Abstract
Introduction
Thromboembolic events (TEs) are associated with considerable costs. However, there is a paucity of evidence quantifying the economic burden associated with TEs among patients with immune-mediated diseases (IMDs).
Methods
This retrospective cohort study used the IBM MarketScan® Commercial and Medicare Supplemental Claims databases (2014–2018). Commercially insured adults with IMDs were classified into two cohorts based on diagnosis of TEs (deep vein thrombosis, pulmonary embolism, ischemic stroke, myocardial infarction). Patients in the TE cohort were matched on type of IMD, age, sex, and year of diagnosis to patients in the no TE cohort. In the TE cohort, the index date was the date of first TE following first IMD diagnosis. In the no TE cohort, the index date was assigned so the duration from first IMD diagnosis to index date matched the duration for the corresponding patient in the TE cohort. All-cause total healthcare costs were compared between cohorts in the 30-day and 1-year periods following the index date (inclusive). Unadjusted comparisons were conducted using Wilcoxon signed-rank tests. Adjusted results were estimated using generalized estimating equations with robust sandwich estimator.
Results
Overall, 9681 matched patients were included in each cohort (mean age 61.1 years; 63.7% female). The TE cohort had higher proportions of comorbidities than the no TE cohort (Charlson Comorbidity Index [1.5 vs. 0.9]; p < 0.0001). Adjusted all-cause total healthcare costs were significantly greater in the TE cohort versus no TE cohort in the 30-day and 1-year periods following the index date (cost difference: 30-day, $17,574; 1-year, $36,459; both p < 0.0001) and were driven by inpatient costs (cost difference: 30-day, $14,864; 1-year, $23,360; both p < 0.0001). TE-related healthcare costs were $15,955 and $20,239 in the 30-day and 1-year periods, respectively.
Conclusion
Among patients with IMDs, TEs are associated with substantial economic burden within 30-days and 1-year following the event.
Keywords: Cost, Deep vein thrombosis, Economic burden, Immune-mediated diseases, Ischemic stroke, Myocardial infarction, Pulmonary embolism, Thromboembolic events
Key Summary Points
| Why carry out this study? |
| Immune-mediated diseases (IMDs) are associated with an increased risk of thromboembolic events (TEs), which include venous events, such as deep vein thrombosis and pulmonary embolism, as well as arterial events, such as ischemic stroke and myocardial infarction. |
| IMDs and TEs are each associated with a substantial economic burden; however, limited evidence is available regarding the economic burden of TEs among patients with IMDs. |
| What was learned from this study? |
| Among adults with IMDs, the adjusted all-cause total healthcare costs incurred over the 30-day and 1-year periods following a TE were significantly greater among patients who experienced TEs than among patients who did not experience TEs (cost difference: 30-day, $17,574; 1-year, $36,459; both p < 0.0001); inpatient costs accounted for most of the cost differences. |
| Efforts aimed at reducing the risk of TEs among patients with IMDs may help lower the economic burden in this population. |
Introduction
Immune-mediated diseases (IMDs) encompass a broad spectrum of unrelated conditions that involve dysregulation of the immune system leading to abnormal activation of inflammatory pathways [1]. IMDs can affect any organ in the body and typically result in debilitating symptoms that may be acute or chronic [2]. Over 100 conditions have been classified as IMDs; examples include rheumatoid arthritis, ankylosing spondylitis, psoriasis/psoriatic arthritis, systemic lupus erythematosus, atopic dermatitis, multiple sclerosis, and inflammatory bowel disease [2, 3]. Although the prevalence of IMDs is reported to vary from 3% to 8% in Western regions (e.g., approximately 10–15 million Americans) [2, 4], these disabling conditions are among the leading causes of morbidity and mortality.
Patients with IMDs have increased risk of comorbidities, such as cardiovascular disease and thromboembolic events (TEs). TEs are potentially life-threatening events that include venous events, such as deep vein thrombosis (DVT) and pulmonary embolism (PE), as well as arterial events, such as ischemic stroke (IS) and myocardial infarction (MI) [5, 6]. TEs carry a significant economic burden [5]. Conservative estimates of the costs of incident venous TE (VTE) to the United States (US) healthcare system are approximately $7–10 billion each year [7]. TEs are also a strong predictor for unplanned readmissions in the US which can have a substantial economic impact on society [8].
While there have been studies on healthcare resource use and costs of TEs among the general population, for patients undergoing surgery and those diagnosed with cancer, less is known about the economic burden of TEs among patients with IMDs [9–11]. As the cost of TEs among patients with IMDs may differ from the costs of TEs in the general population or other patient populations, partly due to different comorbidity profiles, there is a need to quantify the economic burden in this patient population. To help address this knowledge gap, the current study quantified healthcare costs broadly among patients with IMDs who had evidence of a TE relative to patients with IMDs and no evidence of a TE.
Methods
Data Source
Data from the IBM MarketScan® Commercial and Medicare Supplemental Databases (2014–2018) were used for this study. These databases contain information on employer-paid encounters for active employees, early retirees, Consolidated Omnibus Budget Reconciliation Act continuees and dependents, as well as employer-sponsored Medicare supplemental healthcare encounters. Detailed information on patient demographic characteristics (e.g., age, sex, and geographic region), enrollment history, dates of service, and claims for medical (e.g., professional and institutional) and pharmacy services are also included in these databases.
Compliance with Ethics Guidelines
Institutional review board approval was not required for this study. The pre-existing, retrospective data from the IBM MarketScan® Commercial and Medicare Supplemental Databases are represented by IBM MarketScan to be fully de-identified in accordance with the Health Insurance Portability and Accountability Act. The data were provided under license agreement with IBM.
Study Design and Sample Selection
To be eligible for inclusion in this retrospective cohort study, patients were required to have at least two diagnoses (on separate dates) for an IMD, which included ankylosing spondylitis, atopic dermatitis, inflammatory bowel disease, multiple sclerosis, psoriasis, psoriatic arthritis, rheumatoid arthritis, and systemic lupus erythematosus. Patients diagnosed with a TE following an IMD diagnosis were matched to patients with no evidence of a TE at any time on the following characteristics: first IMD diagnosis, age at first IMD diagnosis, sex, and year of first IMD diagnosis. In this study, TEs included DVT, PE, IS, and MI. For patients with TE (i.e., TE cohort), the first diagnosis for a TE following the first diagnosis of an IMD was defined as the index date to help ensure that patients had an IMD at the time of the index TE. For patients in the cohort without TEs (i.e., no TE cohort), the index date was assigned so that the duration of time from the first IMD diagnosis to index date matched the duration from matched patients with TE. In this study, patients were required to have at least 6 months of continuous enrollment prior to the index date, at least one year of continuous enrollment following the index date, and be at least 18 years old on the index date. Patients in the TE cohort with no eligible matched controls were excluded from the analysis. For patients in the TE cohort with at least one eligible matched patient without a TE, one eligible patient was randomly selected.
Study Measures and Outcomes
Patient Characteristics
The following patient characteristics were assessed during the baseline period: demographics (age on index date, sex), type of IMD and non-IMD-related medications, and select comorbidities/conditions of interest.
Healthcare Costs of TE
Unadjusted all-cause total healthcare costs (medical and pharmacy) and cost differences between the TE and no TE cohorts were assessed during the 30-day and 1-year periods following the index date. In addition, models adjusted for the following: age on index date, sex (female), index year, healthcare plan type (capitation), baseline comorbidities/conditions of interest, baseline non-IMD medications, and baseline IMD medications. TE-related healthcare costs (i.e., cost of medical visits with diagnosis of TE) were also reported during the 30-day and 1-year periods following the index date.
Statistical Analysis
Study measures were described using means and standard deviations for continuous variables and counts and percentages for categorical variables. Unadjusted statistical comparisons for matched samples were conducted using Wilcoxon signed-rank tests for continuous variables and McNemar tests for categorical variables. The unadjusted results included mean (standard deviation) costs and differences in mean costs. Adjusted results included mean costs and p values that were estimated and compared using generalized estimating equations with a robust sandwich estimator. Data processing and statistical analyses were performed using SAS Enterprise Guide version 7.15 (SAS Institute Inc., Cary, NC).
Results
Patient Characteristics
After the sample selection criteria were applied, a total of 9681 matched patients were included in each cohort (Fig. 1). Across both cohorts, rheumatoid arthritis (31.6%) was the most prevalent type of first IMD, followed by inflammatory bowel disease (19.5%), psoriasis (16.5%), systemic lupus erythematosus (12.4%), multiple sclerosis (8.7%), atopic dermatitis (7.5%), psoriatic arthritis (3.1%), and ankylosing spondylitis (1.5%). The most common index event in the TE cohort was DVT (39.6%) followed by IS (31.8%), MI (18.9%), and PE (14.3%) (Table 1). In general, the TE cohort had higher rates of comorbidities than the no TE cohort, as reflected by the significant difference in the Charlson Comorbidity Index (1.5 vs. 0.9; p < 0.0001) and proportion of patients with comorbidities/conditions of interest (cardiovascular diseases, 68.0% vs. 52.8%; type 2 diabetes, 22.8% vs. 14.1%; both p < 0.0001) (Table 1). The three most common medications in the TE cohort were glucocorticoids (35.6%), non-biologic immunomodulators (29.1%), and nonsteroidal anti-inflammatory drugs (21.6%). Use of anticoagulants was significantly higher in the TE cohort vs. the no TE cohort (17.2% vs. 3.4%; p < 0.0001) (Table 1).
Fig. 1.
Sample selection of patients with IMD with and without TEs. IMD immune-mediated disease, TE thromboembolic event. aIMDs included ankylosing spondylitis, atopic dermatitis, inflammatory bowel disease, multiple sclerosis, psoriasis, psoriatic arthritis, rheumatoid arthritis, and systemic lupus erythematosus. bQualifying diagnoses for IMDs were identified on the inpatient and/or outpatient services claims datasets. All patients were required to have eligibility data. cTEs included deep vein thrombosis, pulmonary embolism, ischemic stroke, and myocardial infarction. dMatching between the thromboembolic event cohort and no TE cohort was done with a 1:41 ratio to keep as many eligible patients with thromboembolic events as possible. eFor patients with TE with ≥ 1 eligible matched patient with no TE, 1 patient with no TE was randomly selected
Table 1.
Demographics and clinical characteristics among patients with IMDs measured during the baseline perioda
| TE cohort (n = 9681) |
No TE cohort (n = 9681) |
p value | |
|---|---|---|---|
| Age at index date (years), mean ± SD | 61.1 ± 14.6 | 61.0 ± 14.6 | < 0.0001 |
| Female, n (%) | 6169 (63.7) | 6169 (63.7) | – |
| Healthcare plan type, n (%) | |||
| Plans with capitation | 958 (9.9) | 1077 (11.1) | 0.0049 |
| Plans without capitation | 8616 (89.0) | 8537 (88.2) | 0.0715 |
| Unknown | 107 (1.1) | 67 (0.7) | 0.0023 |
| Index year, n (%) | |||
| 2015 | 1704 (17.6) | 1736 (17.9) | 0.0845 |
| 2016 | 3251 (33.6) | 3234 (33.4) | 0.5404 |
| 2017 | 2625 (27.1) | 2611 (27.0) | 0.6245 |
| 2018 | 2101 (21.7) | 2100 (21.7) | 0.9597 |
| Immune-mediated diseaseb, n (%) | |||
| Ankylosing spondylitis | 179 (1.8) | 161 (1.7) | 0.0080 |
| Atopic dermatitis | 775 (8.0) | 753 (7.8) | 0.0164 |
| Inflammatory bowel disease | 1956 (20.2) | 1932 (20.0) | 0.0259 |
| Multiple sclerosis | 863 (8.9) | 854 (8.8) | 0.1060 |
| Psoriasis | 1750 (18.1) | 1729 (17.9) | 0.1707 |
| Psoriatic arthritis | 435 (4.5) | 410 (4.2) | 0.1073 |
| Rheumatoid arthritis | 3301 (34.1) | 3201 (33.1) | < 0.0001 |
| Systemic lupus erythematosus | 1292 (13.3) | 1256 (13.0) | 0.0033 |
| TEs during baseline, n (%) | 1049 (10.8) | – | – |
| Deep vein thrombosis | 491 (5.1) | – | – |
| Pulmonary embolism | 289 (3.0) | – | – |
| Ischemic stroke | 337 (3.5) | – | – |
| Myocardial infarction | 119 (1.2) | – | – |
| TEs on index, n (%) | – | ||
| Deep vein thrombosis | 3838 (39.6) | – | – |
| Pulmonary embolism | 1385 (14.3) | – | – |
| Ischemic stroke | 3080 (31.8) | – | – |
| Myocardial infarction | 1826 (18.9) | – | – |
| Charlson comorbidity index, mean ± SD | 1.5 ± 1.7 | 0.9 ± 1.2 | < 0.0001 |
| Conditions/comorbidities of interest, n (%) | |||
| Cancer | 1300 (13.4) | 861 (8.9) | < 0.0001 |
| Cardiovascular diseases | 6584 (68.0) | 5113 (52.8) | < 0.0001 |
| Atherosclerosis | 1911 (19.7) | 844 (8.7) | < 0.0001 |
| Atrial fibrillation | 850 (8.8) | 390 (4.0) | < 0.0001 |
| Heart failure | 791 (8.2) | 238 (2.5) | < 0.0001 |
| Hyperlipidemia | 3878 (40.1) | 3205 (33.1) | < 0.0001 |
| Hypertension | 5354 (55.3) | 3930 (40.6) | < 0.0001 |
| Chronic kidney disease | 888 (9.2) | 402 (4.2) | < 0.0001 |
| Chronic obstructive pulmonary disease | 1059 (10.9) | 469 (4.8) | < 0.0001 |
| Diabetes | |||
| Type 1 | 315 (3.3) | 138 (1.4) | < 0.0001 |
| Type 2 | 2204 (22.8) | 1364 (14.1) | < 0.0001 |
| Fracture (hip or leg) | 149 (1.5) | 50 (0.5) | < 0.0001 |
| Peripheral vascular disease | 1135 (11.7) | 513 (5.3) | < 0.0001 |
| Pregnancyc | 86 (1.4) | 65 (1.1) | 0.0665 |
| Common classes of medications, n (%) | |||
| Non-immunomodulatory | |||
| Anticoagulants | 1669 (17.2) | 330 (3.4) | < 0.0001 |
| Hormone replacement therapiesc | 345 (5.6) | 397 (6.4) | 0.0481 |
| Testosterone replacement therapiesc | 110 (3.1) | 102 (2.9) | 0.5809 |
| Oral contraceptivesc | 208 (3.4) | 248 (4.0) | 0.0386 |
| Immunomodulatory | |||
| Biologics | 1006 (10.4) | 1122 (11.6) | 0.0038 |
| TNF inhibitors | 766 (7.9) | 908 (9.4) | < 0.0001 |
| Interferon-β1a | 83 (0.9) | 101 (1.0) | 0.1521 |
| Interleukin inhibitors | 114 (1.2) | 78 (0.8) | 0.0080 |
| Other biologics | 62 (0.6) | 50 (0.5) | 0.2568 |
| JAK inhibitors | 58 (0.6) | 41 (0.4) | 0.0843 |
| Non-biologic immunomodulators | 2813 (29.1) | 2936 (30.3) | 0.0287 |
| Methotrexate | 1117 (11.5) | 1246 (12.9) | 0.0017 |
| S1P receptor modulators | 34 (0.4) | 56 (0.6) | 0.0151 |
| Other non-biologic immunomodulators | 1941 (20.0) | 1978 (20.4) | 0.4725 |
| 5-Aminosalicyclic acid derivative agents | 1033 (10.7) | 1059 (10.9) | 0.4843 |
| Glucocorticoids | 3443 (35.6) | 2412 (24.9) | < 0.0001 |
| NSAIDs | 2087 (21.6) | 2014 (20.8) | 0.1851 |
aThe baseline period was defined as the 1-year period prior to the index date
IMD immune-mediated disease, JAK Janus kinase, NSAIDs nonsteroidal anti-inflammatory drugs, S1P sphingosine 1-phosphate, SD standard deviation, TEs thromboembolic events, TNF tumor necrosis factor
bIMDs were reported at any time prior to the index date
cThe proportions of patients with pregnancy, hormone replacement therapies, and oral contraceptives were reported out of the total number of female patients in each group. The proportion of patients with testosterone replacement therapies was reported out of the total number of male patients in each group
Healthcare Costs
In both the unadjusted and adjusted analyses, the TE cohort incurred significantly greater total healthcare costs in the 30-day and 1-year periods following the index event versus the no TE cohort IMD (unadjusted cost difference: 30-day, $18,050; 1-year, $38,650; adjusted cost difference: 30-day, $17,574; 1-year, $36,459; all p < 0.0001) (Tables 2 and 3). Overall, the adjusted cost differences in the 30-day and 1-year periods were slightly less than the unadjusted cost differences but remained statistically significant after adjusting for potential confounders. The total healthcare cost differences were largely driven by differences in inpatient costs (unadjusted cost difference: 30-day, $15,628; 1-year, $25,046; adjusted cost difference: 30-day, $14,864; 1-year, $23,360; all p < 0.0001) (Table 2). In the TE cohort, TE-related healthcare costs were $15,955 and $20,239 in the 30-day and 1-year periods, respectively.
Table 2.
Unadjusted cost differences during the 30-day and 1-year periods among patients with IMDs
| 30-day period | 1-year period | |||||||
|---|---|---|---|---|---|---|---|---|
| TE cohort (n = 9681) |
No TE cohort (n = 9681) |
Cost difference | p value | TE cohort | No TE cohort | Cost difference | p value | |
| All-cause healthcare costs ($)a,b | ||||||||
| Total costs | 19,681 | 1631 | 18,050 | < 0.0001 | 58,474 | 19,824 | 38,650 | < 0.0001 |
| Medical costs | 18,640 | 777 | 17,863 | < 0.0001 | 45,710 | 8956 | 36,753 | < 0.0001 |
| Inpatient | 15,812 | 184 | 15,628 | < 0.0001 | 27,432 | 2387 | 25,046 | < 0.0001 |
| Outpatient | 1990 | 551 | 1440 | < 0.0001 | 15,708 | 6079 | 9628 | < 0.0001 |
| Emergency department | 838 | 42 | 796 | < 0.0001 | 2,570 | 490 | 2079 | < 0.0001 |
| Pharmacy costs | 1041 | 854 | 187 | < 0.0001 | 12,764 | 10,867 | 1896 | < 0.0001 |
IMDs immune-mediated diseases, TE thromboembolic event
aUnadjusted results include predicted costs and p values, estimated using generalized estimating equations with a robust sandwich estimator
bAll costs were inflated to 2019 United States dollar
Table 3.
Adjusted cost differences during the 30-day and 1-year periods among patients with IMDs
| 30-day period | 1-year period | |||||||
|---|---|---|---|---|---|---|---|---|
| TE cohort (n = 9681) |
No TE cohort (n = 9681) |
Cost difference | p value | TE cohort | No TE cohort | Cost difference | p value | |
| All-cause healthcare costs ($)a,b | ||||||||
| Total costs | 19,306 | 1731 | 17,574 | < 0.0001 | 57,374 | 20,915 | 36,459 | < 0.0001 |
| Medical costs | 17,849 | 872 | 16,977 | < 0.0001 | 42,742 | 9987 | 32,755 | < 0.0001 |
| Inpatient | 15,081 | 217 | 14,864 | < 0.0001 | 25,945 | 2585 | 23,360 | < 0.0001 |
| Outpatient | 1923 | 576 | 1347 | < 0.0001 | 14,666 | 6710 | 7956 | < 0.0001 |
| Emergency department | 854 | 42 | 812 | < 0.0001 | 2383 | 547 | 1836 | < 0.0001 |
| Pharmacy costs | 1191 | 827 | 364 | < 0.0001 | 14,066 | 10,909 | 3157 | < 0.0001 |
IMDs immune-mediated disease, TE thromboembolic event
aAdjusted results include predicted costs and p values, estimated using generalized estimating equations with a robust sandwich estimator. The adjusted models controlled for the following: cohort assignment, age at index date, sex (female), index year, healthcare plan type (capitation), baseline comorbidities/conditions of interest, baseline non-immune-mediating medications, and select baseline immune-mediating medications
bAll costs were inflated to 2019 United States dollar
Discussion
This retrospective cohort study quantified the healthcare costs among adults with IMDs who had evidence of a TE relative to patients with IMDs and no evidence of a TE. Overall, our results showed that patients with IMDs with a TE incurred greater total healthcare costs relative to those without a TE. Moreover, the main driver of this high-cost burden was inpatient costs. Taken together, results from this study have the potential to provide healthcare stakeholders with insights regarding decisions to prioritize efforts aimed at reducing the high economic burden of TEs among patients with IMDs.
To date, few studies have examined healthcare costs associated with TEs among patients with IMDs [7, 12]. As a result, insights regarding the cost burden in the IMD population have been limited. Previously, cost studies of TE have focused on specific subtypes of TE, IMDs, or the cost burden of TEs among the general population or in populations without IMDs [7, 12–14]. For example, a retrospective study published in 2019 based on data from 2003 to 2011 found that hospitalization costs among patients with systemic lupus erythematosus who experienced VTEs were greater by $25,400 compared with those who did not experience VTEs [7]. The current study not only included patients with systemic lupus erythematosus but also with other IMDs, and found similar hospitalization costs. Other studies have shown that patients with TEs experience a significant economic burden compared with the general population. For example, one study estimated that annualized all-cause median costs were $17,512 and $18,901 for patients with DVTs and PEs, respectively, compared with $680 in the control group (general population) [14]. Results from another study estimated that among patients with a VTE, the total annual healthcare costs for a VTE ranged from $7594 to $16,644 [13]. While the current study also found an increased economic burden among patients with TEs, the incremental economic burden of TE in our study among patients with IMDs is greater than the incremental burden previously reported in the general population. This difference can be possibly attributed to more severe TEs among IMD populations, higher downstream costs due to long-term medical needs after an acute TE, and/or a more severe comorbidity profile that further complicates the management of TEs, compared to the general population. Our findings extend the literature by quantifying the healthcare costs of TEs among patients with a range of IMDs. Additionally, this study assessed the overall burden of TE by including both venous and arterial events while previous studies have focused on the burden associated with specific subtypes of TE, such as venous TE [7, 13, 14]. The current study did not assess the cost associated with each TE, but future studies could consider how costs may differ by subtype of TE.
Understanding the drivers of the increased healthcare costs can help stakeholders identify where to direct resources to mitigate costs. In this study, inpatient costs were the main driver behind the differences in healthcare costs between patients with IMDs with TEs and without TEs. The differences in inpatient costs accounted for 85% and 64% of the adjusted total cost difference in the 30-day and 1-year periods. This difference may be due to the acute TE on the index date and resulting inpatient stays. In this study, TE-related healthcare costs (i.e., cost of medical visits with diagnosis of TE) accounted for 88% and 52% of the unadjusted total cost difference in the 30-day and 1-year periods. It is important to note that the economic burden of TEs extends beyond the diagnosis and treatment of the initial event as costs of recurring TEs and associated longer-term effects can cumulatively add to the overall long-term cost burden, which is reflected in the 30-day vs. 1-year costs. Moreover, history of a TE is a significant risk factor for recurrent TEs [15, 16]. For example, the risk of recurrence of VTEs has been reported to be 5–7% per year, which is 50 times higher than the risk in patients without a history of VTE [17]. Certain medications, such as glucocorticoids, nonsteroidal anti-inflammatory drugs, and Janus kinase inhibitors, have been reported to increase the risk of TE [5]. Given the substantial clinical and economic burden of TE among patients with IMDs, the risks of TEs among patients with IMDs should be carefully considered when optimizing treatment for this patient population. In addition, it may be helpful for further studies to evaluate ways to reduce the burden of TE after its occurrence among patients with an IMD.
Limitations
This study should be considered within the context of specific limitations. First, as with any observational claims-based study, databases may be vulnerable to errors in coding and/or data omission. Second, the primary function of claims data is to capture diagnostic and procedure codes for reimbursement. Therefore, the impact of omitted variables on costs associated with TE outcomes (e.g., body mass index, smoking, and immobility) could not be considered in the adjusted analysis as these measures are not collected in claims data. Moreover, other unmeasured and unobserved confounders could not be adjusted for, although this study adjusted for factors that were as comprehensive as was feasible from claims data. Finally, this analysis was conducted using a commercially insured population in the US. As a result, the findings may not be generalizable to other populations such as the Medicaid population, which may have different patient profiles than commercially insured patients, resulting in a cost estimate of the TE burden that could potentially be greater. Future studies using generalizable databases could provide insight into the economic burden among other segments of the population like Medicaid or uninsured/self-pay patients. As a result of these limitations, the results from this dataset may be a conservative estimate of the economic burden among patients with IMDs who experience TEs.
Conclusions
Among patients with IMDs, TEs are associated with substantial economic burden within the 30-day and 1-year periods after the event. Research focused on TE risk reduction among patients with IMDs may help to reduce their economic burden. Specifically, given the elevated risks of TEs and the high economic burden of TEs among patients with IMD, the risk of TEs should be carefully considered when optimizing treatment for this patient population.
Acknowledgements
Funding
Funding for this study and the Journal’s Rapid Service Fee were provided by Arena Pharmaceuticals, Inc.
Medical Writing/Editorial Assistance
Editorial assistance in the preparation of this article was provided by Dr. Gloria DeWalt of Analysis Group, Inc. Support for this assistance was funded by Arena Pharmaceuticals, Inc.
Authorship
All named authors meet the International Committee of Medical Journal Editors (ICMJE) criteria for authorship for this article, take responsibility for the integrity of the work as a whole, and have given their approval for this version to be published.
Author Contributions
Juliana Setyawan, Emma Billmyer, Fan Mu, Miriam L. Zichlin, Hongbo Yang, Nathaniel Downes were involved in the study design and data acquisition. All authors were involved in data analysis and interpretation, drafting or revising the manuscript for intellectual content, take responsibility for the integrity of the work as a whole, and approved the final manuscript.
Disclosures
Emma Billmyer, Fan Mu, Miriam L. Zichlin, Hongbo Yang, and Nathaniel Downes are employees of Analysis Group Inc., which received consulting fees from Arena Pharmaceuticals, Inc. for the conduct of this study. Juliana Setyawan is an employee of Arena Pharmaceuticals, Inc. Andres Yarur serves as a paid consultant for Arena Pharmaceuticals, Prometheus Bioscience, and Takeda. Nassir Azimi is a member of the Delphi panel for Arena Pharmaceuticals; AstraZeneca – Speaker's Bureau; Daiichi Sankyo – Advisory Committee/Board Member, Speaker's Bureau; Gilead – Advisory Committee/Board Member, Speaker's Bureau; Janssen – Advisory Committee/Board Member, Speaker's Bureau. Vibeke Strand has received consultancy fees from AbbVie, Amgen, Arena Pharmaceuticals, AstraZeneca, Bayer, Blackrock, Bioventus, BMS, Boehringer Ingelheim, Celltrion, Concentric Analgesics, Crescendo/Myriad Genetics, EMD Serono, Equilium, Eupraxia, Flexion, Galapagos, Genentech/Roche, Gilead, GSK, Horizon, Ichnos, Inmedix, Janssen, Kiniksa, Kypha, Lilly, Merck, MiMedx, MyoKardia, Novartis, Pfizer, Regeneron, Samsung, Samumed, Sandoz, Sanofi, Scipher, Servier, Setpoint, Tonix, UCB. Vibeke Strand has served on Advisory Boards for AbbVie, Amgen, AstraZeneca, Bayer, BMS, Boehringer Ingelheim, Celltrion, Crescendo, EMD Serono, Galapagos, Genentech/Roche, GSK, Horizon, Ichnos, Janssen, Lilly, Merck, Novartis, Pfizer, Regeneron, Samsung, Sandoz, Sanofi, UCB.
Compliance with Ethics Guidelines
Institutional review board approval was not required for this study. The pre-existing, retrospective data from the IBM MarketScan® Commercial and Medicare Supplemental Databases are represented by IBM MarketScan to be fully de-identified in accordance with the Health Insurance Portability and Accountability Act. The data were provided under license agreement with IBM.
Data Availability
The datasets generated during the current study are not publicly available due to licensing agreement with IBM.
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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 generated during the current study are not publicly available due to licensing agreement with IBM.