Abstract
BACKGROUND:
The recent expansion of US Food and Drug Administration–approved treatment options for moderate to severe atopic dermatitis (AD) has notably improved clinical management options. With the availability of these novel therapies, data on frequency of therapy switching and differences in health care resource utilization (HCRU) and costs between switchers and nonswitchers are limited.
OBJECTIVE:
To evaluate the frequency of treatment switching from first- to second-line systemic targeted therapies and compare HCRU and costs between switchers and nonswitchers among commercially insured US patients with moderate to severe AD.
METHODS:
We conducted a retrospective cohort study in which adult patients with AD initiating a first systemic targeted therapy (index date) between January 1, 2022, and December 31, 2022, were identified and followed for at least 1 year from index date. Two cohorts were classified based on whether switching occurred over follow-up. All-cause and AD-related HCRU oucomes, including hospitalizations, emergency department (ED) visits, and outpatient services, and associated costs were compared between switchers and nonswitchers during the follow-up period.
RESULTS:
After approximately 1 year following the initiation of first-line systemic targeted therapy, 466 (5.8%) switched to second-line systemic targeted therapy among the 8,063 patients with moderate to severe AD included in this study. Nearly all switchers (96.4%) had at least 1 AD-related outpatient service compared with 82.8% for nonswitchers (P < 0.01), and the annualized rate of visits was higher among switchers compared with nonswitchers (4.9 vs 3.1, P < 0.01). AD-related hospitalizations and ED visits were rare. Mean total AD-related health care costs across the annualized follow-up period were also significantly higher among switchers compared with nonswitchers ($59,876 vs $51,327; P < 0.01), with drug costs accounting for approximately 99% of AD-related health care expenditures in both groups.
CONCLUSIONS:
We found a small proportion (5.8%) of patients switched from first- to second-line systemic targeted therapy after a median follow-up of approximately one year. Patients who switched therapies incurred significantly higher AD-related outpatient service use and total health care costs compared with nonswitchers, which may potentially reflect either worsening disease severity or inadequate response or intolerability to first-line therapy. These findings emphasize the increased importance of personalized considerations for the selection of first-line systemic targeted therapy for patients with moderate to severe AD to reduce downstream economic burden. As additional therapies become available, future research exploring reasons for treatment switching and patient factors influencing response will be critical to guide clinical and formulary decision-making in this evolving treatment landscape.
Plain language summary
This study looked at health care use and costs for patients with moderate to severe atopic dermatitis (AD) who did or did not switch from their first-line treatments. We found few patients ended up switching, and those who did switch had more provider visits and higher costs than those who continued receiving the same treatment. These results can help providers and health plans better support patients with AD.
Implications for managed care pharmacy
The study provides real-world evidence on treatment switching and its economic impact among patients with moderate to severe AD. Although few patients switched therapies, those who did incurred significantly higher AD-related outpatient visits and total health care costs. These findings may inform formulary decision-making and support future efforts to better understand treatment patterns and their economic implications.
Atopic dermatitis (AD) is a chronic, relapsing inflammatory skin condition characterized by intense itch and recurrent eczematous lesions.1 It is the most common chronic inflammatory skin disease, with prevalence estimates ranging from 3.2% to 10.2% for adults in the United States.2 AD is strongly associated with other atopic conditions (eg, asthma and allergic rhinitis), significantly reducing quality of life.3
Many patients with AD can achieve adequate disease control with some combination of nonpharmacologic topical interventions (eg, moisturizers and emollients) and/or pharmacologic topical therapies, such as corticosteroids, calcineurin inhibitors, phosphodiesterase 4 inhibitors, and Janus kinase (JAK) inhibitors.4 However, for the 40% of AD patients with uncontrolled moderate to severe disease, treatment with phototherapy or systemic oral or parenteral treatments is recommended by the American Academy of Dermatology.4 Systemic treatments include nontargeted immunosuppressants (eg, methotrexate, cyclosporine, azathioprine, and mycophenolate mofetil) as well as targeted therapies, such as biologics and JAK inhibitors.
The introduction of systemic targeted therapies with their improved efficacy and safety profiles has transformed the treatment landscape for patients with moderate to severe AD. Since the US Food and Drug Administration (FDA) approval of dupilumab for adults with AD in 2017, 5 additional systemic targeted therapies have been approved for adults with moderate to severe AD. These include 2 JAK inhibitors, abrocitinib and upadacitinib (both approved January 2022), 2 IL-13 inhibitors, tralokinumab (approved December 2021) and lebrikizumab (approved September 2024), and 1 IL-31 inhibitor, nemolizumab (approved December 2024).
Although the expanded range of treatment options benefits patients given the heterogeneity of AD and variability in treatment response, guidance on preferred sequencing of systemic targeted therapies remains inconsistent. On one hand, the 2024 American Academy of Dermatology guidelines equally recommends dupilumab, tralokinumab, upadacitinib, and abrocitinib as first-line use for the treatment of moderate to severe AD through shared decision-making between patients and clinicians.4 On the other hand, the 2023 American Academy of Allergy, Asthma and Immunology/American College of Allergy, Asthma and Immunology Joint Task Force strongly recommends dupilumab and tralokinumab and only conditionally recommends the JAK inhibitors abrocitinib and baricitinib after trial of systemic treatments inclusive of a biologic because of safety concerns.5
Furthermore, although trials such as HEADS UP and LEVEL UP have assessed the efficacy and safety of switching between systemic targeted therapies, real-world data on switching patterns are limited.6,7 In particular, the frequency of switching and differences in health care resource utilization (HCRU) and costs between switchers and nonswitchers remain poorly characterized. Switching may reflect clinical factors (eg, inadequate response, adverse events, worsening disease) or nonclinical drivers (eg, formulary changes, cost) that may affect HCRU and costs by patients. Real-world claims data on HCRU and costs can inform clinical and payer decision-making by highlighting the burden of moderate to severe AD and guiding strategies to better support patients.
In this study, we evaluated the frequency of treatment switching from first- to second-line systemic targeted therapies and compared HCRU and costs between switchers and nonswitchers among commercially insured US patients with moderate to severe AD.
Methods
STUDY DESIGN AND DATA SOURCE
We conducted a real-world retrospective observational cohort study to assess switch rates, HCRU, and associated costs among patients with moderate to severe AD as indicated by being treated with a systemic targeted therapy. Data from Merative MarketScan Commercial Claims and Encounters (CCAE) databases were used to identify patients and capture HCRU and costs. The CCAE databases include employees and dependents covered by employer-sponsored private health insurance plans in the United States and captures claims across all settings of care and outpatient pharmacy. We collected all enrollment, inpatient, outpatient, and drug claim records within the study period from January 1, 2021 (the start of baseline period), to December 31, 2023 (the end of the follow-up period) (Figure 1).
FIGURE 1.
Study Design Schematic
aTwo claims for AD diagnosis were searched throughout the full study period.
bBaseline conditions included allergic rhinitis, asthma, chronic sinusitis, nasal polyps, food allergy, allergic conjunctivitis, atopic keratoconjunctivitis, allergic urticaria, and eosinophilic esophagitis.
cPrior therapies included topical therapies, immunosuppressants, systemic corticosteroids, and phototherapy.
AD = atopic dermatitis; HCRU = health care resource utilization.
STUDY POPULATION
Patients were included if they had at least 2 medical claims with an International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) diagnosis of AD at the primary diagnosis code position during the study period (Supplementary Table 1 (257.1KB, pdf) , available in online article). Additional inclusion criteria required initiation of a new systemic targeted therapy (index date) between January 1, 2022, and December 31, 2022, and continuous medical and pharmacy coverage during both the 12-month baseline and a minimum 12-month follow-up period. Patients were excluded if they were younger than 18 years on the index date, had prescription drug claims for a targeted systemic therapy during the baseline period, or received more than 2 different targeted systemic therapies during follow-up. In this study, first-line systemic targeted therapy was defined as the first prescription of any systemic targeted therapy (dupilumab, tralokinumab, abrocitinib, upadacitinib) and second-line systemic targeted therapy was defined as the second prescription of any systemic targeted therapy.
Within the overall population, 2 subgroups were created based on whether switching occurred over follow-up, which was defined as discontinuation of first systemic targeted therapy and initiation of second systemic targeted therapy. The study outcomes were assessed during the follow-up period, defined as the time from the index date to the end of the study period or the end of continuous enrollment, whichever occurred first.
STUDY MEASURES AND OUTCOMES
Demographic and clinical characteristics were assessed during the baseline period. Information regarding sex, age, insurance plan type, geographic regions, Charlson Comorbidity Index (CCI) scores, atopic comorbidities (identified through ICD-10-CM codes in Supplementary Table 1 (257.1KB, pdf) ), index therapy, and prior AD-related therapies were reported. Prior AD-related therapies included topical therapies, immunosuppressants, systemic corticosteroids, and phototherapy (Supplementary Table 2 (257.1KB, pdf) ).
Switching from first-line to second-line systemic targeted therapy was assessed by switch rate, defined as the proportion of patients who initiated a new systemic targeted therapy following the initiation of the index treatment, and time to switch, defined as the duration from the index treatment initiation date to the start date of a subsequent systemic targeted therapy among patients who switched within the follow-up period.
HCRU outcomes included the number of hospitalizations, emergency department (ED) visits, and outpatient services during the follow-up period, stratified by switch status (switchers vs nonswitchers). HCRU outcomes were assessed from the index date across both cohorts. Health care settings were defined and categorized by the place-of-service variable in Marketscan, with codes adapted from prior literature (Supplementary Table 3 (257.1KB, pdf) ).8–10 HCRU was further categorized as all-cause or AD-related, which required the presence of a primary diagnosis code for AD.
Health care costs were estimated based on the total amount paid from adjudicated claims, including insurer and health plan payments as well as patient cost-sharing (copayments, deductibles, and coinsurance). Costs were categorized into medical and drug components. Medical costs included expenditures related to inpatient, ED, and outpatient HCRU, whereas drug costs reflected spending on prescription medications. Both types of costs were also further classified as all-cause and AD-related, which also required a primary diagnosis code for AD. Total health care costs during the follow-up period were defined as the sum of medical and drug costs from the index date. Costs were adjusted to 2023 US dollars using the medical care component of the US Consumer Price Index.11
To account for varying lengths of follow-up, all HCRU and cost outcomes were annualized by standardizing to a 360-day year. Raw counts and costs were divided by each patient’s follow-up time (in days) and multiplied by 360 to obtain annualized rates.
STATISTICAL ANALYSIS
Baseline demographic and clinical characteristics, as well as treatment switch rates, were summarized descriptively. Statistical tests were conducted to compare HCRU and health care costs between switchers and nonswitchers. Proportion of patients with at least 1 hospitalization, ED visit, or outpatient service were independently compared using chi-square or Fisher exact tests. Mean number of HCRU events among those with 1 or more events and medical, drug, and total costs were compared using independent t-tests.
As a secondary analysis, adjusted logistic regression models were used to estimate the probability of any hospitalizations and ED visits. Adjusted negative binomial regression was used to estimate the mean number of outpatient service visits. Medical, pharmacy, and total costs were modeled using a generalized linear model with a gamma distribution and log link. Demographic variables (age, sex, insurance plan type, geographic region) were examined and found to be balanced across groups; therefore, adjusted models included only clinical characteristics (atopic comorbidities, CCI, prior AD-related therapies, index systemic targeted therapy) and baseline health care costs, which are most directly related to disease burden and likelihood of health care utilization.12,13 The natural logarithm of follow-up time was incorporated as an offset to account for differential observation periods. Categorical variables were dummy coded, with dupilumab as the reference for index systemic targeted therapy and “no” as the reference for prior AD therapy and atopic comorbidities. Continuous variables (CCI and baseline health care costs) were modeled as continuous without transformation.
Statistical significance was defined as a 2-sided P value of less than 0.05. Where applicable, 95% CIs were reported. All statistical analyses were performed using SAS version 9.4 (SAS Institute Inc.) and R version 4.3.2 (R Foundation for Statistical Computing).
Results
A total of 8,063 patients were included, with 466 (5.8%) identified as switchers and 7,597 (94.2%) as nonswitchers (Table 1) (Figure 2). The overall population consisted of primarily female (58.2%) patients living in the South (52.2%) with a mean age of 41.2 years. Patients had a mean CCI of 0.5 and had atopic comorbidities such as allergic rhinitis (24%) and asthma (18.8%). Many patients had prior claims 12 months before the index date for prescription topical therapies (45.4%) and systemic corticosteroids (28.5%), whereas few patients had prior claims for phototherapy (1.9%) and none had immunosuppressants. Nearly all patients initiated their first systemic targeted therapy with dupilumab (99.4%). Baseline demographic characteristics were similar between switchers and nonswitchers. Use of prior AD-related therapies was observed more frequently among switchers than among nonswitchers. Compared with nonswitchers, switchers were more frequently augmented with both prescription oral corticosteroids (27.7% vs 15.8%) and topical corticosteroids (41.6% vs 25.2%) after initiation of index therapy.
TABLE 1.
Baseline Characteristics
| Switchers (n = 466) |
Nonswitchers (n = 7,597) |
Overall (N = 8,063) |
|
|---|---|---|---|
| Age, years | |||
| Mean (SD) | 40.9 (14.3) | 41.3 (14.2) | 41.2 (14.2) |
| Sex, n (%) | |||
| Male | 201 (43.1) | 3,169 (41.7) | 3,370 (41.8) |
| Female | 265 (56.9) | 4,428 (58.3) | 4,693 (58.2) |
| Insurance plan type, n (%) | |||
| Comprehensive | 18 (3.9) | 175 (2.3) | 193 (2.4) |
| EPO or PPO | 206 (44.2) | 3,658 (48.2) | 3,864 (47.9) |
| HMO | 56 (12.0) | 962 (12.7) | 1,018 (12.6) |
| POS | 35 (7.5) | 700 (9.2) | 735 (9.1) |
| CDHP or HDHP | 147 (31.5) | 1,976 (26.0) | 2,123 (26.3) |
| Unknown | 4 (0.9) | 126 (1.7) | 130 (1.6) |
| Geographic region, n (%) | |||
| Northeast | 64 (13.7) | 1,217 (16.0) | 1,281 (15.9) |
| North Central | 86 (18.5) | 1,252 (16.5) | 1,338 (16.6) |
| South | 253 (54.3) | 3,958 (52.1) | 4,211 (52.2) |
| West | 62 (13.3) | 1,138 (15.0) | 1,200 (14.9) |
| Unknown | 1 (0.2) | 32 (0.4) | 33 (0.4) |
| CCI, mean (SD) | 0.5 (0.9) | 0.5 (1.0) | 0.5 (1.0) |
| Atopic comorbidities, n (%) | |||
| Allergic rhinitis | 99 (21.2) | 1,837 (24.2) | 1,936 (24.0) |
| Asthma | 65 (13.9) | 1,447 (19.0) | 1,512 (18.8) |
| Chronic sinusitis | 17 (3.6) | 306 (4.0) | 323 (4.0) |
| Nasal polyps | 19 (4.1) | 285 (3.8) | 304 (3.8) |
| Food allergy | 16 (3.4) | 232 (3.1) | 248 (3.1) |
| Allergic conjunctivitis | 14 (3.0) | 198 (2.6) | 212 (2.6) |
| Atopic keratoconjunctivitis | 7 (1.5) | 97 (1.3) | 104 (1.3) |
| Allergic urticaria | 7 (1.5) | 71 (0.9) | 78 (1.0) |
| Eosinophilic esophagitis | 0 (0) | 51 (0.7) | 51 (0.6) |
| Indexed 1L therapy, n (%) | |||
| Dupilumab | 460 (98.7) | 7,552 (99.4) | 8,012 (99.4) |
| Tralokinumab | 0 | 0 | 0 |
| Abrocitinib | 3 (0.6) | 10 (0.1) | 13 (0.2) |
| Upadacitinib | 3 (0.6) | 35 (0.5) | 38 (0.5) |
| Prior AD-related therapies, n (%) | |||
| Topical therapiesa | 258 (55.4) | 3,405 (44.8) | 3,663 (45.4) |
| Immunosuppressantsb | 0 | 0 | 0 |
| Systemic corticosteroids | 167 (35.8) | 2,134 (28.1) | 2,301 (28.5) |
| Phototherapy | 15 (3.2) | 140 (1.8) | 155 (1.9) |
| Baseline total cost ($USD), mean (SD) | 31,379 (46,465) | 29,483 (31,546) | 29,593 (32,593) |
Topical corticosteroids, calcineurin inhibitors, PDE-4 inhibitors, JAK inhibitor.
Methotrexate, azathioprine, cyclosporine, mycophenolate mofetil.
1L = first line; AD = atopic dermatitis; CCI = Charlson Comorbidity Index;
CDHP = consumer-driven health plan; EPO = exclusive provider organization; HDHP = high-deductible health plan; HMO = health maintenance organization; JAK = Janus kinase; POS = point-of-service plan; PPO = preferred provider organization; USD = US dollars.
FIGURE 2.
Patient Identification Flowchart
ICD-10-CM = International Classification of Diseases, Tenth Revision, Clinical Modification.
SWITCH RATES
Among the 466 switchers, the majority received dupilumab (n = 460) as first-line therapy, whereas only a small number initiated abrocitinib (n = 3) or upadacitinib (n = 3); no patients initiated tralokinumab as first-line therapy (Supplementary Table 4 (257.1KB, pdf) ). Total switch rate was determined to be 5.8% out of the overall population. The most common second-line therapy among dupilumab initiators was upadacitinib (56.3%), followed by tralokinumab (35.2%) and abrocitinib (8.5%). The overall mean time to switch from first-line to second-line therapy ranged from 186.3 days (first line: upadacitinib) to 395.7 days (first line: abrocitinib).
HCRU
Median follow-up duration was 381 and 379 days for switchers and nonswitchers, respectively. Patients experiencing an all-cause hospitalization were similar between the groups, with 5.4% of switchers and 5.2% of nonswitchers experiencing at least 1 hospitalization (P = 0.83) (Table 2). ED visits were significantly higher among switchers, with 31.8% having at least 1 ED visit vs 22.3% of nonswitchers (P < 0.01), although the annualized rate of ED visits among those with at least 1 visit did not differ significantly. Although nearly all patients had at least 1 outpatient service use in both groups, switchers had a higher annualized rate of outpatient visits compared with nonswitchers (26.9 vs 22.0; P < 0.01). AD-related hospitalizations and ED visits were rare across both groups. Nearly all switchers (96.4%) had at least 1 AD-related outpatient service compared with 82.8% of nonswitchers (P < 0.01), and the annualized rate of visits was higher among switchers compared with nonswitchers (4.9 vs 3.1, P < 0.01). Results remained consistent after adjusting for baseline covariates. There were no significant differences in the adjusted odds of experiencing a hospitalization (all-cause or AD-related) between switchers and nonswitchers (Supplementary Table 5 (257.1KB, pdf) ). Switchers had higher adjusted odds of an all-cause ED visit in a year (odds ratio = 1.7; 95% CI = 1.3 - 2.0); however, no difference was observed for AD-related ED visits, likely because of small event counts. Switchers had an estimated increase of 9 all-cause and 3 AD-related outpatient service visits per year compared with nonswitchers.
TABLE 2.
Annualized All-Cause and AD-Related HCRU Among Switchers vs Nonswitchers Incurred During the Follow-Up Period
| Switchers (n = 466) | Nonswitchers (n = 7,597) | P value | |
|---|---|---|---|
| Follow-up duration in days, median (IQR) | 381 (373,388) | 379 (371,387) | — |
| All-cause HCRU | |||
| Hospitalizations | |||
| Total number of patients with ≥1 hospitalizations, n (%) | 25 (5.4) | 395 (5.2) | 0.83 |
| Annualized rate of hospitalizationsa, mean (SD) | 2.0 (2.8) | 1.3 (1.0) | 0.45 |
| ED visits | |||
| Total number of patients with ≥1 ED visit, n (%) | 148 (31.8) | 1,696 (22.3) | <0.01 |
| Annualized rate of ED visitsa, mean (SD) | 1.7 (1.4) | 1.8 (2.5) | 0.45 |
| Outpatient services | |||
| Total number of patients with ≥1 outpatient service, n (%) | 465 (99.8) | 7,538 (99.2) | 0.26 |
| Annualized rate of outpatient servicesa, mean (SD) | 26.9 (23.5) | 22.0 (22.5) | <0.01 |
| AD-related HCRU | |||
| Hospitalizations | |||
| Total number of patients with ≥1 hospitalizations, n (%) | 1 (0.2) | 1 (0) | 0.11 |
| Annualized rate of hospitalizationsa, mean (SD) | 1 (0) | 1 (0) | — |
| ED visits | |||
| Total number of patients with ≥1 hospitalizations, n (%) | 4 (0.9) | 4 (0.1) | <0.01 |
| Annualized rate of hospitalizationsa, mean (SD) | 1 (0) | 1 (0.2) | — |
| Outpatient services | |||
| Total number of patients with ≥1 outpatient services, n (%) | 449 (96.4) | 6,293 (82.8) | <0.01 |
| Annualized rate of outpatient servicesa, mean (SD) | 4.9 (5.0) | 3.1 (5.5) | <0.01 |
Unadjusted results tested using chi-square and Fisher exact tests.
Among patients with at least 1 event, rates were standardized to an annualized 360-day period.
AD = atopic dermatitis; ED = emergency department; HCRU = health care resource utilization; IQR = interquartile range.
Health Care Costs
Over a standardized 1-year follow-up period, switchers incurred an $11,408 higher mean total all-cause health care cost compared with nonswitchers ($78,876 vs $67,468; P < 0.01) (Table 3). Similarly, mean total AD-related health care costs were also significantly higher among switchers compared with nonswitchers ($59,876 vs $51,327; P < 0.01). This difference was primarily driven by higher AD-related drug costs among switchers, who incurred an average of $59,246 (95% CI = $56,865-$61,626) compared with $51,027 (95% CI = $50,471-$51,584) for nonswitchers (P < 0.01). AD-related medical costs were also higher among switchers, with mean costs of $630 (95% CI = $561-$700) vs $299 (95% CI = $274-$324) in nonswitchers (P < 0.01). Differences in all-cause and AD-related costs between switchers and nonswitchers remained consistent with unadjusted results after adjusting for baseline covariates (Supplementary Table 6 (257.1KB, pdf) ).
TABLE 3.
Annualized All-Cause and AD-Related Costs Among Switchers vs Nonswitchers Incurred During Follow-Up Period
| Switchers (n = 466) | Nonswitchers (n = 7,597) | Difference | |
|---|---|---|---|
| All-cause costs | |||
| Medical costs, mean (95% CI) | $13,983 ($10,184-$19,426) | $12,497 ($11,939-$13,796) | $ 1,486 ($-2,956-$5,929) P = 0.51 |
| Drug costs, mean (95% CI) | $64,892 ($62,188-$67,597) | $54,971 ($54,318-$55,625) | $9,921 ($7,139-$12,703) P < 0.01 |
| Total health care costs, mean (95% CI) | $78,876 ($73,822-$83,929) | $67,468 ($66,283-$68,654) | $11,408 ($6,217-$16,597) P < 0.01 |
| AD-related costs | |||
| Medical costs, mean (95% CI) | $630 ($561-$700) | $299 ($274-$324) | $331 ($257-$405) P < 0.01 |
| Drug costs, mean (95% CI) | $59,246 ($56,865-$61,626) | $51,027 ($50,471-$51,584) | $8,219 ($5,774-$10,662) P < 0.01 |
| Total health care costs, mean (95% CI) | $59,876 ($57,495-$62,257) | $51,327 ($50,769-$51,885) | $8,549 ($6,104-$10,995) P < 0.01 |
Unadjusted results tested using independent 2-sided t-tests.
AD = atopic dermatitis.
Discussion
In this study of commercially insured patients with moderate to severe AD, we found that 5.8% of patients switched from first- to second-line systemic targeted therapy after a median follow-up of approximately 1 year, suggesting that first-line treatments may offer effective and well-tolerated disease control for most patients in the real-world setting. Almost all (99.4%) patients initiated their first-line systemic targeted therapy with dupilumab, which may be attributed to its earlier approval and limited uptake of more recently introduced systemic targeted therapies. Compared with nonswitchers, patients who switched systemic targeted therapies incurred significantly higher AD-related outpatient service use and total health care costs. This may be expected as switching may reflect either worsening disease severity, inadequate response or intolerability to first-line therapy. Notably, drug costs accounted for approximately 99% of AD-related health care expenditures in both groups.
Our observed switch rate is consistent with a prior study using IQVIA’s claims database from a similar time period, in which a switch rate of 5.1% was reported among 7,006 adults with AD initiating a first-line systemic targeted therapy.14 To our knowledge, however, this is the first study comparing HCRU and costs between switchers and nonswitchers following the approval of systemic targeted therapies beyond dupilumab. Previous research has established the substantial economic burden of AD in the US adult population. For instance, Shrestha et al reported significantly higher HCRU and per-patient total costs among commercially insured adults with AD compared with matched controls ($10,461 vs $7,187),15 whereas Drucker et al similarly estimated an adjusted annual incremental cost of $3,302 associated with AD.16 Prior to the introduction of newer agents, patients commonly augmented dupilumab with systemic or topical corticosteroids, highlighting the difficulty of managing AD with the treatment options at the time.17
Our study offers important context to inform managed care strategies for patients initiating systemic targeted therapies in AD. While the $11,408 mean annualized total health care cost difference between switchers and nonswitchers is notable, whether this magnitude justifies changes to utilization management criteria will likely depend on individual plan priorities and budget constraints. Rather, these findings underscore the potential value of complementary care strategies (eg, proactive monitoring, patient education, adherence support) to help mitigate the higher resource use and costs observed among switchers. Moreover, these findings may help decision makers anticipate budget impact and resource needs when managing these patients.
The recent expansion of FDA-approved systemic targeted therapies for moderate to severe AD has notably improved clinical management options. Our findings highlight that patients who switch therapies tend to use more health care resources and incur higher costs with a median follow-up of approximately 1 year. With multiple targeted therapies now available, it is increasingly important to align initial treatment decisions with patient-specific clinical, economic, and contextual factors to reduce downstream health care burden.
LIMITATIONS
This study has several limitations. First, claims data do not capture the clinical reasons for treatment switching, and they do not include information on disease severity or response to therapy. We assumed systemic targeted therapies were prescribed on-label for patients with AD of moderate to severe severity. The number of patients receiving newer agents, such as tralokinumab, abrocitinib, and upadacitinib, was limited because of the timing of FDA approvals, and recently approved therapies, such as lebrikizumab and nemolizumab, are not captured within the current dataset. Furthermore, our analysis was restricted to first- and second-line systemic targeted therapies as well as a short and variable follow-up period; future studies with longer observation windows are needed to evaluate later-line treatment patterns and their associated longer-term HCRU and costs. Total health care costs may be underestimated, as over-the-counter treatments and indirect costs are not included. On the other hand, AD-specific health care costs may be overestimated, as we attributed all costs from encounters listing AD as the primary diagnosis, which may not fully account for the influence of comorbid conditions that also contribute to health care utilization. It is important to note that cost-effectiveness of these therapies was not evaluated in this study; therefore, higher spending observed among switchers may not necessarily reflect poorer value, as increased costs may be associated with better outcomes. Lastly, commercial patients included in the CCAE data may not be representative of all US commercial patients, as the database underrepresents smaller employers and excludes those with state-funded insurance. As with all retrospective studies using administrative claims data, results may be influenced by coding errors, misclassification, and variations in billing practices.
Conclusions
This study provides real-world insights into treatment patterns and economic burden among commercially insured patients with moderate to severe AD who initiated a systemic targeted therapy. We found that a small proportion of patients switch systemic targeted therapies, and those who switch experience higher health care resource use and costs. These findings underscore the increased importance of personalized considerations for the selection of first-line systemic targeted therapy for patients with moderate to severe AD to reduce downstream economic burden. As additional therapies become available, future research exploring reasons for treatment switching and patient factors influencing response will be critical to guide clinical and formulary decision-making in this evolving treatment landscape.
Disclosures
Dr Li was supported by a Sanofi-sponsored training fellowship with the University of Washington.
Acknowledgments
The authors would like to acknowledge Ronald Preblick and Cori Gray for their valuable contributions to the study design and thoughtful review and feedback on the manuscript.
Data Availability
The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.