Research Article - International Journal of Clinical Rheumatology (2021) Volume 16, Issue 5

Treatment patterns and costs of patients with ankylosing spondylitis initiating biologic therapy in taiwan - a population-based analysis

*Corresponding Author:
Chia-Fang Lee
Eli Lilly and Company (Taiwan), Inc. Taipei, Taiwan
E-mail: [email protected]

Abstract

Objective: To evaluate the real-world treatment patterns and costs of patients initiating their first biologic therapy for the treatment of Ankylosing Spondylitis (AS) in Taiwan.

Methods: Taiwan’s National Health Insurance claims data between 1/1/2014 and 12/31/2017 was used to identify and follow patients with AS initiating their first biologic therapy in 2015. Patients > 18 years of age, with AS (ICD-9-CM: 720.0), a claim for a biologic therapy in 2015, continuous enrollment for at least one year following index, and no claims for biologics in the previous year were indexed into the study. A matched cohort of non-biologic patients with AS receiving anti-inflammatory drugs was derived. Patients were followed from their index date (first biologic claim) through the end of the study period, death, or they were lost to follow-up.

Results: There were 430 as patients included in the biologic-initiators cohort (Adalimumab=191; Etanercept=122; Golimumab=177). PRE-index utilization rates were significantly higher for biologic-initiators compared to the matched cohort for corticosteroids, opioids, and csDMARDs (all p<0.0001). utilization rates of NSAIDs and csDMARDs were lower for biologic initiators and higher for the matched cohort during the follow-up period compared to the pre-index period. mean total healthcare costs were higher and average non-medication costs were lower for biologic-initiators compared to the matched cohort during the two years post-index.

Conclusions: Patients initiating their first biologic therapy for as had high rates of as-related medication utilization during the pre-index period followed by a decrease in utilization rates after biologic initiation.

Keywords

asia-pacific • economics • epidemiology

Introduction

During the pre-index period biologic initiators had significantly higher utilization rates of corticosteroids (58.8% vs. 37.2%; p<0.0001), opioids (58.6% vs. 37.2%; p<0.0001), and csDMARDs (85.8% vs. 42.8%; p<0.0001) compared to the matched cohort (Figures 1-3). Biologic initiators also had non-significantly higher absolute utilization rates compared to the matched cohort for all medication classes including NSAIDs (92.3% vs. 87.1%), topical analgesics (19.1% vs. 18.3%), muscle relaxants (52.1% vs. 49.8%), and pregabalin (1.2% vs. 1.0%).

clinical-rheumatology-timeline

Figure 1. Study timeline.

clinical-rheumatology-selection

Figure 2. Patient selection.

clinical-rheumatology-initiation

Figure 3. Medication utilization and relative change in the pre- and post-biologic initiation periods.

Relative reductions in medication usage between the pre- and post-index periods was generally higher for the biologic-initiators cohort than the matched cohort. The only increase in medication utilization for biologic-initiators was for sleep aids (+5.9%), compared to the matched cohort, which saw relative rates of utilization increase in NSAIDs (+2.2%), csDMARDs (+9.1%), sleep aids (+7.6%), and pregabalin (+70.0%). Relative reductions in medication utilization for biologic-initiators were found in muscle relaxants (-34.0%), opioids (-30.9%), corticosteroids (-30.8%), anxiolytics (-28.1%), pregabalin (-25.0%), topical analgesics (-24.6%), NSAIDs (-22.9%), csDMARDs (-9.2%), and antidepressants (-9.5%).

Biologic Switching

The median follow-up time of the biologic initiators was 29.9 m. The median length of follow-up did not significantly vary between first-line biologics with 29.8 m for adalimumab and etanercept, and 30.1 m for golimumab. Over the follow-up period, there were 40 (9.3%) patients switching to a second-line biologic. Switching patterns between biologics are described in the Sankey diagram (Figure 4). Patients initiating adalimumab were most likely to switch (12.0%; 23/191), followed by etanercept (7.4%; 9/122), and golimumab (6.8%; 8/117) during the follow-up period. The most utilized second-line therapy after switching was golimumab (57.5%; 23/40), followed by adalimumab (25.0%; 10/40), and etanercept (17.5%; 7/40).

clinical-rheumatology-patterns

Figure 4. Sankey diagram of treatment selection at index and switching patterns over follow-up of biologic-initiators (n=430).

Cost

Average mean total healthcare costs were higher for the biologic-initiators cohort (NT$579,444 and NT$571,244) compared to the matched cohort (NT$75,327 and NT$71,619) in both the first and second years of follow-up (Tables 1 & 2). The incremental cost between the cohorts was driven by additional drug costs for the biologic-initiators cohort. Average mean non-medication costs were lower for the biologic-initiators cohort in both years of follow-up. Non-drug costs decreased by 15.2% (NT$8,179), from NT$53,885 to NT$45,707 in the second year of followup compared to a 4.3% (NT$2,446) decrease from NT$56,893 to NT$54.447 for the matched cohort.

Characteristics Biologic Initiators Matched Cohort1 P-Value
(n=430) (n=1,678)
N % N %
Age         0.6861
  Mean (SD) 41.9 14.1 41.6 13.9  
  Median (IQR) 41 29.8-53.7 41.5 30.3-53.3  
    18.0 - 20.5 21 4.9 84 5 0.9938
    20.6 - 24.5 26 6 104 6.2  
    24.6 - 30.5 63 14.7 252 15  
    30.6 - 41.5 111 25.8 432 25.7  
    41.6 - 53.5 100 23.3 395 23.5  
    53.6 - 61.5 64 14.9 253 15.1  
    61.6 - 64.5 23 5.3 89 5.3  
    64.6 - 71.5 19 4.4 64 3.8  
>71.6 3 0.7 5 0.3  
Gender, Male 310 72.1 1216 72.5 0.8769
CCI (mean, SD) 0.8 1.3 0.7 1.1 0.2706
Cardiovascular 108 25.1 278 16.6 <0.0001
  Angina 10 2.3 25 1.5 0.2263
  Atherosclerosis 14 3.3 35 2.1 0.1508
  Cerebrovascular disease/Stroke 7 1.6 48 2.9 0.1525
  Coronary Artery Disease 21 4.9 45 2.7 0.0193
  Hypertension 97 22.6 242 14.4 <0.0001
  Myocardial Infarction 3 0.7 4 0.2 0.1546
  Peripheral Vascular Disease (PVD) 6 1.4 7 0.4 0.0208
  Venous Thromboembolism (VTE) 3 0.7 4 0.2 0.1546
GI Disorder 97 22.6 313 18.7 0.068
  Inflammatory Bowel Disease (IBD) 10 2.3 7 0.4 <0.0001
  Peptic Ulcer Disease 94 21.9 310 18.5 0.1115
Malignancies 7 1.6 32 1.9 0.7016
Metabolic Syndrome 73 17 244 14.5 0.2074
  Diabetes 33 7.7 142 8.5 0.5972
  Dyslipidemia 52 12.1 191 11.4 0.6807
Neurologic / Psychologic Conditions 2 0.5 1 0.1 0.1077
  Multiple Sclerosis 0 0 0 0 -----
  Parkinson Disease 2 0.5 1 0.1 0.1077
Respiratory Diseases 11 2.6 81 4.8 0.0399
  Asthma 8 1.9 71 4.2 0.0209
  Sleep Apnea 3 0.7 12 0.7 0.9693
Other Diseases          
  Rheumatoid Arthritis 45 10.5 88 5.2 <0.0001
  Osteoporosis 13 3 27 1.6 0.0552
  Uveitis 59 13.7 69 4.1 < 0.0001
  Psoriasis 30 7 12 0.7 <0.0001

Table 1. Baseline patient demographics and clinical characteristics.

Cost (Nt$) Biologic-Naive Matched Cohort
YEAR 1   YEAR 2 YEAR 1 YEAR 2
(n=430) (n=427) (n=1,678) (n=1,671)
MEAN SD MEDIAN IQR   MEAN SD MEDIAN IQR   MEAN SD MEDIAN IQR   MEAN SD MEDIAN IQR
Inpatient Costs
Medication 3,993.80 31,749.40 - 0-0 2,953.80 24,332.70 - 0 - 0 2,800.30 29,310.10 - 0 - 0 1,729.20 11,694.10 - 0 - 0
  Non-Medication 20,134.10 113,039.60 - 0-0 15,200.20 65,393.50 - 0 - 0 23,230.50 109,211.90 - 0 - 0 20,806.30 78,434.80 - 0 - 0
  Total Inpatient Costs 24,128.00 138,208.00 - 0-0 18,153.90 80,088.30 - 0 - 0 26,030.70 133,812.70 - 0 - 0 22,535.50 87,316.00 - 0 - 0
Outpatient Costs
  Medication 521,475.90 172,750.00 529,447.50 415,929–645,511 522,513.80 172,380.20 536,250.00 415,929 – 648,506 15,523.50 39,020.90 6,614.00 2,271 – 14,594 15,336.70 38,555.50 6,538.00 2,265 – 14,536
  Non-Medication 32,594.70 48,518.20 23,151.50 16,932–36,189 29,664.70 21,338.30 23,018.00 16,926 – 36,189 31,781.70 55,414.40 20,584.00 11,961 – 35,542 31,783.30 55,488.80 20,593.00 11,961 – 35,575
  Total Outpatient Costs 554,070.60 180,811.80 570,649.00 446,083–679,173 552,178.50 177,513.30 570,418.00 443,177 – 678,699 47,305.20 72,367.10 29,583.00 16,407 – 52,943 47,120.00 72,204.50 29,549.00 16,404 – 52,833
ER Costs
  Medication 88.7 426.6 - 0-0 69.7 332.9 - 0 - 0 110.2 603.4 - 0 – 1,499 105.5 575.3 - 0 - 72
  Non-Medication 1,156.50 5,176.80 - 0-0 841.8 2,458.80 - 0 - 0 1,881.10 5,716.70 - 0 - 73 1,857.80 5,704.20 - 0 – 1,403
  Total ER Costs 1,245.20 5,495.10 - 0-0 911.5 2,657.30 - 0 - 0 1,991.30 6,017.80 - 0 – 1,412 1,963.40 5,991.40 - 0 – 1,489
Total Costs
  Medication 525,558.50 172,269.40 543,485.50 419,344–649,572 525,537.30 172,795.30 543,313.00 415,929 – 650,620 18,434.00 50,619.40 7,012.50 2,536 – 16,312 17,171.40 41,107.20 6,978.00 2,506 – 16,277
  Non-Medication 53,885.30 148,702.20 25,149.50 17,324–43,915 45,706.60 75,296.60 24,797.00 17,234 – 43,346 56,893.30 136,371.40 24,930.50 13,479 – 53,172 54,447.40 111,897.60 24,868.00 13,457 – 53,051
  Total Costs 579,443.80 233,906.70 576,872.50 450,579–70,5261   571,243.90 194,007.10 576,741.00 448,664 – 704,487   75,327.20 167,513.60 35,260.00 18,920 – 71,446   71,618.80 130,881.30 35,117.00 18,829 – 71,228

Table 2. Healthcare Costs (NT$) during the follow-up period.

Discussion

We evaluated the treatment patterns and costs of AS patients in Taiwan initiating their first biologic and a matched cohort of AS patients receiving NSAIDs without a biologic for a minimum of one year. There were significantly higher rates of IBD (p<0.0001), uveitis (p<0.0001), and psoriasis (p<0.0001) in the cohort of patients initiating their first biologic compared to the matched cohort, which reflect the heterogeneity of axial spondyloarthritis conditions. Baseline utilization rates for corticosteroids, opioids, NSAIDs, muscle relaxants, and csDMARDs were all numerically higher for biologic-initiators than the matched cohort during the pre-index period. The heightened presence of baseline axial spondyloarthritis burden and pre-index medication utilization may have been contributing factors to the selection of a biologic for AS treatment.

This study showed a higher rate of rheumatoid arthritis diagnosis (10.5%) within the cohort of AS patients initiating their first biologic compared to the matched cohort (5.2%). The high rate of rheumatoid arthritis with AS patients observed in our study is consistent with other published analyses of claims-based datasets in the Asia-Pacific region including another study in Taiwan (4.98% among all AS patients) and Japan (53.9% among biologic DMARD patients) [1,2]. However, the coexistence of rheumatoid arthritis and AS in clinical practice is a relatively rare occurrence [3]. Rationales for the high RA prevalence rates in these claims analyses may include the use of rheumatoid arthritis diagnostic codes during the diagnostic process of AS or the presence of peripheral arthritis that is being misclassified.

An analysis of the hospital-based Medical Data Vision database in Japan also reported medication utilization during a 12-month follow-up period for AS biologic-initiators [2]. Utilization rates during the 12-month follow-up period for the biologic-initiators of the measured classes of medication higher for opioids (40.5% vs. 5.2%) and csDMARDs (77.9% vs. 66.1%) but lower for antidepressants (6.7% vs. 11.3%), anxiolytics (25.6% vs. 30.4%), and corticosteroids (40.7% vs. 52.2%) in our study compared to the recent study in Japan [2]. However, it should be noted that the study in Japan utilized a hospital-based database and may not be representative of the general AS population, which is observed in our analysis.

Of the patients initiating their first biologic for AS, 9.3% (n=40) switched to another TNFi during the follow-up period (median of 29.9 months) in this study. This rate of switching is consistent with other real-world studies evaluating treatment patterns of first-time biologic initiators in AS [4,5]. A study by Lindstrom et al. of 2,590 AS patients starting their first TNFi in Sweden between 2006 – 2015 reported 13% of patients were on their second TNFi at the end of their first year on therapy [4]. Palmer et al. reported 8.9% of TNFi initiators switched to another biologic within a 3-year follow-up period [5]. A claims-based analysis in the United States reported a slightly higher percentage (26.1%) of switching for first-time TNFi users for AS to a second TNFi during the two-year follow-up period [6].

Patients receiving biologic therapy in this study had higher average total costs compared to the matched cohort of non-biologic patients. However, nonmedication costs were similar between the two cohorts with average costs of NT$53,885 and NT$56,893 in the biologic and matched non-biologic cohorts, respectively. Furthermore, non-medication costs were reduced by 15.2% (NT$8,179) in the biologic cohort compared to 4.3% (NT$2,446) in the matched non-biologic cohort when comparing year one and year two of the followup period. The reduction in non-medication costs could be attributed to the effectiveness of biologics [7-11]. Comparison of costs across studies in different settings is difficult due to different health systems and pricing. However, most economic analyses of AS patients receiving biologics have reported that biologics are a high percentage of total healthcare costs [12,13].

The results of this study can be considered by decision-makers and stakeholders in Taiwan to understand the treatment patterns, cost, and unmet needs associated with TNFi biologics in Taiwan. Compared to the matched cohort, patients initiating a biologic experienced a greater decline in medication (corticosteroid, opioid, NSAID, antidepressant, anxiolytic, csDMARD, topical analgesic, muscle relaxants, and pregabalin) utilization after index, and a greater reduction in non-medication costs between year one and two of follow-up [14-18]. These changes show the value of biologic therapy in lowering the medication utilization and non-medication cost burden. However, 9% of patients initiating their first biologic had to switch to another biologic during the follow-up period. Furthermore, during the time of this study patients were limited in their selection of biologics during the index date to only TNFis, and the only alternative-MOA biologic, secukinumab, only became available towards the tail-end of the follow-up period [19-22]. As the TRA notes in their recommendations if there is intolerance and/or toxicity to the initial TNFi it is recommended for patients to try an alternative MOA [6]. As there was no alternative MOA available for the majority of this study’s timeline there may have been an even higher percentage of patients that would have benefited from switching to an alternative MOA. This suggests an unmet need for biologics with new mechanisms of action and/or better optimization of the first choice of biologic [23,24].

This study has several limitations. This was a non-randomized retrospective analysis that relied on propensity score matching of the limited clinical information available in the claims database and was subject to the potential of unmeasured confounding. The propensity score matching included age, gender, and CCI, but did not include the musculoskeletal and non-musculoskeletal manifestations and comorbidities included in this analysis, which could have accounted for differences between the cohorts [25]. AS-related comorbidities were not controlled for to allow for differences in disease severity between the two cohorts. As it is a claims-based database analysis only limited clinical information such as diagnostic codes are available, clinical information that could have been used to evaluate the effectiveness of biologic and non-biologic treatment was not included. Thus, no inference as to the reason for treatment switching, discontinuation, or augmentation can be made. The database also only contains data for direct healthcare costs (reimbursed materials and services) and does not include indirect costs such as those related to absenteeism and presenteeism, which are important factors for consideration in ankylosing spondylitis [26,27]. Second, ankylosing spondylitis is often subject to misdiagnosis and without clinical information validation of the ICD-code algorithm used to identify AS in this analysis cannot be trusted as fully accurate [28]. Lastly, the current treatment paradigm for biologic therapy of AS patients in Taiwan is likely different than in 2015 due to the reimbursement of new biologics with different mechanisms of action [29,30].

Conclusions

Patients initiating their first biologic therapy experienced large declines in the utilization of other AS-related medications and non-medication costs during their first year of therapy compared to a matched cohort of AS patients receiving NSAID therapy without biologic use. The rate of switching to a second-line biologic may suggest the need for additional biologic options at initiation and improvements in initial treatment selection.

Funding

This study was funded by Eli Lilly & Co.

Disclosures

Bruce CM Wang and Wesley Furnback are paid consultants to Eli Lilly & Co. Ching-Yun Wei and Chia-Fang Lee are employed by Eli Lilly & Co. Masayo Sato was employed by Eli Lilly & Co. at the time of this study.

References