Abstract
BACKGROUND:
Alopecia areata (AA) is an autoimmune disorder characterized by hair loss. Patients may present with hair loss of the scalp, eyelashes, eyebrows, and/or body. Alopecia totalis (AT), total scalp hair loss, or alopecia universalis (AU), total body hair loss, are extensive forms. Although the impact of AA on quality of life is understood, evidence of its economic burden is limited. A better understanding of the all-cause health care costs for health plans and patients with AA is critical to comprehend disease burden.
OBJECTIVE:
To evaluate all-cause health care resource utilization and direct health care costs in US adults with AA with or without AT or AU, vs matched control subjects.
METHODS:
Patients (≥ 18 years) with AA with no less than 2 claims of AA at diagnosis (October 31, 2015, to March 3, 2018) were identified in the IBM MarketScan Commercial Claims and Encounters and Medicare Supplemental databases. Patients were enrolled no less than 12 months before and after first diagnosis (index). Patients were grouped according to AT or AU status (AT/AU group) or AA without AT/AU (non-AT/AU group) and matched 1:3 to control subjects without AA/AT/AU. Summary statistics were calculated for demographic and clinical characteristics at baseline and follow-up.
RESULTS:
At baseline, there were 14,972 adult patients with AA and 44,916 control subjects. Of patients with AA, 1,250 and 13,722 were in the AT/AU and non-AT/AU groups, respectively. A significantly greater proportion of patients with AA had atopic and autoimmune comorbidities vs control subjects. After index, patients with AA used significantly more corticosteroid treatments (injectable/oral/topical) than control subjects. A greater mean number of annual outpatient and dermatologist visits was observed for both AA groups vs control subjects (outpatient visits: AT/AU group: 17.8 vs 11.8; non-AT/AU group: 15.4 vs 11.2; dermatologist visits: AT/AU group: 3.4 vs 0.4; non-AT/AU group: 3.4 vs 0.4; P < 0.001 for all). Mean total all-cause medical and pharmacy costs (2018 US$) were higher in both AA groups vs control subjects (AT/AU group: $18,988 vs $11,030; non-AT/AU group: $13,686 vs $9,336; P < 0.001 for both). Patient out-of-pocket costs were higher for AA vs control subjects (AT/AU group: $2,685 vs $1,457; non-AT/AU group: $2,223 vs $1,341; P < 0.001 for both).
CONCLUSIONS:
Compared with control subjects, patients with AA are more likely to have atopic and autoimmune comorbidities, to use corticosteroids, and to make outpatient visits. Patients with AA have greater all-cause medical (including pharmacy) and out-of-pocket costs. The difference in total medical costs for patients with AT/AU vs control subjects is higher than the difference for patients with non-AT/AU vs control subjects.
Plain language summary
Information on the medical costs involved in the care of people with alopecia areata (AA) is limited, but mounting evidence points to significant financial impact for patients with AA. This study explored health care use and medical costs among commercially insured adults with AA in the United States. Patients with AA face greater all-cause medical and out-of-pocket costs, make more health care outpatient visits, and use more corticosteroids than patients without AA.
Implications for managed care pharmacy
Patients with AA face greater all-cause medical and out-of-pocket costs, make more health care outpatient visits, and use more corticosteroids than matched control subjects without AA. Greater incremental cost differences were observed between adults with more severe phenotype (alopecia totalis/alopecia universalis) vs matched control subjects. These findings highlight the overall substantial burden associated with AA in adults and provide new insights into the relative burden of alopecia totalis/alopecia universalis disease. This information may help guide resource allocation in the management of AA.
Alopecia areata (AA) is an immune-mediated disorder that causes hair loss.1 Patients with AA can present with hair loss that may occur suddenly and unpredictably. Hair loss may involve loss of small patches of scalp hair; complete loss of scalp hair (known as alopecia totalis [AT]); or complete loss of scalp, facial, and body hair (known as alopecia universalis [AU]).2-4 AA affects up to 147 million people worldwide, and as many as 6.8 million people in the United States, where there is a lifetime prevalence risk ranging between 1.7% and 2.51%.5-8
Between 34% and 50% of patients with AA have been reported to experience spontaneous regrowth of their hair within 1 year; however, most will experience multiple episodes of AA.9 In about half of patients, AA is a chronic relapsing, remitting autoimmune disease that persists beyond 12 months,10,11 and approximately 7%-36% of patients with AA ultimately experience either AT or AU.6,12 The development of AA is frequently associated with psychological impacts such as anxiety and depression and reduced health-related quality of life.13-19 Patients with AA may present with other autoimmune or atopic comorbidities such as systemic lupus erythematosus, thyroid disorders, vitiligo, psoriasis, and atopic dermatitis.8,20,21 There are no FDA-approved therapies for AA, and effective treatments for persistent or extensive disease are lacking.9 Commonly used approaches for treating AA include, among others, immunosuppressants, such as corticosteroids, and topical immunotherapies, eg, squaric acid dibutylester and diphenylcyclopropenone.22
Evidence on the economic burden among patients with AA is limited, although accruing data points to a significant financial impact of the disease for patients.23,24 A better understanding of the economic impact of AA is crucial to understand the burden to the individual patient and the health care system, identify the drivers of this burden, and appropriately allocate financial resources for cost efficiencies and address patient unmet needs.
The objective of this study was to analyze health care resource utilization (HCRU) and all-cause direct health care costs (medical and pharmacy), including payer and out-of-pocket (OOP) costs (such as enrollee deductible, copayments, and coinsurance) in the US adult population of patients with AA with or without AT/AU vs their matched control groups (ie, without AA/AT/AU).
Methods
STUDY DESIGN AND PATIENT SELECTION
A retrospective cohort study comparing privately insured adult patients with AA with matched control subjects without AA was conducted (Supplementary Figure 1 (63.9KB, pdf) , available in online article). All patients with AA had no less than 2 claims with a diagnosis of AA (International Classification of Diseases, Tenth Revision, Clinical Modification [ICD-10-CM] code: L63.x)25 on different dates of service from October 31, 2015, to March 31, 2018. Individuals in the cohort of suitable control subjects without AA were required to have no claims with AA diagnosis throughout the study period. The index date was defined as the date of the first diagnosis of AA for patients with AA; for control subjects, the index date was the date of a random medical claim incurred during the study period. Patients in both cohorts were required to be aged 18 years or older on the index date and continually enrolled in a health insurance plan for no less than 12 months before and after the index date. The baseline period was defined as the 12-month period prior to the index date, and the follow-up period was defined as the 12-month period after the index date.
Patients with AA included in the analysis were grouped according to whether they had AT or AU (AT/AU group) or AA without AT or AU (non-AT/AU group). Patients with AT/AU were identified by at least one diagnosis of AT (ICD-10-CM: L63.0) or AU (ICD-10-CM: L63.1) on the index date or at any point thereafter. Patients in the AT/AU and non-AT/AU groups were separately matched 1:3 with non-AA control subjects based on age, sex, region, index year, health insurance type, and Charlson Comorbidity Index score.
DATA SOURCE
This study used the IBM MarketScan Commercial Claims and Encounters and Medicare Supplemental databases, which contain health insurance records from approximately 100 different insurance providers and third-party administrators in the United States. The databases include demographics, insurance type and enrollment history, and claims for medical (provider and institutional) and outpatient pharmacy services. Inpatient service records are available at both the claim level and summarized stay level. Data are deidentified and comply with the patient confidentiality requirements of the Health Insurance Portability and Accountability Act. As a result, no institutional review board approval was required.
STATISTICAL ANALYSIS
Summary statistics were calculated for demographic and clinical characteristics at baseline and for HCRU, medication use, and all-cause costs, including medical and pharmacy costs and OOP costs to the patient during the follow-up period. Mean and SD were reported for continuous variables, whereas frequencies and proportions were reported for binary/categorical variables.
Results
PATIENT DEMOGRAPHICS
After applying inclusion and exclusion criteria, the study included a total of 14,972 adult patients with AA and 44,916 control subjects (Figure 1). Of the adult patients with AA, 1,250 were in the AT/AU group and 13,722 were in the non-AT/AU group. The mean (SD) age of all patients with AA was 43.5 (13.5) years, and 65.3% were female. For the AT/AU group, the mean (SD) age was 45.7 (13.7) years, and 72.2% were female (Table 1). For the non-AT/AU group, the mean (SD) age was 43.3 (13.5) years, and 64.7% were female.
FIGURE 1.
Sample Selection
TABLE 1.
Baseline Patient Demographics and Clinical Characteristics
| Characteristic | AT/AU N = 1,250 | Matched control subjects N = 3,750 | P value | Non-AT/AU N = 13,722 | Matched control subjects N = 41,166 | P value |
|---|---|---|---|---|---|---|
| Age, mean ± SD, y | 45.7 ± 13.7 | 45.7 ± 13.7 | 1.000 | 43.3 ± 13.5 | 43.3 ± 13.5 | 1.000 |
| Age group, n (%), y | ||||||
| 18-44 | 557 (44.6) | 1,671 (44.6) | 1.000 | 7,181 (52.3) | 21,543 (52.3) | 1.000 |
| 45-64 | 625 (50.0) | 1,875 (50.0) | 5,984 (43.6) | 17,952 (43.6) | ||
| 65+ | 68 (5.4) | 204 (5.4) | 557 (4.1) | 1,671 (4.1) | ||
| Sex, n (%) | ||||||
| Female | 903 (72.2) | 2,709 (72.2) | 1.000 | 8,878 (64.7) | 26,634 (64.7) | 1.000 |
| Male | 347 (27.8) | 1,041 (27.8) | 4,844 (35.3) | 14,532 (35.3) | ||
| Region, n (%) | ||||||
| South | 497 (39.8) | 1,491 (39.8) | 1.000 | 5,403 (39.4) | 16,209 (39.4) | 1.000 |
| Northeast | 356 (28.5) | 1,068 (28.5) | 3,602 (26.2) | 10,806 (26.2) | ||
| Midwest | 228 (18.2) | 684 (18.2) | 2,351 (17.1) | 7,053 (17.1) | ||
| West | 169 (13.5) | 507 (13.5) | 2,366 (17.2) | 7,098 (17.2) | ||
| Insurance type, n (%) | ||||||
| Managed carea | 956 (76.5) | 2,868 (76.5) | 1.000 | 10,537 (76.8) | 31,611 (76.8) | 1.000 |
| Consumer-drivenb | 254 (20.3) | 762 (20.3) | 2,739 (20.0) | 8,217 (20.0) | ||
| Comprehensive | 40 (3.2) | 120 (3.2) | 446 (3.3) | 1,338 (3.3) | ||
| CCI, n (%) | ||||||
| Group 0 | 975 (78.0) | 2,925 (78.0) | 1.000 | 11,583 (84.4) | 34,749 (84.4) | 1.000 |
| Group 1-2 | 254 (20.3) | 762 (20.3) | 1,981 (14.4) | 5,943 (14.4) | ||
| Group 3-4 | 18 (1.4) | 54 (1.4) | 142 (1.0) | 426 (1.0) | ||
| Group 5 + | 3 (0.2) | 9 (0.2) | 16 (0.1) | 48 (0.1) | ||
| Comorbidities, n (%) | ||||||
| Anemia | 60 (4.8) | 95 (2.5) | < 0.001 | 453 (3.3) | 935 (2.3) | < 0.001 |
| Any atopic disorderc | 271 (21.7) | 662 (17.7) | 0.002 | 2,551 (18.6) | 6,045 (14.7) | < 0.001 |
| Any autoimmune disorderd | 233 (18.6) | 537 (14.3) | < 0.001 | 1,898 (13.8) | 4,984 (12.1) | < 0.001 |
| Any cardiovascular disordere | 191 (15.3) | 553 (14.7) | 0.680 | 1,861 (13.6) | 5,472 (13.3) | 0.430 |
| Any mental health disorderf | 246 (19.7) | 782 (20.9) | 0.396 | 2,558 (18.6) | 8,078 (19.6) | 0.012 |
| Thyroid disorder | 288 (23.0) | 573 (15.3) | < 0.001 | 2,216 (16.1) | 5,239 (12.7) | < 0.001 |
| Rheumatic disease | 64 (5.1) | 91 (2.4) | < 0.001 | 346 (2.5) | 751 (1.8) | < 0.001 |
| Peripheral vascular disease | 27 (2.2) | 62 (1.7) | 0.294 | 219 (1.6) | 496 (1.2) | < 0.001 |
Means and SDs are shown for continuous characteristics; counts and percentages are shown for categorical characteristics, unless otherwise noted.
a Composite of health maintenance organization, preferred provider organization, point of service, and exclusive provider organization plans.
b Composite of consumer-driven health plans and high-deductible health plans.
c Composite of atopic disorders including allergic rhinitis, asthma, atopic dermatitis, celiac disease, chronic urticaria, and conjunctivitis.
d Composite of ankylosing spondylitis, Crohn’s disease, diabetes mellitus type 1, Hashimoto’s disease, psoriasis, rheumatoid arthritis, systematic lupus erythematosus, Sjögren’s syndrome, ulcerative colitis, and vitiligo.
e Composite of atherosclerosis, chest pain, dyspnea, heart palpitations, and shortness of breath.
f Composite of attention deficit hyperactivity disorder, anxiety disorders, depression, obsessive-compulsive disorder, and substance abuse.
AT = alopecia totalis; AU = alopecia universalis; CCI = Charlson Comorbidity Index; y = years.
BASELINE COMORBIDITIES
AT/AU vs Matched Control Subjects.
Anemia (4.8% vs 2.5%; P < 0.001), rheumatic disease (5.1% vs 2.4%; P < 0.001), and thyroid disorder (23.0% vs 15.3%; P < 0.001) were more prevalent in patients with AT/AU than in the matched control subjects at baseline (Table 1); a greater proportion of patients had any atopic disease (21.7% vs 17.7%; P = 0.002). Atopic comorbidity differences between the patients with AT/AU and matched control subjects included allergic rhinitis (12.8% vs 9.9%; P = 0.005), atopic dermatitis (4.0% vs 1.3%; P < 0.001), chronic urticaria (0.6% vs 0.1%; P = 0.003), and conjunctivitis (2.7% vs 1.7%; P = 0.029).
Compared with matched control subjects, patients with AT/AU were more likely to have autoimmune diseases (18.6% vs 14.3%; P < 0.001), including Hashimoto’s disease (3.5% vs 1.3%; P < 0.001), psoriasis (3.0% vs 1.4%; P < 0.001), rheumatoid arthritis (3.0% vs 1.5%; P < 0.001), Sjögren’s syndrome (1.3% vs 0.2%; P < 0.001), systemic lupus erythematosus (1.6% vs 0.9%; P = 0.046), and vitiligo (0.3% vs 0.0%; P = 0.004).
Non-AT/AU vs Matched Control Subjects.
Anemia (3.3% vs 2.3%; P < 0.001), rheumatic disease (2.5% vs 1.8%; P < 0.001), thyroid disorder (16.1% vs 12.7%; P < 0.001), heart palpitations (3.8% vs 3.2%; P = 0.005), and hearing loss (1.7% vs 1.3%; P = 0.003) were more prevalent in the non-AT/AU group than in the matched control group at baseline. A greater proportion of patients had any atopic disease (18.6% vs 14.7%; P < 0.001). Atopic comorbidities with significant differences between the patients in the non-AT/AU group and the matched control subjects included allergic rhinitis (11.7% vs 9.3%; P < 0.001), atopic dermatitis (2.4% vs 0.9%; P < 0.001), conjunctivitis (2.3% vs 1.4%; P < 0.001), and chronic urticaria (0.5% vs 0.2%; P < 0.001) at baseline.
Compared with the matched control group, a greater proportion of patients with non-AT/AU had any of the considered autoimmune diseases (13.8% vs 12.1%; P < 0.001), including Hashimoto’s disease (1.6% vs 0.9%; P < 0.001), psoriasis (2.3% vs 1.2%; P < 0.001), systemic lupus erythematosus (1.3% vs 0.5%; P < 0.001), Sjögren’s syndrome (0.7% vs 0.3%; P < 0.001), ulcerative colitis (0.6% vs 0.4%; P = 0.013), or vitiligo (0.3% vs 0.1%; P < 0.001) at baseline.
MEDICATION USE AND HCRU
At baseline, the proportion of patients in the AT/AU and non-AT/AU groups using corticosteroid treatments was higher (in some cases approximately 4-fold greater) vs their matched control groups (injectable corticosteroids: AT/AU group, 17.9% vs 4.9% and non-AT/AU group, 18.4% vs 4.4%; oral corticosteroids: non-AT/AU group, 11.8% vs 10.4%; and topical corticosteroids: AT/AU group, 16.8% vs 4.3%, and non-AT/AU groups, 14.0% vs 3.7%; P < 0.001 for all comparisons; except oral corticosteroids in the AT/AU group, 14.8 vs 12.1%; P = 0.015). After index, a similar trend was observed, although topical and injectable corticosteroid use was ~6- to ~12-fold greater for patients across the AT/AU and non-AT/AU groups (injectable corticosteroids: AT/AU group, 36.7% vs 5.7% and non-AT/AU group, 57.9% vs 4.9%; oral corticosteroids: AT/AU group, 19.8% vs 13.4% and non-AT/AU group, 14.1% vs 12.0%; and topical corticosteroids: AT/AU group, 28.3% vs 4.1% and non-AT/AU group, 32.4% vs 3.6%) vs their matched control groups (P < 0.001 for all comparisons; Table 2).
TABLE 2.
Post-Index Drug Use, HCRU Visits, and All-Cause Costs
| Characteristic | AT/AU N = 1,250 | Matched control subjects N = 3,750 | P value | Non-AT/AU N = 13,722 | Matched control subjects N = 41,166 | P value |
|---|---|---|---|---|---|---|
| Drug use, n (%) | ||||||
| Antidepressants | 279 (22.3) | 833 (22.2) | 0.969 | 2,550 (18.6) | 8,475 (20.6) | < 0.001 |
| Anxiolytics | 198 (15.8) | 489 (13.0) | 0.015 | 1,661 (12.1) | 4,798 (11.7) | 0.162 |
| Injectable corticosteroids | 459 (36.7) | 213 (5.7) | < 0.001 | 7,944 (57.9) | 2,019 (4.9) | < 0.001 |
| Oral corticosteroids | 248 (19.8) | 504 (13.4) | < 0.001 | 1,937 (14.1) | 4,926 (12.0) | < 0.001 |
| Topical corticosteroids | 354 (28.3) | 155 (4.1) | < 0.001 | 4,446 (32.4) | 1,498 (3.6) | < 0.001 |
| HCRU, annual visits, mean ± SD | ||||||
| PPPY outpatient visits | 17.8 ± 15.6 | 11.8 ± 14.1 | < 0.001 | 15.4 ± 14.8 | 11.2 ± 13.8 | < 0.001 |
| Dermatologist visits | 3.4 ± 5.0 | 0.4 ± 1.6 | < 0.001 | 3.4 ± 3.7 | 0.4 ± 1.4 | < 0.001 |
| HCRU, any visits, n (%) | ||||||
| Dermatologist visits | 860 (68.8) | 767 (20.5) | < 0.001 | 11,223 (81.8) | 7,691 (18.7) | < 0.001 |
| Costs (US$), mean ± SD | ||||||
| Total medical and pharmacy | 18,988 ± 69,749 | 11,030 ± 41,463 | < 0.001 | 13,686 ± 44,921 | 9,336 ± 34,581 | < 0.001 |
| Medical costs | 15,140 ± 65,665 | 8,959 ± 39,678 | < 0.001 | 11,514 ± 43,281 | 7,482 ± 30,907 | < 0.001 |
| Outpatient costs | 10,277 ± 51,339 | 5,713 ± 26,730 | < 0.001 | 8,078 ± 28,696 | 4,672 ± 20,078 | < 0.001 |
| Dermatologist costs | 732 ± 1,559 | 105 ± 631 | < 0.001 | 674 ± 1,537 | 80 ± 624 | < 0.001 |
| Pharmacy costs | 3,849 ± 12,335 | 2,071 ± 8,114 | < 0.001 | 2,172 ± 8390 | 1,855 ± 13,157 | 0.008 |
| Corticosteroid pharmacy costs | 106±355 | 13.9 ± 306 | < 0.001 | 95 ± 391 | 8.5 ± 96 | < 0.001 |
| Other AA-related pharmacy costs | 870 ± 6,440 | 106 ± 1,939 | < 0.001 | 164 ± 3,560 | 85 ± 2,271 | 0.003 |
| Total OOP costs | 2,685 ± 3,001 | 1,457 ± 1,959 | < 0.001 | 2,223 ± 2,651 | 1,341 ± 2,012 | < 0.001 |
Mean and SD are shown for continuous characteristics; counts and percentage are shown for categorical characteristics, unless otherwise noted.
OOP costs include enrollee payments made toward deductible, copays, and coinsurance.
AA = alopecia areata; AT = alopecia totalis; AU = alopecia universalis; HCRU = health care resource utilization; OOP = out-of-pocket; PPPY = per-patient-per year.
The use of immunomodulators such as methotrexate or cyclosporine was also greater compared with matched control subjects after index (methotrexate: AT/AU group: 3.1% vs 0.7%; non-AT/AU group: 0.9% vs 0.5%; cyclosporine: AT/AU group: 1.4% vs 0.1; non-AT/AU group 0.2% vs 0%; all P < 0.001). Although anxiolytic use was comparable among patients in the non-AT/AU group vs matched control subjects after index (12.1% vs 11.7%; P = 0.162), the rate of use was greater in the AT/AU group (15.8% vs 13.0%; P = 0.015). Use of antidepressants was comparable among patients in the AT/AU group vs matched control subjects (22.3% vs 22.2%; P = 0.969) but was lower among patients in the non-AT/AU group (18.6% vs 20.6%; P < 0.001).
After index, relative to matched control subjects, patients with AA had greater mean rates per-patient per-year (PPPY) of outpatient visits (AT/AU group: 17.8 vs 11.8; non-AT/AU group: 15.4 vs 11.2; P < 0.001 for both) and dermatologist visits (AT/AU group: 3.4 vs 0.4; non-AT/AU group: 3.4 vs 0.4; P < 0.001 for both; Table 2).
HEALTH CARE COSTS
After index, mean PPPY total medical and pharmacy costs (US$) were higher for patients in the AT/AU and non-AT/AU groups compared with their respective matched control groups: AT/AU group: $18,988 vs $11,030; non-AT/AU group: $13,686 vs $9,336; P < 0.001 for both (Table 2 and Figures 2 and 3). Medical costs (US$) in the AT/AU and non-AT/AU groups were largely driven by outpatient costs: AT/AU group: $10,277 vs $5,713; non-AT/AU group: $8,078 vs $4,672; P < 0.001 for both (Table 2 and Figures 2 and 3). Mean pharmacy costs (US$) were also higher for patients in the AT/AU and non-AT/AU groups vs their matched control groups: AT/AU group: $3,849 vs $2,071; non-AT/AU group: $2,172 vs $1,855; P < 0.001 and P = 0.008, respectively (Table 2 and Figures 2 and 3).
FIGURE 2.
Post-Index All-Cause Costs: Patients With AT/AU vs Matched Control Subjects
FIGURE 3.
Post-Index All-Cause Costs: Non-AT/AU Patients vs Matched Control Subjects
In addition, OOP costs (US$) were higher in the AT/AU and non-AT/AU groups compared with their matched control groups without AA/AT/AU: AT/AU group: $2,685 vs $1,457; non-AT/AU group: $2,223 vs $1,341; P < 0.001 for both (Table 2 and Figures 2 and 3).
Discussion
Although there are no approved treatments for AA, it is important to understand medication use, HCRU, and all-cause costs to the health care system and to the individual in informing decision-makers on appropriate resource allocation. This study is among the first to document the all-cause costs of a large cohort of commercially insured adults with AA in the United States. Specifically, this study evaluated medication use, all-cause HCRU, and all-cause medical costs among patients with an extensive form of AA (AT/AU) and those with AA but without AT/AU. All findings were compared with matched controls (without AA/AT/AU) with a 1:3 matching by age, sex, Charlson Comorbidity Index, region, and insurance type.
A greater proportion of patients included in the study reported concomitant anemia, atopic dermatitis, and autoimmune comorbidities, including Hashimoto’s disease, psoriasis, rheumatoid arthritis, Sjogren’s syndrome, and systemic lupus erythematosus, compared with non-AA matched control subjects. This finding is consistent with previous literature that has suggested an association of AA with diverse systemic diseases such as atopic and autoimmune comorbidities,21 although for some of the comorbidities, the rates were comparable between the groups despite reaching statistical significance as a result of the large sample size. Thus, in addition to treating AA, an overall evaluation of comorbidities among patients may be valuable in providing quality care and improving overall patient health outcomes.
Commonly used current treatment approaches include immunotherapies such as corticosteroids, cyclosporine, and methotrexate. Other options include azathioprine, mycophenolate, sulfasalazine, squaric acid dibutylester, and diphenylcyclopropenone. However, to date, reliable treatments for AA are lacking. In the current study, corticosteroid use was substantially higher in patients with AA than in matched control subjects, with patients in the AT/AU group having a higher use of oral corticosteroids than those in the non-AT/AU group, and patients in the non-AT/AU group having a higher use of topical and injectable corticosteroids than those in the AT/AU group. Although these observed patterns tend to confirm a priori expectations based on the severity of AA and thus suggest that the corticosteroid treatments used are indeed used for treating AA, these treatments could also be used for other comorbidities.
The study also highlights the association of AA (AT/AU or non-AT/AU) with higher medical and pharmacy costs vs matched control subjects, including higher OOP costs. These costs are driven in part by a greater number of PPPY outpatient visits and dermatologist visits for patients with AA, which potentially reflects a combination of visits directly related to AA and treatment of comorbidities known to be associated with AA, including other autoimmune diseases, rheumatic diseases, and psychiatric conditions.21
Overall, these findings are in line with other recently conducted studies that demonstrated the large economic burden associated with AA in adults.23,24,26 This study expands upon that work by looking at the resource use, costs, and comorbidities in AA with and without AT/AU relative to non-AA. For example, a 2018 survey conducted in 675 participants with AA found hair appointments (n = 552 [81.8%]) and vitamins and/or supplements (n = 457 [67.7%]) to be the most common sources of OOP costs.24 The median yearly spending was highest for cosmetic items or headwear (US$450; IQR, US$50-$1,500).24 It is also possible that the difference in all-cause HCRU and costs are at least partially due to the AA-associated comorbidities, not AA itself, although some AA-associated comorbidities may be based on similar underlying inflammatory or autoimmune mechanisms.27,28
LIMITATIONS
These data must be interpreted in the context of our study design. As this was a retrospective claims analysis conducted using IBM MarketScan Commercial and Medicare databases, the findings may be limited in generalizability to those who are uninsured or do not have employer-sponsored insurance. This study explored the AA disease burden in adult patients and cannot be generalized to other age cohorts such as adolescents and pediatric patients. The OOP costs in this study are those borne by the patient and that are cost-shared through their insurance billing data and do not represent other OOP costs that patients may incur for AA treatment that are not covered by their insurer.24 Claims-based studies may be subject to incomplete, inaccurate, or missing data that could bias the results. This limitation was minimized by only including patients who had continuous health plan enrollment and no less than 2 claims with a diagnosis of AA. The comparisons between AA and control groups may also have been subject to unmeasured confounders not included in the matching algorithm.
Although the study examined all-cause HCRU and costs, the lack of approved treatments and available payer coverage limited our ability to examine AA-specific HCRU and costs and as such would underestimate the true cost burden of AA. However, this study benefits from a very large population sample, leading to a well-powered analysis. The procedure of matching patients with AA to control subjects allows for a balanced comparison of the economic burden in AA, including for the subgroup analysis of patients with AT/AU. Owing to a lack of clinical information in administrative claims, patients with a diagnosis of AA could not be stratified by extent of scalp hair loss, aside from AT and AU subtypes.
Conclusions
Collectively, these findings highlight the overall substantial burden associated with AA in adults and provide new insights into the relative burden of AT/AU disease. Patients with AA reported more atopic and autoimmune comorbidities, higher use of corticosteroids, and higher rate of outpatient visits than matched control subjects. The differences in HCRU and medication use also resulted in higher payer and patient OOP costs in AA/AT/AU groups than in matched control subjects.
ACKNOWLEDGMENTS
Medical writing support was provided by David Sunter, PhD, of Engage Scientific Solutions and was funded by Pfizer.
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