation rate), and imaging procedures (eg, x-rays, magnetic resonance imaging).12

Because the presentation of RA affects many components of a patient’s functioning, such as physical, functional, and emotional burdens, no single measure can reliably capture disease activity in all patients. One approach used to address this limitation has been the “pooling” of individual measures of disease activity into composite scores.13 Examples of composite disease activity indices that have been used in clinical trials involving RA-based treatments include the Simplified Disease Activity Index, Clinical Disease Activity Index, and Disease Activity Score.14-16 These scales involve measures that are scored using a single number on a continuous scale.

Patient self-reports of RA severity have also been widely used through various validated instruments.17,18 Many factors play a role in how much benefit patients can derive from medications for RA. Measuring a patient’s symptom experience is an important way of amplifying the patient’s voice, and can be clinically impor­tant to aid healthcare professionals in tailoring the use of oral and biologic DMARDs. RA instruments that assess patient-reported outcomes include the Health Assessment Questionnaire (HAQ), the modified HAQ, and the multidimensional HAQ, with questions ranging from 8 to 20 items and assessing various aspects of patient functionality and overall mental health status.19 In these instruments, patients are asked about various aspects of their functionality (eg, dressing themselves, getting out of bed without difficulty, bending), and the degree to which it is difficult to perform these functions on a regular basis. Therefore, patient self-reports of their functional limitations are a widely accepted method of assessing RA severity.17,18

The cost of untreated RA represents a significant financial burden on the US healthcare system and the economy, predominantly because of lost productivity.20,21 Patients, employers, family members or caregivers, payers, and society as a whole share this significant economic burden. A US claims-based analysis of excess payer- and beneficiary-paid costs per patient with RA (compared with matched controls) reported annual excess healthcare costs of $8.4 billion, indirect costs of $10.9 billion, and total annual societal costs of $19.3 billion (including direct, indirect, and intangible costs, such as QOL deterioration).22 According to this analysis, patients incurred an estimated 28% of that burden, employers incurred 33% of that burden, the government spent 20% of the cost, and caregivers incurred an estimated 19% of the total cost. Adding intangible costs of QOL deterioration ($10.3 billion) and premature mortality ($9.6 billion), the total annual societal costs of RA (direct, indirect, and intangible) increased to $39.2 billion.22

Benefits in terms of enhanced productivity and quality-adjusted life-years conferred by the use of TNF-alpha blockers have been demonstrated in several cost-effectiveness analyses.23-25 These evaluations have been based on the concept that, if treated, patients with RA will not progress to a greater disease severity—or will not progress as quickly—and thereby will avoid or defer the high costs and low utilization associated with more severe and progressed disease.26

Previous studies have looked at patterns of TNF-alpha blocker treatment but have not linked these patterns to productivity-based, financial expenditures–based, and utilization-based outcomes.6-8,10 In addition, population-­based studies of patients with RA using nationally representative data sources have not been successful in identifying differences in severity for patients with RA, because the information required to determine RA severity is often not available in these data sources. The Medical Expenditure Panel Survey (MEPS) database, cosponsored by the Agency for Healthcare Research and Quality and the National Center for Health Statistics, is a nationally representative survey of the US civilian noninstitutionalized population.

The uniqueness of the MEPS database lies in its abundance of information, which includes patient self-reported outcomes of functioning and mental health, along with information on sociodemographics, medical utilization, cost of healthcare services, employment, missed workdays, and Short Form (SF)-12 scores. The ability to link these many domains within the MEPS data source allowed the authors of this study to develop different severity categories for RA based on a unique algorithm created by the authors for this study.

This RA severity–ranking algorithm was based on 5 health-related outcomes (ie, SF-12 physical and mental summary scores, patient’s perceived physical and mental health status, and the number of comorbid conditions), which were used to group TNF-alpha blocker nonusers into the 3 mutually exclusive RA severity cohorts—mild, moderate, and severe RA. Patients with RA using TNF-alpha blockers were not grouped using this algorithm and were not ranked. In addition, the MEPS data provide self-reports of work loss because of illness.

The objective of the present study was to use data from the MEPS for the following outcomes—healthcare expenditures, utilization, and self-reported productivity—and to compare these outcomes between patients with RA who are TNF-alpha blocker users and TNF-alpha blocker nonusers with mild, moderate, or severe RA.

Methods
We used 1998-2007 MEPS data that are available for public use. The MEPS is used to collect detailed information on (1) sociodemographic characteristics, such as age, sex, race, ethnicity, and education; (2) economic characteristics, such as employment status, annual wage(s), and missed workdays because of illness and injury; and (3) health characteristics, such as perceived physical and mental health status, SF-12 physical and mental summary scores, health conditions, comorbidities, smoking status, and physical function variables.

Outcome Measures
The main outcomes of interest in the current analysis were healthcare expenditures, medical service utilization, and work-related productivity of patients with RA.

Total annual healthcare expenditures were defined as the sum of all-cause medical and pharmacy expenditures; in addition, medical and pharmacy expenditures were described separately, and were inflation adjusted to 2010 costs.

Medical service utilization and pharmacy components included the all-cause annual number of office-based visits, outpatient visits, hospitalizations, average length of stay for hospitalizations, as well as the annual number of prescribed medications.

Productivity was estimated using multiple measures. First, we studied 1 full year of employment status, which we obtained from respondents’ answers to the annual MEPS. Respondents who were employed during all 3 rounds of the survey within a calendar year were assumed to be employed for a full year. Then, for those who were employed, we studied days (a half day or more) of work missed as a result of illness or injury; and finally, we explored the annual wage differences. Each person in the MEPS database has a record of his/her total annual wages.

The MEPS medical conditions file in the MEPS database contains 3-digit International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) codes based on medical and pharmacy utilization and self-reporting. We identified patients with RA by the presence of the ICD-9 diagnosis code 714, and stratified them into 1 of 2 major groups: TNF-alpha blocker users and TNF-alpha blocker nonusers. Users of TNF-alpha blockers were identified on the basis of pharmacy utilization and/or relevant intravenous therapy at office-based or outpatient visits with the ICD-9-CM diagnosis code 714.

TNF-alpha blocker nonusers were classified into 1 of 3 groups according to RA severity ranking (mild, moderate, or severe) as determined by the algorithm developed for this study (as described below). Users of TNF-alpha blockers were not included in the severity-ranking analysis, because of the assumption that patients with the most severe form of RA were taking these medications, which is typically normative practice for this patient population.

RA Severity Algorithm
The RA severity–ranking algorithm was based on 5 health-related outcomes, which were used to group TNF-alpha blocker nonusers into the 3 mutually exclusive RA severity cohorts. The 5 health-related outcomes included in the algorithm were:

  • SF-12 physical summary score
  • SF-12 mental summary score
  • Patients’ perceived physical status
  • Patients’ perceived mental status
  • Number of comorbid chronic conditions.

The RA severity–ranking algorithm assigned equal weight to each of these 5 variables, with a total severity score ranging from 0 to 5. Patients with a severity score of 0 to 2 were assigned to the “mild RA” cohort, patients with a severity score of 3 were classified as having “moderate RA,” and patients with a severity score of 4 or 5 were classified as the “severe RA” group. The RA severity–ranking algorithm for each patient was based on the following formula:

  • RSF12-P = 1 if a patient’s SF-12 physical summary score was in the bottom quartile (lower SF-12 scores) among all adult patients with RA in the MEPS database, and 0 otherwise
  • RSF12-M = 1 if a patient’s SF-12 mental summary score was in the bottom quartile (lower SF-12 scores) among all adult patients with RA in the MEPS, and 0 otherwise
  • RPH-P = 1 if a patient’s perceived physical score was in the bottom quartile (worse health status) among all adult patients with RA in the MEPS, and 0 otherwise
  • RPH-M = 1 if a patient’s perceived mental score was in the bottom quartile (worse health status) among all adult patients with RA in the MEPS, and 0 otherwise
  • RNCC = 1 if a patient’s number of chronic conditions was in the top quartile (higher number of chronic conditions) among all adult patients with RA in the MEPS, and 0 otherwise.

Therefore, a higher severity score indicates a worse physical and/or mental state and a higher number of chronic comorbidities. Based on this algorithm and on TNF-alpha blocker use, patients in the MEPS-based sample with RA were assigned to 1 of the following 4 mutually exclusive groups—TNF-alpha blocker users, TNF-alpha blocker nonusers with mild RA, TNF-alpha blocker nonusers with moderate RA, and TNF-alpha blocker nonusers with severe RA.

To control for confounding factors in the statistical analyses, several sociodemographic and clinical (comorbidity) characteristics were identified. The number of chronic conditions was calculated by summing the total number of ICD-9-CM codes for chronic conditions reported for each individual, excluding RA, to create a measure of comorbidity burden. The following variables were measured categorically—age (18-29, 30-39, 40-49, 50-59, 60-69, 70-79, ≥80 years); education (no degree, high school degree or equivalent, other degree, bachelor’s degree, master’s degree, PhD); race (white, black, American Indian, other race); ethnicity (Hispanic or non-Hispanic); and insurance coverage (private, public, or uninsured).

Data Analysis
Negative binomial regression was used to estimate the impact of the type of RA group (ie, TNF-alpha blocker user or TNF-alpha blocker nonuser with mild, moderate, or severe RA) on healthcare utilization outcomes and missed workdays. A generalized linear model with log link and gamma distribution was used to estimate the impact of the type of RA group on healthcare expenditures. The Heckman selection model, which is a 2-stage model that is used to estimate the costs for populations that may include individuals with zero costs as well, was used to estimate the impact of the type of RA group on the annual wage. These outcome variables were regressed using the type of RA group (ie, “mild RA” as the reference group), controlling for age, sex, race, ethnicity, region of residence, education, income, type of insurance coverage, and comorbidity. To estimate wages and employment, income was excluded from the models. All analyses were conducted with STATA version 11 (Stata Corporation, College Station, TX).

Table 1
Table 1: Sociodemographic Characteristics.

Results
A total of 1152 patients were included in the study. Approximately 5.6% of the patients (N = 65) were using TNF-alpha blockers. Of the patients with RA who were not using these drugs, 720 patients (62.50% of the study sample) had mild RA, 159 (13.81%) had moderate RA, and 208 (18.05%) had severe RA. The sociodemographic characteristics of all study groups are depicted in Table 1.

Approximately 70% to 75% of the patients in all groups were female. The mean age ranged from 55 to 60 years across the various study cohorts. Between 80% and 90% of all patients were white, and one third of all members resided in the Midwest or the South. The majority of patients (55%-65%) had completed a high school education.

Table 2
Table 2: Differences in Unemployment Rates between the Study Groups.

Outcomes
Productivity (unemployment, missed workdays, and annual wages)
. As shown in Table 2, TNF-alpha blocker nonusers with severe RA were approximately 5 times more likely to be unemployed (incidence rate ratio [IRR], 5.64; P <.000) compared with TNF-alpha blocker nonusers with mild RA.

TNF-alpha blocker nonusers with moderate RA showed a similar trend; they were approximately 3 times more likely to be unemployed (IRR, 3.19; P <.000) compared with TNF-alpha blocker nonusers with mild RA. There was no significant difference between TNF-alpha blocker users and nonusers with mild RA regarding the likelihood of being employed.

Table 3
Table 3: Differences in Missed Workdays between the Study Groups.

With regard to overall missed workdays and workdays that resulted in individuals staying in bed, few differences were seen among the 3 groups when adjusting for various covariates (Table 3). One noticeable difference was that TNF-alpha blocker nonusers with moderate RA were twice as likely to miss workdays by staying in bed compared with TNF-alpha blocker nonusers with mild RA. However, there was no significant difference between TNF-alpha blocker users and nonusers with mild RA, or between TNF-alpha blocker nonusers with severe RA and those with mild RA with regard to the likelihood of missing workdays.

The unadjusted mean number of missed workdays was lowest for TNF-alpha blocker users, ranging from approximately 20 days (moderate and severe RA) to 11 days (mild RA), compared with all other groups. Of note, we were not able to estimate the costs associated with the lost workdays.

With regard to significant differences in wages, TNF-alpha blocker nonusers with moderate RA constituted the only group whose mean wage was significantly lower than that of TNF-alpha blocker nonusers with mild RA ($7175; P <.001).

Table 4
Table 4: Differences in Healthcare Expenditures between the Study Groups (2009 US $).

Healthcare expenditures. The incremental impact on annual medical expenditures, prescribed medication expenditures, and total healthcare expenditures is shown in Table 4. All 3 categories of expenditures were higher for TNF-alpha blocker users compared with nonusers with mild RA. For example, on average, TNF-alpha blocker users spent $2096 more in annual medical expenditures compared with TNF-alpha blocker nonusers with mild RA (the reference group). Similarly, on average, TNF-alpha blocker users spent $2454 more in annual prescribed expenditures and $4880 more in total healthcare expenditures compared with TNF-alpha blocker nonusers with mild RA.

The total healthcare expenditures, on average, were $1864 higher for TNF-alpha blocker nonusers with moderate RA and $2484 higher for TNF-alpha blocker nonusers with severe RA compared with TNF-alpha blocker nonusers with mild RA. Annual prescription expenditures were $611 higher for TNF-alpha blocker nonusers with moderate RA and $698 higher for TNF-alpha blocker nonusers with severe RA compared with patients with mild RA, and annual medical expenditures were $1088 higher for TNF-alpha blocker nonusers with moderate RA and $1640 higher for TNF-alpha blocker nonusers with severe RA compared with TNF-alpha blocker nonusers with mild RA.

Table 5
Table 5: Differences in Healthcare Utilization between the Study Groups.

Healthcare resource utilization. The notable differences in medical service utilization between the various study groups were with regard to all-cause emergency department visits, the number of hospitalizations, the average length of stay for a hospitalization, and the number of prescribed medications (Table 5). Significant differences with regard to emergency department visits and hospitalizations were observed between TNF-alpha blocker nonusers with severe RA and TNF-alpha blocker nonusers with mild RA. The differences in the number of prescribed medications were significant between TNF-alpha blocker users and nonusers with mild RA, as well as between TNF-alpha blocker users with severe RA and nonusers with mild RA.

With regard to emergency department visits and hospitalizations, TNF-alpha blocker nonusers with severe RA were almost twice as likely to incur an emergency department visit (IRR, 1.76; P = .002) and a hospitalization (IRR, 2.24; P = .008) compared with nonusers with mild RA. This group was almost 1.5 times more likely to have a greater length of stay (IRR, 1.65; P = .022) compared with nonusers with mild RA as well. TNF-alpha blocker users had a greater likelihood of having more prescription medications (IRR, 1.49; P <.001) as were nonusers with severe RA (IRR, 1.25; P = .006) and nonusers with moderate RA (IRR, 1.22; P = .012) compared with nonusers of TNF-alpha blockers with mild RA.

Discussion
This study is unique in comparing how TNF-alpha blocker treatment affects patient-reported outcomes versus TNF-alpha blocker nonuse among patients with varying degrees of RA severity. The outcomes examined in this study are more detailed than those observed from claims data alone and emphasize the importance of patient-reported measures in examining how drug treatment can influence key outcomes in the management of RA.

To our knowledge, this is the first study to link patterns of TNF-alpha blocker treatment to patient-reported outcomes. Our results reveal that TNF-alpha blocker treatment confers increased benefit with regard to employment status and is associated with lower rates of hospitalizations and emergency department visits compared with other RA medications and compared with nonuse of TNF-alpha blockers in patients with moderate or severe RA.

As anticipated, one of our key findings was that patients with RA who were using TNF-alpha blockers incurred the highest total healthcare, medical, and prescription expenditures compared with the other RA groups. However, despite these increased costs, we found that patients with severe RA who were not using TNF-alpha blockers had more emergency department visits and hospitalizations and longer hospital stays compared with the other groups.

Another key finding was that TNF-alpha blocker users had a greater likelihood of being employed compared with TNF-alpha blocker nonusers with moderate or severe RA. Unadjusted means also show that TNF-­alpha blocker users were less likely to have missed workdays compared with the other RA groups (ie, users and nonusers), although these differences were not significant. The demonstrated positive impact of TNF-alpha blocker use on employment status may be of importance to employers and to payers alike.

Our study results, although unique, can be corroborated by previously reported findings on TNF-alpha blocker use and the association with productivity. Breedveld showed that early intervention with TNF-inhibitors improves patients’ functional status and health-related QOL, reduces fatigue, decreases job loss, and reduces the amount of work time missed.27 He concluded that although the drug costs are high, TNF-alpha blocker use is cost-effective as a result of the compensation in increased employment and productivity.27

Augustsson and colleagues estimated the effect of TNF-antagonist treatment on workforce participation in a population-based registry of patients with RA, showing that in unadjusted analyses, significant improvements in hours worked weekly were observed in patients at 6 months (mean, +2.4 hours weekly; 95% confidence interval [CI], 1.3-3.5), with further increases compared with baseline at 1-year follow-up (mean, +4.0 hours weekly; 95% CI, 2.4-5.6) and at 2-year follow-up (mean, +6.3 hours weekly; 95% CI, 4.2-8.4), resulting in significant indirect cost benefits.28

In a prospective, single-arm intervention study, Hoving and colleagues evaluated the outcomes and costs associated with a 6-month course of TNF inhibitors by examining their effect on perceived work ability, QOL, and fatigue in patients with RA.7 They reported that all 3 of these outcomes showed a significant improvement in mean scores from baseline at 6 months. There was a 2-fold increase per patient per week (PPPW) in average total direct and indirect costs. Direct costs included costs for TNF inhibitors, other medications, specialist visits, and hospital admissions, as well as costs related to comorbidities and side effects.7 Indirect costs included the costs of productivity losses (absenteeism from paid work because of RA, rests taken at work, and employees’ departures from their jobs). The overall total costs (PPPW) at 6 months were nearly double the costs observed at baseline.7

Our present study confirms the benefits of TNF-alpha blockers with regard to enhancing patients’ productivity, and illustrates the associated direct healthcare expenditures of treating this group of patients with RA, thereby providing a balanced picture of the overall costs and benefits for TNF-alpha blocker users. Employers and other payers can use this information to assess all cost components of managing this RA subgroup of TNF users to make better-informed decisions about coverage and access issues related to TNF-alpha blockers for their members. Such medication data that can demonstrate a tradeoff of savings on other healthcare costs provides additional value for payers. Such tradeoffs can include a return on investments related to workplace productivity, QOL, or activities of daily living.29

Further research is needed to inform clinical decisions such as what point in the RA disease process is the optimal time to initiate TNF-alpha blockers to derive the greatest cost-effectiveness and the most benefit to patients.

Limitations
Certain limitations should be considered when interpreting the results of this study. First, the measure of RA severity was based on patient self-reports of their functioning and level of disability and not on provider assessments. Therefore, the determination of RA severity may be biased, although, as discussed before, patient self-reporting is a validated and common method of assessing RA severity.17,18

In addition, the RA severity–ranking algorithm that was developed for this study has not been previously validated. The small (N = 65) sample of TNF-alpha blocker users may further limit the generalizability of our findings.

We also did not determine how many patients in each of the TNF-alpha blocker nonuser groups were taking any other RA medications. Therefore, we do not know how other RA drug treatment influenced the outcomes we examined. Our goal, however, was to compare the impact of TNF-alpha blocker use and nonuse on patient outcomes.

Furthermore, we examined all-cause and not RA-specific healthcare and pharmacy expenditures and utilization, which may have been influenced by non–RA-related factors. We also did not examine differences between the employed and unemployed patients with RA to determine the incremental impact of employment on the outcomes we measured. Finally, we were unable to measure presenteeism, an important productivity measure that was not available in the MEPS database.

Conclusions
RA is ranked among the highest of all chronic diseases for its adverse impact on health-related QOL, limitations in physical function, increased pain and fatigue, and dim­inished work performance and attendance. TNF-alpha blockers are used for the treatment of patients with RA, but their use is often limited by payers, because of the drugs’ high costs. Our findings highlight that TNF-alpha blockers are able to reduce some of the negative effects of RA and to prevent or minimize the occurrence of high-cost drivers of healthcare utilization (ie, emergency department visits), and potentially keep workers employed longer, a very meaningful goal in these days of lean internal corporate resources. This finding should be of interest to payers when trying to justify the high cost of TNF-alpha blockers, by realizing the potential of these medications to prevent or minimize high-cost drivers of healthcare utilization. However, we would like to use caution in our interpretation of these findings, because only some of these differences were statistically significant.

Acknowledgments
The authors thank Victoria Porter, medical writer, for her assistance with the preparation of this manuscript.

Study Funding
Funding for this study was provided by Janssen Health Services.


Author Disclosure Statement
Dr Nair is a consultant to Janssen and receives grants from Daiichi Sankyo, Janssen, and Takeda. Dr Naim is an employee of Janssen Scientific Affairs and owns stocks of Johnson & Johnson. Dr Ghushchyan has nothing to disclose.

References

  1. Strand V, Khanna D. The impact of rheumatoid arthritis and treatment on patients’ lives. Clin Exp Rheumatol. 2010;28(3 suppl 59):S32-S40.
  2. Helmick CG, Felson DT, Lawrence RC, et al, for 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.
  3. Carmona L, Cross M, Williams B, et al. Rheumatoid arthritis. Best Pract Res Clin Rheumatol. 2010;24:733-745.
  4. Rindfleisch JA, Muller D. Diagnosis and management of rheumatoid arthritis. Am Fam Physician. 2005;72:1037-1047.
  5. Saag KG, Teng GG, Patkar NM, et al. American College of Rheumatology 2008 recommendations for the use of nonbiologic and biologic disease-modifying antirheumatic drugs in rheumatoid arthritis. Arthritis Rheum. 2008;59:762-784.
  6. Lindén C, Björklund A. Living with rheumatoid arthritis and experiencing everyday life with TNF-α blockers. Scand J Occup Ther. 2010;17:326-334.
  7. Hoving JL, Bartelds GM, Sluiter JK, et al. Perceived work ability, quality of life, and fatigue in patients with rheumatoid arthritis after a 6-month course of TNF inhibitors: prospective intervention study and partial economic evaluation. Scand J Rheumatol. 2009;38:246-250.
  8. Bejarano V, Quinn M, Conaghan PG, et al, for Yorkshire Early Arthritis Register Consortium. Effect of the early use of the anti-tumor necrosis factor adalimumab on the prevention of job loss in patients with early rheumatoid arthritis. Arthritis Rheum. 2008;59:1467-1474.
  9. Curtis JR, Jain A, Askling J, et al. A comparison of patient characteristics and outcomes in selected European and US rheumatoid arthritis registries. Semin Arthritis Rheum. 2010;40:2.e1-14.e1.
  10. Delavallée L, Semerano L, Assier E, et al. Active immunization to tumor necrosis factor-alpha is effective in treating chronic established inflammatory disease: a long-term study in a transgenic model of arthritis. Arthritis Res Ther. 2009;11:R195.
  11. Bardwell WA, Nicassio PM, Weisman MH, et al. Rheumatoid Arthritis Severity Scale: a brief, physician-completed scale not confounded by patient self-report of psychological functioning. Rheumatology (Oxford). 2002;41:38-45.
  12. Aletaha D, Neogi T, Silman AJ, et al. 2010 rheumatoid arthritis classification criteria: an American College of Rheumatology/European League Against Rheumatism collaborative initiative. Arthritis Rheum. 2010;62:2569-2581.
  13. Aletaha D, Smolen J. The Simplified Disease Activity Index (SDAI) and the Clinical Disease Activity Index (CDAI): a review of their usefulness and validity in rheumatoid arthritis. Clin Exp Rheumatol. 2005;23(5 suppl 39):S100-S108.
  14. Smolen JS, Breedveld FC, Schiff MH, et al. A simplified disease activity index for rheumatoid arthritis for use in clinical practice. Rheumatology (Oxford). 2003;42: 244-257.
  15. Aletaha D, Nell VP, Stamm T, et al. Acute phase reactants add little to composite disease activity indices for rheumatoid arthritis: validation of a clinical activity score. Arthritis Res Ther. 2005;7:R796-R806.
  16. van der Heijde DM, van ’t Hof MA, van Riel PL, et al. Judging disease activity in clinical practice in rheumatoid arthritis: first step in the development of a disease activity score. Ann Rheum Dis. 1990;49:916-920.
  17. Alten R, Pohl C, Choy EH, et al; OMERACT RA Flare Definition Working Group. Developing a construct to evaluate flares in rheumatoid arthritis: a conceptual report of the OMERACT RA Flare Definition Working Group. J Rheumatol. 2011; 38:1745-1750.
  18. Mason JH, Anderson JJ, Meenan RF, et al. The rapid assessment of disease activity in rheumatology (radar) questionnaire. Validity and sensitivity to change of a patient self-report measure of joint count and clinical status. Arthritis Rheum. 1992;35: 156-162.
  19. Zatarain E, Strand V. Monitoring disease activity of rheumatoid arthritis in clinical practice: contributions from clinical trials. Nat Clin Pract Rheumatol. 2006;2:611-618.
  20. Filipovic I, Walker D, Forster F, Curry AS. Quantifying the economic burden of productivity loss in rheumatoid arthritis. Rheumatology (Oxford). 2011;50:1083-1090.
  21. Franke LC, Ament AJ, van de Laar MA, et al. Cost-of-illness of rheumatoid arthritis and ankylosing spondylitis. Clin Exp Rheumatol. 2009;27(4 suppl 55):S118-S123.
  22. Birnbaum H, Pike C, Kaufman R, et al. Societal cost of rheumatoid arthritis patients in the US. Curr Med Res Opin. 2010;26:77-90.
  23. Davies A, Cifaldi MA, Segurado OG, Weisman MH. Cost-effectiveness of sequential therapy with tumor necrosis factor antagonists in early rheumatoid arthritis. J Rheumatol. 2009;36:16-26.
  24. Kobelt G, Lindgren P, Geborek P. Costs and outcomes for patients with rheumatoid arthritis treated with biological drugs in Sweden: a model based on registry data. Scand J Rheumatol. 2009;38:409-418.
  25. Brennan A, Bansback N, Nixon R, et al. Modelling the cost effectiveness of TNF-alpha antagonists in the management of rheumatoid arthritis: results from the British Society for Rheumatology Biologics Registry. Rheumatology (Oxford). 2007; 46:1345-1354.
  26. Benucci M, Li Gobbi F, Sabadini L, et al. The economic burden of biological therapy in rheumatoid arthritis in clinical practice: cost-effectiveness analysis of sub-cutaneous anti-TNFalpha treatment in Italian patients. Int J Immunopathol Pharmacol. 2009;22:1147-1152.
  27. Breedveld F. The value of early intervention in RA—a window of opportunity. Clin Rheumatol. 2011;30(suppl 1):S33-S39.
  28. Augustsson J, Neovius M, Cullinane-Carli C, et al. Patients with rheumatoid arthritis treated with tumour necrosis factor antagonists increase their participation in the workforce: potential for significant long-term indirect cost gains (data from a population-based registry). Ann Rheum Dis. 2010;69:126-131.
  29. 29. Solomon DH. The comparative safety and effectiveness of TNF-alpha antagonists [corrected]. J Manag Care Pharm. 2007;13(1 suppl):S7-S18.
Stakeholder Perspective
Assessing the Value of TNF-Alpha Blockers for Patients with Rheumatoid Arthritis
Michael S. Jacobs, RPh
MSA & Associates
Sandy Springs, GA

Modern pharmaceutical therapies, such as tumor necrosis factor (TNF)-alpha blockers for patients with rheumatoid arthritis, have approached being perceived as “magic” for many patients with this condition and their physicians.

PAYERS: These therapies, however, often exceed tens of thousands of dollars annually in cost on a per-­patient basis and are therefore a difficult “sale” to payers of all types (with the possible exception of the government), who are concerned with the value of the investment itself, or at least with the alternative value that can be purchased for this substantial financial investment in an individual’s healthcare. When health plan sponsors examine the impact that TNF-alpha blockers have in the more global context of payer thought and decision-making processes, such as budgeting, the coverage rules and coverage decisions become even murkier for payers.

When the relatively improved clinical efficacy associated with these therapies is compared with the efficacy of substantially less expensive alternate therapies, and with the “value” that is being purchased, appropriate cost-sharing burden levels become a true concern for all stakeholders—payers, patients, and family members. And when all of these dimensions of therapy and coverage components are combined, these questions not only concern the patients themselves but also the impact these issues have on family members, coworkers, and, of course, plan sponsors. All of this “noise,” regretfully, can obscure the identified and promised clinical value of the therapy with TNF-alpha blockers.

PATIENTS/PHYSICIANS: According to the study presented by Nair and colleagues, patients with rheumatoid arthritis who were receiving TNF-alpha blocker therapy were found to have lower odds of being unemployed compared with nonusers of this therapy who had moderate or severe disease. From a patient (and most likely a physician) perspective, this therapy is a significant advancement in the treatment of rheumatoid arthritis. From a cost perspective, the payer will need to address a number of questions, such as, “Would this patient be employed even with this therapy?” or “Is the economic value of the employment reasonable when the cost of the employment, including therapy, combined with the other costs of employment, such as wages and taxes, is calculated?”

EMPLOYERS: Employers, who are often the health plan sponsors themselves, pay wages based on a number of considerations and variables, including the value received for the work effort performed and the financial compensation paid. According to the Bureau of Business and Economic Research at the University of New Mexico, the average annual wage in the United States in 2011 (preliminary estimate) was $48,301.1 If we add to this amount the cost of expensive therapies, such as those identified in the present study, the question now becomes, “Is this employee worth the total cost of employment?” This is one question that should be addressed in the near future, as these expensive therapies become more common within the healthcare system.

Dr Murphy is the Chief Medical Officer and Scientific Officer, Worldwide Clinical Trials, King of Prussia, PA

  1. Bureau of Business and Economic Research. Annual average wage/salary disbursements per job, U.S. and States 2000-2011. Revised October 12, 2012. http://bber.unm.edu/econ/us-wage.htm. Accessed April 9, 2013.
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