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Association of Osteoporosis-related Healthcare Costs with the Use of Tenofovir Disoproxil Fumarate and Tenofovir Alafenamide in Chronic Hepatitis B Patients: a Population-based National Cohort Study in Korea
Yakhak Hoeji 2024;68(1):26-35
Published online February 29, 2024
© 2024 The Pharmaceutical Society of Korea.

You Ran Noh*,** and Hae Sun Suh*,**,***,#

*Department of Regulatory Science, Graduate School, Kyung Hee University
**Institute of Regulatory Innovation through Science (IRIS), Kyung Hee University
***College of Pharmacy, Kyung Hee University
Correspondence to: #Hae Sun Suh, PhD, College of Pharmacy, Kyung Hee University, 26, Kyunghee-daero, Dongdaemun-gu, Seoul, Republic of Korea
Tel: +82-2-961-9492, Fax: +82-2-961-9580
E-mail: haesun.suh@khu.ac.kr
Received November 12, 2023; Revised January 7, 2024; Accepted January 7, 2024.
Abstract
Long-term administration of tenofovir disoproxil fumarate (TDF) for chronic hepatitis B (CHB) may lead to bone mineral density loss. Tenofovir alafenamide (TAF) developed to address these concerns. This study aimed to investigate whether there is a significant difference in osteoporosis-related healthcare costs between CHB patients treated with TDF and TAF. This study is a retrospective cohort study using claims data from the Health Insurance Review and Assessment Service (HIRA) covering the entire population in Korea. The cohort included CHB patients treated with TDF or TAF from November 2017 to April 2022. We applied inverse probability of treatment weighting (IPTW) to balance baseline characteristics observed for one-year preceding prescription date. Osteoporosis-related costs per patient per year (PPPY) included all healthcare costs with an osteoporosis diagnosis code including outpatient and hospitalization costs. 7,172 and 3,837 patients were administered TDF and TAF respectively. After IPTW, TDF group had higher outpatient costs ($11.2) compared to TAF group ($6.1), but the difference was not statistically significant (p=0.1001). The total hospitalization cost was $24.6 in TDF group and $9.8 in TAF group, not statistically significant (p=0.1633). This large-scale population-based study found no significant difference in osteoporosis-related healthcare costs between CHB patients treated with TDF and TAF.
Keywords : Chronic hepatitis B virus, Tenofovir Disoproxil Fumarate, Tenofovir Alafenamide, Osteoporosis, Healthcare costs, Real-world data
Introduction

Chronic hepatitis B (CHB) is defined as the presence of hepatitis B surface antigen (HBsAg) for more than 6 months after infection with the hepatitis B virus (HBV).1) The endemicity of Hepatitis B virus is classified as high, intermediate, and low based on HBsAg prevalence and the mode of infection. Korea was classified as an area of intermediate endemicity. The prevalence of HBsAg carriage was 8 to 10% in the 1980s and has remained at 2.9% since 2010 in Korea.2)

The goals of antiviral treatment are to decrease the morbidity and mortality related to CHB. The achievement of a sustained suppression of HBV replication has been associated with normalization of serum alanine aminotransferase (ALT), loss of hepatitis B e antigen (HBeAg) and improvement in liver histology.3)

Nucleos(t)ide analogues (NA) can be classified into drugs with high genetic barriers and drugs with low genetic barriers. For the treatment of patients with CHB, monotherapy using NAs with high genetic barriers to resistance or peginterferon alfa is recommended. NAs with high genetic barriers available in Korea are as follows: Entecavir (ETV), Tenofovir Disoproxil Fumarate (TDF), Tenofovir Alafenamide (TAF) and Besifovir (BSV).4)

TDF was approved for marketing by Ministry of Food and Drug Safety (MFDS) in June 2010 and reimbursed from December 2012. Long-term administration of adefovir or TDF in the patients with CHB, may result in decreased renal function and bone mineral density.4) TAF is designed as an alternate prodrug form of tenofovir to have higher plasma stability compared to TDF. Therefore, it has the advantage of delivering the active metabolite, tenofovir-diphosphate, to hepatocytes at a lower dose than TDF.5) Based on these advantages, TAF has demonstrated non-inferior antiviral efficacy and improved safety on bone and kidney compared to TDF in patients with chronic hepatitis B in a randomized, double-blind, non-inferiority Phase 3 clinical trial.6) TAF was approved for marketing by MFDS in May 2017 and reimbursed from November 2017. Previous literatures comparing the effects of oral antiviral agents, including TDF, on osteoporosis in patients with chronic hepatitis B only included the studies comparing the impact of TDF and ETV on bone density. Those studies were conducted only to compare osteoporosis incidence on a small scale.7-10) However, there were no available studies that compared TDF and TAF on osteoporosis-related medical costs or healthcare resource utilizations. Therefore, this study aims to analyze whether there is a significant difference in osteoporosisrelated medical costs among chronic hepatitis B patients who are administrating TDF and TAF using a large-scale dataset from the Health Insurance Review and Assessment Service.

Methods

Data sources

This study utilized claims data from the Health Insurance Review and Assessment Service (HIRA) from November 2016 to April 2022 as the data source. HIRA claims data, which encompass approximately 98% of the entire population of South Korea through national health insurance, include medical service records spanning a broad range of healthcare environments, from infants to the elderly, regardless of geographical location. This representation and comprehensiveness offer advantages for conducting research that may be challenging through randomized controlled trials (RCTs). Additionally, as individuals’ medical service usage records are continuously accumulated in the database, it allows for the ongoing observation of the same subjects over a certain period. This longitudinal characteristic makes it suitable for cohort studies exploring long-term outcomes due to exposures.11) The Kyung-Hee University Institutional Review Board determined that this study was exempted from ethical review (KHSIRB-22-456(EA).



Study population

The study cohort consisted of adult patients aged 18 years and older diagnosed with chronic hepatitis B from November 2017 to April 2022. Chronic hepatitis B was defined as patients diagnosed with hepatitis B virus infection according to the International Classification of Diseases (ICD-10), specifically with chronic viral hepatitis B with delta-agent (B18.0) or without delta-agent (B18.1). Patients with a history of receiving treatment for chronic hepatitis B from November 2016 to October 2017 were excluded. Subsequently, patients who were prescribed the oral antiviral agents TDF and TAF for the treatment of chronic hepatitis B were included in the study. Each medication was defined based on the codes from the HIRA: 493901ATB, 664901ATB, 665001ATB, 665101ATB, 665201ATB, 665501ATB for TDF, and 665301ATB for TAF. The codes for TDF included not only the original product but also generics, while the code for TAF only covered original product, as no generics were available. Finally, patients diagnosed with osteoporosis based on operational definitions were included in the study.12)

Patients who met the following criteria were excluded from the study: 1) Age under 18, 2) History of taking different antiviral agents within the past year prior to being prescribed the oral antiviral agents under investigation, 3) Diagnosed with osteoporosis or history of taking osteoporosis treatment within the past year prior to being prescribed the oral antiviral agents under investigation, and 4) Concurrent infection with Acquired Immune Deficiency Syndrome (AIDS). 5) Unable to follow-up for 1 year from the diagnosis date of osteoporosis.



Study design

The study is a retrospective cohort study, and the overall study scheme is illustrated in Fig. 1. The diagnosis date of chronic hepatitis B was set as the first cohort entry date, and the date of prescription of oral antiviral agents was set as the second cohort entry date. A one-year period prior to the second cohort entry date was defined as the washout period, during which patients who met the exclusion criteria described in the study were excluded. Subsequently, the diagnosis date of osteoporosis was set as the index date.



Fig. 1. Study scheme

In this study, patient age, sex, and insurance type were determined based on the second cohort entry date, and the following baseline covariates were observed for the one-year period preceding the second cohort entry date: history of liver transplantation, fracture history, Charlson Comorbidity Index (CCI), co-medication, and comorbidity. For co-medication and comorbidity, factors known to increase the risk of osteoporosis, which is the outcome of interest in this study, were selected.13,14) Co-medications included oral glucocorticoids, thyroid hormones, aromatase inhibitors, and comorbidities included conditions such as diabetes and rheumatoid arthritis.

To reduce the risk of immortal time bias, the following methods were employed. First, only new users of the medication were included by excluding patients with a history of taking other antiviral agents in the year prior to the second cohort entry date. Second, an active comparator group, rather than a placebo group, was used as the control group.



Exposure and outcomes

The exposure of interest in this study is the use of oral antiviral agents, specifically TDF and TAF. Oral antiviral agent exposure was defined using an as-treated approach, where patients were considered exposed to the medication until switching to other oral antiviral agents, discontinuation of the study medication, death, or the end of the follow-up period. The study only included patients with a minimum of one year of guaranteed follow-up. Patients may have gaps between the last day of previous prescription medication use and the next prescription date, and this interval was considered a grace period. In this study, the grace period was defined as 30 days, and if the gap between prescriptions exceeded 30 days, it was considered as medication discontinuation.15)

The outcome of interest in this study is osteoporosis related healthcare costs. Osteoporosis was defined based on the following four criteria:12) 1) Prescription of medications exclusively used for osteoporosis, 2) Receiving a diagnosis of osteoporosis (ICD-10 code M80, M81) and being prescribed osteoporosis-related medications, 3) Hospitalization for osteoporosis in males aged 70 or older and females aged 65 or older, or two or more outpatient visits or one-day hospital stays, and 4) Incidence of one or more osteoporotic fractures. Osteoporosis-related healthcare costs were evaluated during a one-year follow-up period. These costs were categorized into outpatient-related costs and hospitalization costs based on the type of visit, further divided into medication-related costs and medical expenses. After the first diagnosis of osteoporosis, all healthcare costs with a diagnosis code for osteoporosis were considered as osteoporosis-related costs. Costs were calculated as average costs per patient per year in each group and were expressed in US dollars based on the 2022 exchange rate. (1USD =1,294 Korean won).



Statistical analysis

In this study, the inverse probability of treatment weighting (IPTW) method was used to address the imbalance between the groups taking TDF and TAF. In observational studies, the underlying characteristics of patients often influence the choice of treatment. Therefore, when estimating the treatment effects on outcomes, it is essential to account for differences in baseline characteristics between the treatment and control groups. IPTW is one of the widely used methods based on propensity scores to reduce the impact of these confounding factors in observational studies. In comparison to TDF, TAF, which has been relatively recently introduced to the market, was chosen for the IPTW method due to its lower patient count, reducing concerns about patient loss during the process. To assess the balance between the two treatment groups, the absolute standardized difference was used, and a difference of 0.1 or less was considered acceptable.16) IPTW was performed by estimating propensity scores using logistic regression, including the following covariates: gender, age, type of insurance, CCI, comedication, and comorbidity.

For continuous variables, the mean and standard deviation were reported, while for categorical variables, proportions (%) were reported. To test differences between groups, t-tests were used for continuous variables, and chi-square tests were used for categorical variables. A two-sided p-value less than 0.05 was considered statistically significant. All statistical analyses were performed using SAS Enterprise Guide 9.4 (SAS Institute Inc., Cary, North Carolina, USA).

Results

This study included 17,082 adult patients as a cohort, aged 18 and above diagnosed with chronic hepatitis B from November 2017 to April 2022 who were taking the oral antiviral drugs TDF or TAF. Among them, a total of 11,009 patients met the inclusion criteria after excluding those who did not meet the criteria: 7,172 were using TDF, and 3,837 were using TAF (Fig. 2).



Fig. 2. Flow chart of included patients

The baseline characteristics of the TDF treatment group and the TAF treatment group after IPTW were shown in Table 1. Chronic hepatitis B was most common in the age group of 35-64 years, and it was more common in males than females. In the cohort before IPTW, there were differences between the two groups in terms of age and the proportion of loop diuretic co-medication, with an absolute standardized difference of 0.1 or higher. IPTW method was used to balance the two treatment groups. In the cohort after IPTW, all covariates had an absolute standardized difference of less than 0.1, indicating appropriate balance between the two groups (Table 2).

Baseline characteristics of TDF group and TAF group before IPTW

TDF N=7,172 TAF N=3,837 p-value aSD
Age: n (%) <0.001 0.104
20-34 years 900 (12.5) 460 (12.0)
35-49 years 2,872 (40.0) 1,728 (45.0)
50-64 years 2,826 (39.4) 1,388 (36.2)
65- years 574 (8.0) 261 (6.8)
Female: n (%) 2,757 (38.4) 1,539 (40.1) 0.091 0.034
Insurance: n (%) <0.001 0.089
National health insurance 6,888 (96.0) 3,745 (97.6)
Medical aid, Veterans 284 (4.0) 92 (2.4)
Liver transplant status: n (%) 22 (0.3) 0 (0.0) 0.001 0.078
Fracture history: n (%) 1 (0.0) 0 (0.0) 1.000 0.017
Charlson Comorbidity Index: mean (SD) 0.85 (0.99) 0.80 (0.93) 0.028 0.044
Co-medication: n (%)
Hormonal therapy
Glucocorticoids 2,397 (33.4) 1,343 (35.0) 0.100 0.033
Thyroid hormone 120 (1.7) 80 (2.1) 0.142 0.030
Aromatase inhibitors 17 (0.2) 1 (0.0) 0.121 0.035
Ovarian suppressing agents 46 (0.6) 15 (0.4) 0.121 0.035
Androgen deprivation therapy 15 (0.2) 2 (0.1) 0.081 0.043
Thiazolidinediones 69 (1.0) 21 (0.5) 0.028 0.048
Psychotropic and anticonvulsant therapy
SSRI 190 (2.6) 101 (2.6) 1.000 0.001
Anticonvulsants 0 (0.0) 0 (0.0) - <0.001
Drugs used for cardiovascular diseases
Heparins 146 (2.0) 73 (1.9) 0.685 0.010
Loop diuretics 390 (5.4) 104 (2.7) <0.001 0.138
Drugs targeting the immune system
Calcineurin inhibitors 41 (0.6) 21 (0.5) 0.977 0.003
Drugs used for gastrointestinal diseases
Proton pump inhibitors 2,600 (36.3) 1,292 (33.7) 0.007 0.054
Comorbidity: n (%)
HCV co-infection 91 (1.3) 51 (1.3) 0.858 0.005
Endocrine disorders
Hyperthyroidism 5 (0.1) 0 (0.0) 0.243 0.037
Hypogonadism 15 (0.2) 8 (0.2) 1.000 <0.001
Hyperparathyroidism 11 (0.2) 5 (0.1) 0.968 0.006
Diabetes mellitus 21 (0.3) 5 (0.1) 0.142 0.035
Growth hormone deficiency and acromegaly 0 (0.0) 0 (0.0) - <0.001
Cushing syndrome 4 (0.1) 4 (0.1) 0.597 0.017
Gastrointestinal, hepatic, and nutritional disorders
Celiac disease & malabsorption 0 (0.0) 0 (0.0) - <0.001
Inflammatory bowel disease 0 (0.0) 0 (0.0) - <0.001
Gastric bypass surgery 0 (0.0) 0 (0.0) - <0.001
Anorexia nervosa 0 (0.0) 0 (0.0) - <0.001
Hematological disorders
Multiple myeloma 6 (0.1) 2 (0.1) 0.831 0.012
Renal disorders
Idiopathic hypercalciuria 124 (1.7) 59 (1.5) 0.503 0.015
Chronic kidney disease 17 (0.2) 22 (0.6) 0.008 0.053
Autoimmune disorders
Rheumatoid arthritis 1 (0.0) 5 (0.1) 0.039 0.043
Systemic lupus erythematosus 0 (0.0) 0 (0.0) - <0.001
Ankylosing spondylitis 1 (0.0) 0 (0.0) 1.000 0.017
Chronic obstructive pulmonary disease 225 (3.1) 109 (2.8) 0.420 0.017

Abbreviations: TAF, tenofovir alafenamide; TDF, tenofovir disoproxil fumarate; aSD, absolute standardized difference; SSRI, selective serotonin reuptake inhibitor; HCV, hepatitis C virus; SD, standard deviation; IPTW, inverse probability of treatment weighting



Baseline characteristics of TDF group and TAF group after IPTW

TDF TAF p-value aSD
Age: % 0.996 0.005
20-34 years 12.4 12.5
35-49 years 41.8 41.9
50-64 years 38.2 38.0
65- years 7.6 7.5
Female: % 39.0 39.3 0.800 0.005
Insurance: % 0.859 0.004
National health insurance 96.6 96.5
Medical aid, Veterans 3.4 3.5
Liver transplant status: % 0.2 0.0 <0.001 0.063
Fracture history: % 0.0 0.0 0.318 0.013
Charlson Comorbidity Index: mean (SD) 0.83 (0.98) 0.83 (0.94) 0.866 0.003
Co-medication: %
Hormonal therapy
Glucocorticoids 34.0 34.0 0.983 <0.001
Thyroid hormone 1.8 1.8 0.915 0.002
Aromatase inhibitors 0.2 0.1 0.871 0.006
Ovarian suppressing agents 0.6 0.5 0.787 0.006
Androgen deprivation therapy 0.2 0.2 0.814 0.007
Thiazolidinediones 0.8 0.8 0.861 0.004
Psychotropic and anticonvulsant therapy
SSRI 2.6 2.7 0.913 0.002
Anticonvulsants 0.0 0.0 - <0.001
Drugs used for cardiovascular diseases
Heparins 2.0 2.0 0.931 0.002
Loop diuretics 4.5 4.5 0.922 0.002
Drugs targeting the immune system
Calcineurin inhibitors 0.6 0.4 0.132 0.028
Drugs used for gastrointestinal diseases
Proton pump inhibitors 35.3 35.3 0.926 0.002
Comorbidity: %
HCV co-infection 1.3 1.3 0.991 <0.001
Endocrine disorders
Hyperthyroidism 0.0 0.0 0.026 0.030
Hypogonadism 0.2 0.2 0.952 0.001
Hyperparathyroidism 0.1 0.1 0.881 0.003
Diabetes mellitus 0.2 0.2 0.792 0.006
Growth hormone deficiency and acromegaly 0.0 0.0 - <0.001
Cushing syndrome 0.1 0.1 0.989 <0.001
Gastrointestinal, hepatic, and nutritional disorders
Celiac disease & malabsorption 0.0 0.0 - <0.001
Inflammatory bowel disease 0.0 0.0 - <0.001
Gastric bypass surgery 0.0 0.0 - <0.001
Anorexia nervosa 0.0 0.0 - <0.001
Hematological disorders
Multiple myeloma 0.1 0.1 0.751 0.006
Renal disorders
Idiopathic hypercalciuria 1.6 1.6 0.887 0.003
Chronic kidney disease 0.3 0.3 0.918 0.002
Autoimmune disorders
Rheumatoid arthritis 0.0 0.1 0.697 0.009
Systemic lupus erythematosus 0.0 0.0 - <0.001
Ankylosing spondylitis 0.0 0.0 0.318 0.013
Chronic obstructive pulmonary disease 3.0 3.1 0.965 0.001

Abbreviations: TAF, tenofovir alafenamide; TDF, tenofovir disoproxil fumarate; aSD, absolute standardized difference; SSRI, selective serotonin reuptake inhibitor; HCV, hepatitis C virus; SD, standard deviation; IPTW, inverse probability of treatment weighting



Table 3 represents the average healthcare costs related to osteoporosis per patient per year in the TDF treatment group and the TAF treatment group before IPTW. In the TDF treatment group, the average outpatient cost was \$11.3, which was higher than the average outpatient cost of \$6.3 in the TAF treatment group, but this difference was not statistically significant (p=0.1001). Among these costs, medical expenses were \$6.1 in the TDF treatment group and \$1.3 in the TAF treatment group, with the TDF treatment group having higher medical expenses, but this difference was not statistically significant (p=0.0744). The average total hospitalization cost was \$25.6 in the TDF treatment group and \$9.4 in the TAF treatment group, both of which were higher than total outpatient costs, but there was no statistically significant difference between the two groups (p=0.1321). Hospitalization costs had a significant proportion of medical expenses, with \$14.9 in the TDF treatment group and \$8.6 in the TAF treatment group, and there was no statistically significant difference between the two groups (p=0.2740).

Osteoporosis related healthcare costs of TAF and TDF group before IPTW

Unit: USD (Per patient per year) TDF group Mean (SD) TAF group Mean (SD) p-value
Outpatient visits
Total outpatient cost 11.3 (232.7) 6.3 (81.4) 0.1001
Medical expense 6.1 (218.5) 1.3 (39.4) 0.0744
Medication cost 5.2 (76.3) 5.0 (80.3) 0.8657
Hospitalizations
Total hospitalization cost 25.6 (867.4) 9.4 (203.3) 0.1321
Medical expense 14.9 (412.6) 8.6 (188.7) 0.2740
Medication cost 10.7 (494.4) 0.8 (15.9) 0.0899

Abbreviations: TAF, tenofovir alafenamide; TDF, tenofovir disoproxil fumarate; IPTW, inverse probability of treatment weighting; USD, United States dollar; SD, Standard deviation

Student’s t-test was used to compare TDF group and TAF group.



Table 4 represents the average healthcare costs related to osteoporosis per patient per year in the TDF treatment group and the TAF treatment group after IPTW. Both the total outpatient cost and total hospitalization cost remained statistically nonsignificant between the TDF treatment group and the TAF treatment group, as they were before IPTW (p=0.1001 and p=0.1633, respectively). When dividing these costs into medical expenses and medication costs for comparison, there were still no statistically significant differences between the TDF treatment group and the TAF treatment group.

Osteoporosis related healthcare costs of TAF and TDF group after IPTW

Unit: USD (Per patient per year) TDF group Mean (SD) TAF group Mean (SD) p-value
Outpatient visits
Total outpatient cost 11.2 (207.3) 6.1 (96.3) 0.1001
Medical expense 6.2 (196.1) 1.3 (46.5) 0.0709
Medication cost 5.0 (64.6) 4.8 (93.9) 0.9171
Hospitalizations
Total hospitalization cost 24.6 (746.7) 9.8 (250.8) 0.1633
Medical expense 14.4 (360.1) 9.0 (233.3) 0.3455
Medication cost 10.1 (420.4) 0.8 (19.1) 0.0994

Abbreviations: TAF, tenofovir alafenamide; TDF, tenofovir disoproxil fumarate; IPTW, inverse probability of treatment weighting; USD, United States dollar; SD, Standard deviation

Student’s t-test was used to compare TDF group and TAF group.


Discussion

This study is the first large-scale population-based research analyzing the difference in osteoporosis-related healthcare costs in chronic hepatitis B patients administering oral antiviral therapy, TDF and TAF. TDF, commonly used for the treatment of chronic hepatitis B, may lead to renal impairment and decreased bone density with long-term use. To address these drawbacks, TAF, another prodrug form of tenofovir, was developed. TAF demonstrated improved bone density-related safety for chronic hepatitis B patients in randomized double-blind non-inferior phase 3 clinical trials when compared head-to-head with TDF. Therefore, this study aimed to analyze whether there was a significant difference in osteoporosis-related healthcare costs between the TAF treatment group and the TDF treatment group in chronic hepatitis B patients, using a large-scale claims data from the Health Insurance Review and Assessment Service.

In this study, 7,172 patients with TDF and 4,712 patients with TAF who were diagnosed with chronic hepatitis B were included from November 2017 to April 2022. (Fig. 2) Randomized Controlled Trials (RCTs) are considered the standard approach for estimating the effects of treatment, intervention, and exposure on outcomes. Assigning to treatment randomly helps ensure that baseline characteristics, whether measured or unmeasured, are not confounded, allowing for a direct comparison of the treatment's effects between the treatment and control groups. There is a growing interest in using observational studies, in addition to RCTs, to estimate the impact of treatment on outcomes. In observational studies, the selection of treatment is frequently influenced by the patients’ baseline characteristics. Consequently, when analysing the impact of treatments on results, it is crucial to consider and adjust for variations in baseline characteristics between the groups receiving treatment and those in the control group. Recently, there has been growing interest in methods based on propensity scores to reduce the influence of such confounding factors.17) Among these, IPTW is a method that uses propensity scores to assign weights to each individual based on their inverse probability of receiving the actual treatment, thus balancing the baseline characteristics between the treatment and control groups. Importantly, IPTW offers the advantage of increasing the effective sample size because it does not exclude patients, unlike propensity score matching methods that exclude unmatched patients from the analysis.18) Therefore, in this study, given the smaller number of patients receiving TAF compared to TDF, we aimed to correct for confounding factors in baseline characteristics using the IPTW method, which does not result in data loss. Most patients diagnosed with chronic hepatitis B taking TDF or TAF in this study were in the age group of 35-64, and the male-to-female ratio was higher. When comparing the TDF treatment group and the TAF treatment group, there were absolute standardized differences of 0.1 or higher in baseline characteristics such as age and loop diuretic use before IPTW. However, after implementing IPTW, all covariates represented an absolute standardized difference of 0.1 or less, indicating balance between the groups.

The study compared osteoporosis-related healthcare costs between the TDF group and the TAF group before and after implementing IPTW. While the TDF group showed higher costs than the TAF group for all costs, there was no statistically significant difference. This trend persisted even after conducting IPTW. After IPTW, the mean outpatient costs were low in the TDF group at \$11.2 and \$6.1 in the TAF group. This can be attributed to the low incidence of osteoporosis in both groups, with a rate of 1.35% (97 out of 7,172 patients) in the TDF group and 1.20% (46 out of 3,837 patients) in the TAF group, indicating that osteoporosis did not occur in most patients.

This study has limitations that it lacks information on laboratory measurements such as weight and height because of the characteristics of the claims data from the Health Insurance Review and Assessment Service. Considering that factors like a low Body Mass Index (BMI) are known risk factors for osteoporotic fractures,14) this study did not include all risk factors that may influence osteoporosis outcomes. Additionally, the claims data only include items covered by health insurance and do not cover non-reimbursable items. Information on over-the-counter medications such as calcium supplements or dietary supplements used for osteoporosis prevention is not available from the claims data. This study attempted to overcome the limitations of observational research by conducting IPTW to adjust for confounding factors among patient groups. However, unlike randomized controlled trials, the use of propensity scores can only adjust for measurable confounders, and it has limitation that it cannot adjust for unmeasurable confounding factors.18) Finally, this study was analyzed without considering the skewness of medical costs. Therefore, further studies that take into account the skewness of medical costs will be necessary.

Nonetheless, this study is the first study that analyzed osteoporosis-related healthcare costs in chronic hepatitis B patients taking TAF compared to TDF using a large-scale claims data. Particularly, the study aimed to correct for confounding factors and balance the baseline characteristics of the two groups through the implementation of IPTW. The research findings revealed no statistically significant difference in osteoporosis-related costs between the TAF treatment group and the TDF treatment group in patients with chronic hepatitis B.

Conclusion

This study is the first large-scale population-based research analyzing the difference in osteoporosis-related healthcare costs in chronic hepatitis B patients administering oral antiviral therapy, TDF and TAF. The research findings revealed no statistically significant difference in osteoporosis-related costs between the TAF treatment group and the TDF treatment group in patients with chronic hepatitis B.

Acknowledgement

This research was supported by a grant (21153MFDS601) from Ministry of Food and Drug Safety in 2023.

Conflict of Interest

All authors declare that they have no conflict of interest.

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