Abstract
BACKGROUND:
The biosimilar market is growing rapidly, as evidenced by 41 approvals and 37 launches to date. As adalimumab biosimilars launch in the United States, competition among biosimilar and reference adalimumab will likely increase across multiple reference indications, including rheumatology, dermatology, and gastrointestinal diseases, which may lead to decreased payer costs.
OBJECTIVE:
To evaluate the costs of adding biosimilar adalimumab to a US commercial plan by exploring various utilization and price differential scenarios.
METHODS:
A 3-year budget impact model for a US commercial plan of 1 million people was developed to assess switching from reference adalimumab or any self-injectable reference tumor necrosis factor (TNF) inhibitor to biosimilar adalimumab. Pharmacy and medical costs were analyzed through high- and low-conversion scenarios from reference adalimumab and the TNF inhibitor class. Price reductions of 5% to 60% relative to reference adalimumab based on previous biosimilar launches were also explored. Short-term medical costs were evaluated as additional simple and complex office visits, with scenarios of half of switch patients having 1 visit up to all switch patients having 10 visits.
RESULTS:
In a target population of 1,863 patients, switching from reference adalimumab to biosimilar adalimumab had cumulative cost savings of $5,756,073 with slow conversion (10%-20% over 3 years) and $28,780,365 with fast conversion (50%-100% over 3 years). Similar results were seen when switching from any other self-injectable reference TNF inhibitor. Cost savings more than $1 million were seen with a 10% conversion from reference adalimumab and a 15% price reduction from reference adalimumab. Additional office visit scenarios had a negligible impact on budget, with no changes in per-member-per-month costs until all switch patients had 10 additional complex visits, in which per-member-per-month costs increased by $0.02.
CONCLUSIONS:
In a hypothetical plan of 1 million lives, use of biosimilar adalimumab in commercial plans can lead to significant cost savings for payers because of increased competition. Greater and faster biosimilar conversion rates from reference adalimumab and other reference TNF inhibitors resulted in decreased costs. Additionally, even with short-term medical expenditures, cost savings were still realized when switching to biosimilar adalimumab.
Plain language summary
Biologics are a type of drug. The first approved biologic is called a “reference product.” Biosimilars are highly similar to the reference product. They have the same treatment risks and benefits. Adalimumab is a biologic used for skin/joint and stomach diseases. We looked at the cost of biosimilars in place of the reference product. In our study, biosimilars saved money for health care plans.
Implications for managed care pharmacy
Results from this 3-year budget impact model that evaluated switching to biosimilar adalimumab demonstrated cost savings across multiple scenarios, including varying conversion rates from reference adalimumab and other reference self-injectable tumor necrosis factor inhibitors, price reduction relative to reference adalimumab, and short-term medical expenditures. The findings of this study in modeling out biosimilar competition with reference adalimumab and other reference tumor necrosis factor inhibitors can potentially aid payers with formulary management decisions to lower overall costs.
The biological market is growing quickly in the United States, as evidenced by the 14.6% compound annual growth rate (CAGR) vs 6.1% CAGR for all US medications over the past 5 years.1 Immunology, oncology, and antidiabetic products account for two-thirds of total biologic spending. Similarly, the development and approval of biosimilars has also been increasing, particularly in the immunology space. As of July 18, 2023, there have been 41 approvals and 37 launches in the US biosimilar market, including 14 tumor necrosis factor (TNF) inhibitors2 that have been approved or launched. Biosimilars are estimated to have saved more than $100 billion across 5 years for payers, and ultimately patients, through increased competition, resulting in lower prices for reference biologics and biosimilars.1,3 As biosimilars have launched, the prices of biosimilars and reference products have decreased at a CAGR of −5% to −20%.3
In the immunology market, the TNF inhibitor adalimumab is of particular interest as it was the highest-expenditure medication worldwide in 2021 and has been prescribed to more than 1 million patients globally.4,5 As of July 2023, 8 adalimumab biosimilars have been launched in the United States and 10 adalimumab biosimilars have launched in the European Union.2,6,7 Since the launch of the first biosimilar adalimumab products in early 2019 in the European Union, reference adalimumab’s market share has decreased to 34%, highlighting the impact of the biosimilar launches.3 Biosimilar adalimumab products have the potential to lower costs and increase patient access to efficacious treatments, which is particularly important in this large patient population.3
There has been some concern that switching from a reference product to a biosimilar may increase health care resource utilization, as patients may need additional information on biosimilars before switching or need additional follow-up after switching. A survey of 500 patients with immunological conditions in the United States indicated that patients would be willing to switch (43%) or start (49%) a biosimilar and that the majority wanted education on general information surrounding biosimilars (71%), potential beneficial effects of biosimilars (55%), the connection between biologics and biosimilars (53%), and biosimilar cost (48%).8 A systematic literature review published in 2022 assessed the economic impact of nonmedical switching from reference products to biosimilar products and included 19 studies in rheumatology and 21 studies in gastroenterology. Several of the included studies found that nonmedical switching led to increased health care resource utilization and costs after switching to a biosimilar and that the increase in health care resource utilization may offset the cost savings realized with switching to biosimilars.9
The purpose of this budget impact model is to understand the potential financial impact of biosimilar adalimumab across various utilization and price differential scenarios.
Methods
MODEL OVERVIEW
A 3-year budget impact model was developed in accordance to Budget Impact Analysis Good Practice Guidance from the Professional Society for Health Economics and Outcomes Research10 in Microsoft Excel for a hypothetical US commercial plan of 1 million people to evaluate costs associated with various uptake scenarios of biosimilar adalimumab in patients with rheumatoid arthritis (RA), juvenile idiopathic arthritis (JIA), ankylosing spondylitis (AS), psoriatic arthritis (PsA), plaque psoriasis (PsO), Crohn’s disease (CD), and ulcerative colitis (UC) currently receiving a self-injectable reference TNF inhibitor (Supplementary Figure 1 (347.5KB, pdf) , available in online article). The budget impact model evaluated the costs associated with switching to biosimilar adalimumab in a health plan formulary for patients currently receiving reference adalimumab or a self-injectable reference TNF inhibitor through commercial insurance. As the overall budget impact to a payer will depend on specific market dynamics, such as biosimilar pricing (in comparison to the reference product) and uptake, several conversion scenarios were explored. Because of concerns that patients switching from a reference product to a biosimilar may result in increased health care resource utilization, we included an additional analysis of potential short-term medical expenditures related to switching to a biosimilar to determine if there was any additional impact on the overall budget. A scenario with inclusion of biosimilar adalimumab (new market) vs without biosimilar adalimumab (current market) was used to estimate incremental costs. Pharmacy costs were included in base case analyses for all patients treated with a self-injectable TNF inhibitor, and medical costs for office visits were added in scenario analyses. Biosimilar adalimumab was assumed to take utilization from comparators in the new market, which included reference adalimumab, and the other self-injectable reference TNF inhibitors (etanercept, certolizumab pegol, and golimumab) that are reimbursed through pharmacy benefits. Infliximab was not included because it is not self-injected and is mainly reimbursed under the medical benefit.
Assumptions made for the model and the multiple scenarios are detailed below. Based on the Institute for Clinical and Economic Review evidence reports and published literature, efficacy and safety of reference adalimumab, etanercept, certolizumab pegol, and golimumab were assumed to be equivalent.11-13 Because of data availability, all patients initiating treatment were assumed to receive continuous treatment without switching or gaps in therapy. Additional costs of starting doses were assumed to be minor and were not included. Lastly, the utilization rates calculated for each included indication were based on multiple references describing the proportion of real-world patients treated with each self-injectable TNF inhibitor and may not reflect individual payer utilization rates. Some of the references may not reflect the current utilization rates if the publications used were not current; however, these rates are based on our best interpretation of the available literature. We assumed in these real-world studies that patients were appropriately treated to their disease severity (ie, moderate or severe) and standard clinical practice (ie, clinical practice guidelines) when prescribed their respective TNF inhibitors in the real world.
MODEL INPUTS
For each indication, prevalent and incident cases were derived from epidemiology inputs and utilization patterns available in the literature (Table 1). Indications included in the model were RA, JIA, AS, PsA, PsO, CD, and UC. Not all TNF inhibitors are indicated for each disease state and not all indications for each TNF inhibitor were included in the model; for example, reference adalimumab is indicated for UC in patients aged 5 years and older, uveitis, and hidradenitis suppurativa but were not modeled, as adalimumab biosimilars were not yet indicated for such at the time of model development.14 Calculations were based on age category (2-17 years, 6-17 years, ≥18 years), the proportion of patients treated with a biologic, and the proportion of patients receiving reference adalimumab, etanercept, certolizumab pegol, or golimumab.
TABLE 1.
Model Inputs
| Input | Value | Notes | Reference | |
|---|---|---|---|---|
| Total plan population | 1,000,000 | Assumption | ||
| Annual population growth | 0.25% | US Census 202224 (health insurance coverage status) | ||
| Age distribution 6-17 years: 17.5% ≥18 years: 61.3% |
2-17 years: 19.9% | US Census 202225 | ||
| Target population | ||||
| Rheumatoid arthritis (age ≥18 years) | Age-standardized rate. Model assumes rate is the same for patients aged ≥18 years | |||
| Prevalence | 0.38% | Safiri 201926 | ||
| Incidence | 0.02% | Safiri 201926 | ||
| % treated with biologic | 41.1 | Gu 201527 | ||
| % treated with reference adalimumab | 30.4 | Curtis 201428 | ||
| % treated with etanercept | 41.5 | Curtis 201428 | ||
| % treated with certolizumab pegol | 2.5 | Assumes similar proportion drug use across different indications | Curtis 201428; Walsh 201829 | |
| % treated with golimumab | 1.4 | Curtis 201428 | ||
| Juvenile idiopathic arthritis (age 2-17 years) | ||||
| Prevalence | 0.05% | Harrold 201330 | ||
| Incidence | 0.01% | Harrold 201330 | ||
| % treated with biologic | 13.0 | Zamora-Legoff 201631 | ||
| % treated with reference adalimumab | 30.4 | Assumes market share of adalimumab among biologics for JIA is the same as for RA | Curtis 201428 | |
| % treated with etanercept | 41.5 | Assumes market share of etanercept among biologics for JIA is the same as for RA | Curtis 201428 | |
| % treated with certolizumab pegol | Not indicated | Not indicated | ||
| % treated with golimumab | Not indicated | Not indicated | ||
| AS (age ≥18 years) | Some published rates are for patients aged ≥18 years. Model assumes rate is the same for patients aged ≥18 years | |||
| Prevalence | 0.09% | Walsh 201932 | ||
| Incidence | 0.003% | Wright 201533 | ||
| % treated with biologic | 39.3 | Walsh 201932 | ||
| % treated with reference adalimumab | 25.0 | Grand View Research 202034 | ||
| % treated with etanercept | 41.5 | Assumes market share of adalimumab among biologics for AS is the same as for RA | Curtis 201428 | |
| % treated with certolizumab pegol | 2.5 | Curtis 201428; Walsh 201932 | ||
| % treated with golimumab | 1.4 | Curtis 201428 | ||
| Psoriatic arthritis (age ≥18 years) | Some published rates are for patients aged ≥18 years. Model assumes rate is the same for patients aged ≥18 years | |||
| Prevalence | 0.14% | Scotti 201835 | ||
| Incidence | 0.007% | Scotti 201835 | ||
| % treated with biologic | 21.7 | Gottlieb 201936 | ||
| % treated with reference adalimumab | 56.6 | Oelke 201937 | ||
| % treated with etanercept | 30.9 | Oelke 201937 | ||
| % treated with certolizumab pegol | 4.6 | Oelke 201937 | ||
| % treated with golimumab | 3.3 | Oelke 201937 | ||
| Plaque psoriasis (age ≥18 years) | Rates across all ages. Model assumes rate is the same for patients aged ≥18 years | |||
| Prevalence | 1.06% | Parisi 201338 | ||
| Incidence | 0.08% | AlQassimi 202039 | ||
| % treated with biologic | 6.0 | Murage 201940 | ||
| % treated with reference adalimumab | 43.0 | Noe 201941 | ||
| % treated with etanercept | 30.5 | Noe 201941 | ||
| % treated with certolizumab pegol | 0.6 | Assumption, median based on the lowest reported value (1.2%) | Noe 201941 | |
| % treated with golimumab | Not indicated | Not indicated | ||
| Crohn’s disease (age ≥6 years) | Median age of diagnosis was 29.5 years (range: 4-93 years). Model assumes rate is the same for patients aged 2-17 years and ≥18 years | |||
| Prevalence | 0.22% | Ye 201842 | ||
| Incidence | 0.01% | Shivashankar 201743 | ||
| % treated with biologic | 31.1 | Yu 201844 | ||
| % treated with reference adalimumab | 54.0 | Brady 201845 | ||
| % treated with etanercept | Not indicated | Not indicated | ||
| % treated with certolizumab pegol | 10.0 | Age ≥16 years | Brady 201845 | |
| % treated with golimumab | Not indicated | Not indicated | ||
| Ulcerative colitis (age ≥18 years) | Median age of diagnosis was 34.9 years (range: 1-91 years). Model assumes rate is the same for patients aged ≥18 years | |||
| Prevalence | 0.29% | Shivashankar 201743 | ||
| Incidence | 0.01% | Shivashankar 201743 | ||
| % treated with biologic | 11.6 | Yu 201844 | ||
| % treated with reference adalimumab | 47.0 | Brady 201845 | ||
| % treated with etanercept | Not indicated | Not indicated | ||
| % treated with certolizumab pegol | Not indicated | Not indicated | ||
| % treated with golimumab | 4.6 | Brady 201845 | ||
| Comparator | WAC per unit | Patient cost share | Net cost per unit | Reference |
| Biosimilar adalimumab 2s (40 mg/0.8 mL) | $2,724.18a | $35.00 | $2,689 | Merative Micromedex RED BOOK 202214; Kaiser Family Foundation 202046 |
| Reference adalimumab 2s (40 mg/0.4 mL) | $3,204.92 | $60.00 | $3,145 | |
| Etanercept 1s (50 mg/1 mL) | $1,602.45 | $35.00 | $1,567 | |
| Certolizumab pegol 1s (200 mg/1 mL) | $5,099.68 | $115.00 | $4,985 | |
| Golimumab 1s (50 mg/0.5 mL) | $5,572.12 | $115.00 | $5,457 | |
| Medical costsb | CPT/HCPCS code | Unit cost per visit | Reference | |
| Simple office visit (education visit, no imaging or laboratory test conducted) | 99211 | $23.46 | CMS Physician Fee Schedule 202217 | |
| Complex office visit (additional physical therapy visit, moderate complexity, typically 30 minutes) | 99213 | $76.15 | ||
a Does not represent actual WAC for biosimilar adalimumab. WAC was assumed to be 15% off reference adalimumab WAC.
b For the base case, it was assumed that no medical office visits were needed. Office visits were included in a scenario analysis.
AS = ankylosing spondylitis; CMS = Centers for Medicare & Medicaid Services; CPT = Current Procedural Terminology; HCPCS = Healthcare Common Procedure Coding System; JIA = juvenile idiopathic arthritis; RA = rheumatoid arthritis; s = syringe; WAC = wholesale acquisition cost.
Pharmacy costs were included in the base case model, and medical costs for office visits were added in scenario analyses (Table 1). Pharmacy costs were based on wholesale acquisition costs (WACs) from the Merative Micromedex RED BOOK.15 As pricing strategies are expected to differ according to specific biosimilar manufacturers, we explored a range of biosimilar price reductions relative to reference adalimumab pricing (ie, 15%-40% decrease), reflective of previous US biosimilar launch experiences.16 Patient costs were accounted for through a tiered copay and coinsurance using 2020 reports from the Kaiser Family Foundation.17 Drug administration costs were not included as they were assumed to be the same across comparators. Medical costs were based on publicly available physician and laboratory fee schedules; no medical costs were included in the base case but were explored in a hypothetical scenario when switching from reference adalimumab to biosimilar adalimuab.17,18 The costs in the model reflected 2022 US dollars (USD) and were not discounted per the Professional Society for Health Economics and Outcomes Research guidelines.10 Results for each scenario are presented as costs per year, cumulative costs over 3 years, and per-member-per-month (PMPM) costs.
SCENARIOS FOR BIOSIMILAR ADALIMUMAB
To account for multiple market complexities of varying uptake, pricing reductions between the biosimilar and reference, and medical expenditures, the impact of 3 scenarios related to switching to biosimilar adalimumab were explored. The first scenario evaluated the budget impact of various conversion rates to biosimilar adalimumab from reference adalimumab alone and from the TNF inhibitor class. The second scenario evaluated the budget impact of switching from reference adalimumab to biosimilar adalimumab across different price reductions and conversion rates. Class shifts from the reference TNF inhibitor class to biosimilar adalimumab across different price reductions were also evaluated. Finally, we modeled the hypothetical total budgetary impact if switching to biosimilar adalimumab resulted in increased health care resource utilization.
Conversion From Reference Adalimumab and Other Reference TNF Inhibitors. The first scenario examined conversion from reference adalimumab and other reference TNF inhibitors to biosimilar adalimumab, in which the utilization rate represented the percentage of treated health plan patients receiving each treatment in the current market (without biosimilar adalimumab) and in the new market (with biosimilar adalimumab). Utilization rates for the current and new markets were based on the prevalence and incidence rates for each indication. To reflect the array of biosimilar utilization across indications and products, the conversion rate of biosimilar adalimumab from reference adalimumab was explored, starting with 10% conversion in year 1, 15% in year 2, 20% in year 3, and incrementally up to 50%, 75%, and 100% in years 1 through 3, respectively (Supplementary Table 2 (347.5KB, pdf) ). This allowed for analysis of faster and slower conversion to biosimilar adalimumab. Utilization rates of all other self-injectable TNF inhibitors were assumed to remain the same in these scenarios.
In addition, a class shift across the reference TNF inhibitor class was also explored. The same incremental conversion scenarios were evaluated in which biosimilar adalimumab was assumed to take a weighted portion of the utilization rate from each reference TNF inhibitor. For example, in the 10% class shift in year 1, 5.7% was taken from reference adalimumab, 3.8% from etanercept, and the remaining 0.5% from certolizumab pegol and golimumab (Supplementary Table 2 (347.5KB, pdf) ).
A 1-way sensitivity analysis was used to assess the robustness of the results and evaluate top parameters influencing the model. The model parameters were varied over a range of ±20% of the slowest conversion rate of reference adalimumab to biosimilar adalimumab (ie, 10% conversion in year 1).
WAC Price Reductions and Utilization Shift From Reference Adalimumab. The second scenario examined WAC price reductions relative to reference adalimumab. Historically, biosimilar WACs have cost 15% to 37% less than their reference products in the United States.16 To understand the impact of WAC price reductions on reference adalimumab, a scenario exploring a relative price reduction of 5% to 60% for biosimilar adalimumab WAC price was explored. Additionally, the conversion rate of biosimilar adalimumab from reference adalimumab and the reference TNF inhibitor class was varied from 5% to 100% in year 1 to further assess the dual impact of the conversion to and potential cost of biosimilar adalimumab.
Medical Expenditure Differentials With Varying Number of Visits From Reference Adalimumab. To understand the impact of hypothetical medical expenditures when switching from reference adalimumab to biosimilar adalimumab, the number of simple office visits and complex office visits were assessed over 1 year. A simple office visit was assumed to be an education visit with the nurse or physician to learn about the biosimilar. Complex office visits were assumed to include imaging and laboratory costs. For the base case (and for the above scenarios), it was assumed that no additional office visits were necessary when patients switched to biosimilar adalimumab. Multiple scenarios for both simple and complex office visits were explored starting with half of switch patients (reference adalimumab to biosimilar adalimumab) who had 1 office visit to all switch patients having 1 visit, 5 visits, and up to 10 visits.
Results
Based on a commercial plan of 1 million people, the total target population was 1,863 in year 1; 1,943 in year 2; and 2,022 in year 3 (Supplementary Table 1 (347.5KB, pdf) ). To understand the effects of fast and slow conversion to biosimilar adalimumab and WAC pricing reductions, results in text are presented for the low and high scenarios.
CONVERSION FROM REFERENCE ADALIMUMAB AND OTHER REFERENCE TNF INHIBITORS
The budget impact of slow to fast conversion to biosimilar adalimumab from reference adalimumab resulted in cost savings each year and cumulatively over 3 years (Table 2). In the slow conversion scenario (10% in year 1, 15% in year 2, and 20% in year 3), savings increased each year, resulting in a total of $5,756,073 over 3 years. The savings PMPM were $0.10 in year 1, $0.16 in year 2, and $0.22 in year 3. Similar results were observed in the fast conversion scenario (50% in year 1, 75% in year 2, 100% in year 3), with total cumulative savings of $28,780,365. Costs savings PMPM increased over time with $0.51 in year 1, $0.79 in year 2, and $1.09 in year 3.
TABLE 2.
Cost Savings With Conversion From Reference Adalimumab or Self-Injectable TNF Inhibitor to Biosimilar Adalimumab
| Slow | Conversion | Fast | ||||
|---|---|---|---|---|---|---|
| Reference adalimumab to biosimilar adalimumab | Year 1 cost savings | 10% | 20% | 30% | 40% | 50% |
| $1,230,903 | $2,461,805 | $3,692,708 | $4,923,610 | $6,154,513 | ||
| Year 2 cost savings | 15% | 30% | 45% | 60% | 75% | |
| $1,905,539 | $3,811,078 | $5,716,616 | $7,622,155 | $9,527,694 | ||
| Year 3 cost savings | 20% | 40% | 60% | 80% | 100% | |
| $2,619,632 | $5,239,263 | $7,858,895 | $10,478,527 | $13,098,158 | ||
| Cumulative cost savings | $5,756,073 | $11,512,146 | $17,268,219 | $23,024,292 | $28,780,365 | |
| TNF inhibitor class to biosimilar adalimumab | Year 1 cost savings | 10% | 20% | 30% | 40% | 50% |
| $2,654,027 | $5,308,054 | $7,962,081 | $10,616,108 | $13,270,135 | ||
| Year 2 cost savings | 15% | 30% | 45% | 60% | 75% | |
| $4,136,735 | $8,273,470 | $12,410,205 | $16,546,941 | $20,683,676 | ||
| Year 3 cost savings | 20% | 40% | 60% | 80% | 100% | |
| $5,723,240 | $11,446,480 | $17,169,719 | $22,892,959 | $28,616,199 | ||
| Cumulative cost savings | $12,514,002 | $25,028,004 | $47,359,547 | $50,056,008 | $62,570,010 | |
TNF = tumor necrosis factor.
When biosimilar adalimumab utilization was drawn from any reference self-injectable TNF inhibitor, cost savings were observed in fast and slow conversions on an annual and cumulative basis (Table 2). For a slow conversion (10%-20% over 3 years), savings increased each year and totaled $12,514,002 cumulatively. The savings PMPM were $0.22 in year 1, $0.34 in year 2, and $0.48 in year 3. In the fast conversion scenario (50%-100% over 3 years), total cumulative savings were $62,570,010. Costs savings PMPM increased over time to $1.11 in year 1, $1.72 in year 2, and $2.38 in year 3.
Results of the 1-way sensitivity analysis showed the model was most sensitive to the WAC of reference adalimumab, the WAC of biosimilar adalimumab, and the plan population size (Supplementary Figure 2 (347.5KB, pdf) ).
WAC PRICE REDUCTIONS AND CONVERSION RATE FROM REFERENCE ADALIMUMAB
When considering varied conversion and biosimilar price reduction from reference adalimumab in the first 12 months, savings increased with increasing conversion and greater price reduction (Figure 1). Assuming a 30% conversion rate of biosimilar adalimumab, a biosimilar WAC price reduction of 5% to 60% lower than reference adalimumab resulted in potential savings of $1,095,853 to $15,378,466 over the first 12 months (Supplementary Table 3 (347.5KB, pdf) ). Likewise, cost savings PMPM increased with increasing price reduction, from $0.09 with a 5% price reduction to $1.28 with a 60% price reduction. The trend was similar for the other price-reduction scenarios.
FIGURE 1.
Varying Utilization and Biosimilar Price Reduction Relative to Reference Adalimumab in the First 12 Months
Cost savings were observed with slow and fast shifts from the reference TNF inhibitor class at all price reductions used in the model (Figure 2). Assuming a 50% shift rate to biosimilar adalimumab, a biosimilar WAC price reduction of 5% to 60% lower than reference adalimumab led to savings of $5,507,365 to $48,202,331 in the first 12 months (Supplementary Table 4 (347.5KB, pdf) ). Savings were also seen in PMPM, ranging from $0.46 with a 5% price reduction to $4.02 with a 60% price reduction. Savings increased as the price reduction and class shift to biosimilar adalimumab increased.
FIGURE 2.
Varying Utilization From Tumor Necrosis Factor Inhibitor Class and Biosimilar Price Reduction Relative to Reference Adalimumab in the First 12 Months
MEDICAL EXPENDITURE DIFFERENTIALS WITH VARYING NUMBER OF VISITS FROM REFERENCE ADALIMUMAB
Continued cost savings were observed with the inclusion of simple and complex office visit expenditures on an annual and cumulative basis (Table 3). For the base cases of no additional visits, the budget impact was $5,756,073 with a PMPM cost of $0.16. With increasing number of visits, cost savings remained stable, with a cumulative differential of $113,000 between base case and 10 additional visits for simple visits. For complex visits, the differential from base case was $635,000 with 10 additional visits. The impact on PMPM was minimal; when compared with the base case scenario of no simple visits, the PMPM remained stable at $0.16, regardless of scenario. For the unlikely scenario of 10 simple office visits, the cumulative costs increased by $56,982 when compared with the scenario of 5 office visits. Likewise, with complex office visits, PMPM costs increased by $0.02 when comparing the assumption that all switch patients incurred 5 complex visits each with the assumption that all switch patients had 10 complex visits.
TABLE 3.
Budget Impact of the Number of Office Visits After Switching From Reference Adalimumab to Biosimilar Adalimumab
| Scenario | Year 1 | Year 2 | Year 3 | Cumulative | |
|---|---|---|---|---|---|
| Budget impact | Budget impact | PMPM | |||
| Simple office visits | |||||
| No additional visits (base case) | −$1,230,903 | −$1,905,539 | −$2,619,632 | −$5,756,073 | −$0.16 |
| 50% of patients have 1 visit | −$1,229,684 | −$1,903,652 | −$2,617,038 | −$5,750,375 | −$0.16 |
| All patients have 1 visit | −$1,228,466 | −$1,901,766 | −$2,614,445 | −$5,744,677 | −$0.16 |
| All patients have 5 visits | −$1,218,717 | −$1,886,675 | −$2,593,699 | −$5,699,092 | −$0.16 |
| All patients have 10 visits | −$1,206,532 | −$1,867,812 | −$2,567,766 | −$5,642,110 | −$0.16 |
| Complex office visits | |||||
| No additional visits (base case) | −$1,230,903 | −$1,905,539 | −$2,619,632 | −$5,756,073 | −$0.16 |
| 50% of patients have 1 visit | −$1,224,146 | −$1,895,040 | −$2,605,148 | −$5,724,335 | −$0.16 |
| All patients have 1 visit | −$1,217,390 | −$1,884,542 | −$2,590,665 | −$5,692,597 | −$0.16 |
| All patients have 5 visits | −$1,163,341 | −$1,800,555 | −$2,474,797 | −$5,438,694 | −$0.16 |
| All patients have 10 visits | −$1,095,780 | −$1,695,571 | −$2,329,963 | −$5,121,314 | −$0.14 |
PMPM = per member per month.
Discussion
In a hypothetical commercial plan of 1 million lives, use of biosimilar adalimumab led to substantial cost savings for payers across multiple scenarios. Greater and faster biosimilar conversion and class shift rates resulted in more cost savings. Faster conversion to biosimilar adalimumab from reference adalimumab or faster shift from the reference TNF inhibitors (etanercept, certolizumab pegol, or golimumab) had nominally more savings compared with slower scenarios. These scenarios illustrate the opportunity cost of conservative biosimilar strategies for payers. However, even conservative strategies can bring a substantial amount of potential cost savings, as evidenced by an estimated $7 million budget impact using the slowest scenario in the model. As future pharmacy benefit management strategies may evolve into managing the entire TNF inhibitor class as a whole, increasing utilization of a TNF biosimilar while decreasing utilization of multiple TNF reference products can lead to even further savings as demonstrated in our scenarios.
Furthermore, the biosimilar price reduction from reference adalimumab may also decrease costs in the near future and long term. In the WAC price-reduction scenarios, potentially lower prices of biosimilar adalimumab can increase cost savings even more for payers. These lower drug acquisition costs can be realized immediately, depending on the upcoming launch prices of adalimumab biosimilars, and in the future with the eventual decline in reference adalimumab price overall because of the increased competition with biosimilars. Historically, biosimilars launch at lower WACs than their corresponding reference products, which leads to instant cost savings for payers as demonstrated in the base case.16 Even if only 10% of patients converted from reference adalimumab, savings more than $1 million were observed with a 15% price reduction from reference adalimumab. With the recent launch of several adalimumab biosimilars and more to come, the drug price of adalimumab products is likely to fall, which would be a benefit for reducing drug costs and developing more sustainable health care. Reducing drug costs may lead to increased patient access to these high-cost medications.
When introducing biosimilars onto a formulary and to patients, especially in the case of nonmedical switching, there are potential short-term costs (ie, simple office visit for a nurse to educate patients on biosimilars or additional laboratory tests or imaging) that can deter inclusion of biosimilars on the formulary. A cohort-based decision-tree model estimated the short-term (1-year) administrative and initiation costs associated with switching patients with RA from the reference biologic to the biosimilar of etanercept.19 The study found that over a 1-year period, switching to a biosimilar was more costly in terms of higher overall annual per-patient costs than continuous reference product treatment because of administrative costs and increased health care resource utilization. Additionally, a systematic literature review by Hillhouse et al suggested that patients who switched from a reference product to a biosimilar had increased short-term health care resource utilization and costs.9
Although short-term medical expenditures are possible, the financial impact of biosimilar use may not be as pronounced when considering the large patient population that uses adalimumab and the cost savings due to reduced biosimilar drug prices. When we modeled the budget impact based on these results, our scenario analyses of additional simple and complex office visits had a minimal impact on the budget and found that the costs observed after switching to biosimilar adalimumab were negligible. Even in the improbable scenario of 10 additional complex office visits per switch patient with biosimilar adalimumab, there was a minimal impact on the budget, and cost savings were still observed with biosimilar adalimumab. The model demonstrated that it would take a highly unlikely scenario of each switch patient to incur 10 additional complex office visits to decrease the PMPM cost savings by $0.02. Indeed, actual savings would depend on factors such as a health plan’s population, drug utilization rates, and the margin between biosimilar and reference pricing. Additionally, the systematic literature review by Hillhouse et al considered etanercept and infliximab; we did not include infliximab in our model as it is reimbursed under the medical benefit and is not self-injected. In the studies that reviewed etanercept, overall cost savings were seen in PsO and mixed results were seen in RA and PsA.
Although the first biosimilar adalimumab was authorized by the European Medicines Agency in 2017, limited evidence exists related to the economic impact of adalimumab biosimilars. A budget impact analysis in the United Kingdom assessed infliximab, etanercept, and adalimumab biosimilars in patients with rheumatology disorders (RA, AS, PsA) and gastroenterology disorders (CD and UC). Results showed that adoption of 3 adalimumab biosimilars provided more than £176 million (approximately $218 million 2023 USD) in savings for rheumatology disorders and £91 million ($113 million 2023 USD) for gastroenterology disorders over 3 years, assuming a 33% price reduction from reference adalimumab and increasing uptake of biosimilar adalimumab annually.20 This current model showed savings ranging from $1 million to $25 million over 1 year with a 30% price reduction relative to the WAC of reference adalimumab in similar disease states.
The launch of adalimumab biosimilars is expected to provide substantial savings in biologic spending. In one estimate, adalimumab biosimilars are expected to save $19.5 billion over 5 years, which accounts for 50.8% of the total biosimilar market savings.21 The majority of the savings are expected to be indirect through the lowering of reference biologic prices. Adalimumab biosimilars have the potential to deliver large cost savings to payers and patients. Incentive programs will likely increase biosimilar use. One such program is required by the Centers for Medicare & Medicaid Services and dictates Medicare payments must include the biosimilar average sales price and a fixed percentage of the reference biologic.22 Patients may experience cost savings in copays or cost sharing as prices of biologics and biosimilars decrease because of increased competition.
LIMITATIONS
Although this budget impact analysis explored multiple scenarios of biosimilar price reductions and utilization rates, as well as short-term medical expenditures, there are some limitations that need to be considered. Current model assumptions and inputs represent a generalization and interpretation from the literature. These include the utilization rates for each of the comparators as they reflect data from real-world studies. The actual and projected savings that individual payers may experience with conversion to a biosimilar will depend on their specific values for each parameter, the most impactful of which were identified by the 1-way sensitivity analysis. Our findings present a range of possible savings, based on some likely (as well as some unlikely) scenarios, and individual payers should conduct their analyses using their own inputs to more precisely project savings. Other complexities, such as payer rebates and copay assistance cards, were also not considered in the model as these vary greatly by payer and patient. As the purpose of the model was to understand the impact of biosimilar adalimumab on the adalimumab and TNF inhibitor landscape as a whole, results were not separated by disease state or indication. We did not consider other TNF inhibitor biosimilars in the model, as at the time of the analysis, there were no self-injectable TNF inhibitor biosimilars launched in the United States; these should be considered in future models. Although the model treats the indications as mutually exclusive groups, patients may have more than 1 indication. This may lead to double counting when estimating the target population size when multiple indications are selected. For example, patients with PsO are significantly more likely to develop PsA or RA in comparison with patients without PsO.23 Additionally, only a commercial plan was explored, and results may not be applicable to Medicare or other types of payers.
Conclusions
In this model of 1 million patients in a commercial plan, use of biosimilar adalimumab leads to cost savings across multiple scenarios of price reductions and biosimilar adalimumab uptake. Future economic models should evaluate the impact of increasing patient access in light of the cost savings seen in this model. Higher and faster biosimilar conversion and shift rates have the potential to further increase savings and drive competition. Additionally, even with short-term medical expenditures, cost savings were still realized when switching to biosimilar adalimumab. Increased competition and lower costs by biosimilars could potentially aid payers with cost savings by switching to biosimilar adalimumab from reference adalimumab or other TNF inhibitors.
ACKNOWLEDGMENTS
The authors would like to acknowledge Andrea Gundlach, PharmD, MPH, CMPP; Bridgette Schroader, PharmD, MPA, BCOP; and Kylie Matthews, MS, of Cencora for medical writing assistance.
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