Osteoporotic Fractures among Selective Estrogen Receptor Modulator Users in South Korea: Analysis Using National Claims Database

Article information

J Bone Metab. 2022;29(2):75-82
Publication date (electronic) : 2022 May 31
doi : https://doi.org/10.11005/jbm.2022.29.2.75
1Department of Orthopaedic Surgery, Seoul National University Bundang Hospital, Seongnam, Korea
2Department of Orthopaedic Surgery, Seoul National University College of Medicine, Seoul, Korea
3Department of Orthopaedic Surgery, Chung-Ang University Hospital, Chung-Ang University College of Medicine, Seoul, Korea
4Department of Orthopaedic Surgery, Seoul Bumin Hospital, Seoul, Korea
Corresponding author: Yong-Chan Ha, Department of Orthopaedic Surgery, Seoul Bumin Hospital, 389 Gonghang-daero, Gangseo-gu, Seoul 07590, Korea, Tel: +82-2-2620-0058, Fax: +82-2-2620-0100, E-mail: hayongch@naver.com
*Jung-Wee Park and Young-Kyun Lee contributed equally to this work and should be considered co-first authors.
Received 2022 January 20; Revised 2022 February 7; Accepted 2022 February 7.



We evaluated (1) compliance with selective estrogen receptor modulator (SERM) use in postmenopausal women; and (2) the risk of osteoporotic fractures according to compliance and other patient characteristics.


National claims data of postmenopausal women from January 2013 to December 2014 were reviewed. Demographics, comorbidities, type of medical institution, and patient compliance were investigated. Compliance was measured according to medication possession ratio (MPR) and the patients were classified into compliant (MPR ≥80%) or non-compliant (MPR <80%) groups. Osteoporotic fractures were followed up for 2 years after prescription.


Among 15,166 postmenopausal women, 4,130 were categorized as compliant. Osteoporotic fractures were confirmed in 669 patients. The hip fracture rate in the non-compliant group (0.39%) was marginally higher than that in the compliant group (0.36%; P=0.06). Compared to age 50 to 54 years, age 55 to 59 years showed protection against fractures (hazard ratio [HR], 0.57; 95% confidence interval [CI], 0.379–0.857; P=0.007), while those over 70 years showed a higher risk of fractures (HR, 2.035; 95% CI, 1.485–2.789; P<0.0001 for age 70–74 years; HR, 2.197; 94% CI, 1.588–3.041; P<0.0001 for age 75–79 years; and HR, 3.53; 95% CI, 2.493–4.999; P<0.0001 for age ≥80 years). Patients with mild (HR, 1.29; 95% CI, 1.088–1.530; P=0.0034) and moderate (HR, 1.286; 95% CI, 1.002–1.652; P=0.0486) comorbidities were associated with higher risks of fractures compared to those without comorbidities.


Among postmenopausal women with osteoporosis, only 27.2% complied with SERM therapy. A marginal difference in hip fracture rate was observed between the compliant and non-compliant groups. Older age and severe comorbidities were associated with higher risks of osteoporotic fractures.


A rising socioeconomic burden of osteoporosis and osteoporotic fractures have been recently recognized as a serious threat to global public health. It is estimated that half of the women and one in 5 men over 50 years of age are likely to suffer an osteoporotic fracture at least once in lifetime.[1] The number of osteoporotic fractures in the European Union was expected to increase from 3.5 million cases in 2010 to approximately 4.5 million cases in 2025.[2] The features of osteoporosis as a chronic disease underlines the importance of long-term medical therapy.

Osteoporosis medications are categorized into anti-resorptive drugs and anabolic drugs. Selective estrogen receptor modulators (SERMs) are drugs that modulate estrogen receptor with tissue selectivity. As anti-resorptive drugs in anti-osteoporotic medication, SERMs are commonly used in postmenopausal women. Currently, raloxifene, lasofoxifene, and bazedoxifene are approved by the US Food and Drug Administration as treatment for osteoporosis. Raloxifene was proven to be effective in reducing vertebral fractures in postmenopausal women with osteoporosis.[3,4] Lasofoxifene was effective in reducing the vertebral fracture risks up to 42% in a 5-year randomized clinical trial (RCT) on postmenopausal women.[5] The efficacy of bazedoxifene was proven to be comparable to that of raloxifene in fracture reduction.[6]

Even with the advancement of diverse medications to treat osteoporosis, poor adherence to medications remains as a vital issue in deterring the treatment effectivity. It was reported one-year compliance was lower than 25% in all osteoporosis therapies, leaving patients with higher risk for fractures and public health costs.[7] Among the antiresorptive osteoporosis drugs, there are numerus studies on compliance of BP,[814] whereas, there are relatively few studies on compliance of SERM.[3,15,16]

The primary objective of this study was (1) to evaluate the compliance to SERM medication in postmenopausal women with osteoporosis; and (2) to determine the risk of osteoporotic fractures according to the compliance or other patient characteristics, using the Korean National Health Insurance (KNHI) claims database.


1. Source of database

This was a retrospective registry study using a claims data from the KNHI database. All medical claims from entire South Korean institutions are reported to KNHI. The integrated KNHI data contain demographics, institutional information, comorbidity, and prescriptions of all postmenopausal osteoporotic patients in South Korea. All information was submitted in form of the International Classification of Diseases, Tenth Revision (ICD-10) diagnostic and procedural codes.

This study was approved by the institutional review board (IRB) of Chung-Ang University Hospital (IRB no. 1903-002-16253).

2. Patients

To evaluate the compliance to SERM medications and subsequent fracture risk, patients who were prescribed with SERMs for osteoporosis medication at least once from January 2013 to December 2014 were searched in the Health Insurance Review and Assessment Service (HIRA) database. The first prescription date of SERMs during the study period was defined as the index date. Patients with following conditions were excluded: (1) patients who are under 50 years of age; (2) patients who were not treated with bisphosphonates (BPs), calcitonin, or SERMs within 1 year before the index date; (3) patients who were treated with BPs or calcitonin during the study period; (4) patients who were diagnosed as cancer or Paget’s disease; (5) patients who died within 1-year after index date; (6) patients who suffered osteoporotic fractures within 2 years before or 1 year after the index date; and (7) patients who lacked basic demographic data. BPs and calcitonin treatments during the study period or underlying cancer or Paget’s disease could be a confounding factor in assessing the fracture risk regardless to the SERM compliance.[17,18] Osteoporotic fractures that occurred within 2 years before the index date is itself a independent risk factor for the secondary osteoporotic fracture.[19] Osteoporotic fractures within 1 year after the prescription of SERMs does not represent the fracture risk related to SERMs but rather it is related to the prior medication.[20]

The basic demographic data was collected. Age groups were stratified with 5-year intervals into 7 groups from 50 years of age to ages over 80 years. Information on the medical institutions where SERMs were prescribed at the index date was also collected. The type of medical institution was classified into tertiary hospitals (number of beds ≥500, number of departments ≥9), general hospitals (number of beds ≥100, number of departments ≥7), hospitals (number of beds ≥30), and clinics (number of beds <30). Underlying comorbidities of included patients were stratified using Charlson’s comorbidity index (CCI).[21]

3. Operational definition and outcome measures

The diagnosis of osteoporosis was specified as ICD-10 codes, M80*, M81*, or M82*. The SERMs used in South Korea during the study period included raloxifene and bazedoxifene. Anatomical Therapeutic Chemical code of G03XC indicated SERMs (G03XC01 as raloxifene and G03XC02 as bazedoxifene). Osteoporotic fractures were defined with ICD-10 codes of hip fractures (S72.0, S72.1), vertebral fractures (S22.0, S22.1, S32.0, S32.7, T08.0),[22] distal radius fractures (S52.5, S52.6),[23] and proximal humerus fractures (S42.2, S42.3).[24] The surveillance of osteoporotic fractures was conducted until 2 years after the prescription date.

The compliance to SERM medications were measured with medication possession ratio (MPR), which is the ratio of available doses of medication against the expected doses over a fixed period of time.[25] Patients were categorized into compliant group (MPR ≥80%) and non-compliant group (MPR <80%) in one year after the index date. A refill prescription was considered to have been continued without a break if there was a continuous gap of 30 days or more between the expected refill date and the actual refill date during the study period.

4. Statistical analysis

All patient data and osteoporotic fractures were compared between compliant group and the non-compliant group. Multivariable Cox proportional hazard models were used to analyze the hazard ratios of osteoporotic fracture occurrence between different compliance, age groups, type of institutions, and CCIs. All statistical analyses were carried out using SPSS for Windows software (version 25.0; SPSS Inc., Chicago, IL, USA). It was considered statistically significant when P was less than 0.05.

The approval of design and protocol of this study was exempted by the Institutional Review Board of our hospital with waived informed consent from all the involved patients as it was retrospective registry study.


1. Patient demographics

A total of 145,923 patients who were prescribed with SERMs for osteoporotic treatment from January, 2013 to December, 2014 were identified in KNHI database. After the exclusion process, 15,166 patients (all women) were included (Fig. 1).

Fig. 1

Flowchart of included patients. SERMs, selective estrogen receptor modulators.

Among the 15,166 included patients, compliant group accounted for 4,130 patients (27.2%) while remaining 11,036 patients (72.8%) were non-compliant. The distribution of age, level of medical institution, and comorbidities between 2 groups are summarized in Table 1.

Patient characteristics of compliant and non-compliant group

The most common age group for SERM prescription was 65 to 69 years both in compliant group and noncompliant group. SERMs were most commonly prescribed from clinics followed by general hospitals, hospitals, and tertiary hospitals in both groups. More than half of the included patients had no comorbidities and less than 5% of patients had severe comorbidities (CCI ≥3).

2. Osteoporotic fractures

There was total 669 (4.41%) osteoporotic fractures that occurred during the study period. Although osteoporotic fracture rate showed higher tendency in the non-compliant group than in the compliant group (4.54 % vs. 4.07 %), the difference was insignificant (P=0.21).

The most common location of osteoporotic fracture was spine (2.88%) followed by distal radius (0.94%), hip (0.38%), and proximal humerus (0.2%). This tendency was apparent in both groups. For spine, distal radius, and proximal humerus fractures, the prevalence of osteoporotic fractures was higher in non-compliant group compared to compliant group, but the difference did not reach statistical significance (Table 2). The prevalence of hip fractures was marginally higher in non-compliant group (0.39%) compared to compliant group (0.36%; P=0.06).

Osteoporotic fractures after selective estrogen receptor modulator treatment

Among the baseline characteristics, age and CCI was related to osteoporotic fractures (Table 3). With age group 50 to 54 years as a reference, age group 55 to 59 years was protective of fractures (hazard ratio [HR], 0.57; 95% confidence interval [CI], 0.379–0.857; P=0.007) while fracture risk increased in ages over 70 years (HR, 2.035; 95% CI, 1.485–2.789; P<0.0001 for age 70–74 years; HR, 2.197; 95% CI, 1.588–3.041; P<0.0001 for age 75–79 years; HR, 3.53; 95% CI, 2.493–4.999; P<0.0001 for age ≥80 years). With patients with no underlying comorbidity (CCI, 0) as a reference, those with mild comorbidity (CCI 1; HR, 1.29; 95% CI, 1.088–1.530; P=0.0034) and those with moderate comorbidity (CCI 2; HR, 1.286; 95% CI, 1.002–1.652; P=0.0486) were related to higher risk of osteoporotic fractures. Other factors such as compliance and type of institutions where the patients were treated were not related to the osteoporotic fracture occurrence.

Multivariable Cox proportional hazard model of baseline characteristics for osteoporotic fractures


Patients who were compliant to SERM treatment (MPR ≥80%) for 2 years only accounted for 27.2% of total SERM prescribed patients in South Korea. Among the SERM prescribed population, 4.41% suffered osteoporotic fractures. Compared to non-compliant group, compliant group tend to show lower prevalence of osteoporotic fractures both in total or by subtypes but the difference was marginal in hip and otherwise insignificant. Osteoporotic fractures were less likely to occur in patients with ages of 50 to 54 years and more likely to occur in patients with ages over 70 years and in those with severe comorbidities.

Adherence to osteoporotic medications has been considered as a serious threat to public health. Although Ringe et al. [15] reported the rate of compliant patients of raloxifene, alendronate, and risedronate as 80%, 79%, and 76%, respectively, other studies reported far inferior adherence to osteoporotic drugs. In 2004, McCombs et al. [7] found that 1-year compliance rate was below 25% in 58,109 patients treated with hormone replacement therapies, BPs, or raloxifene. They also reported 1.32% of osteoporotic fracture (categorized into vertebral, hip, Colles, and other fractures) in a year after raloxifene therapy. In 2007, Kothawala et al. [16] conducted a meta-analysis and reported adherence rates ranging from 34% to 53% in 6 studies. Pooled estimates of adherence rate was 53% in 6 months and decreased to 43% for treatments that lasted 7 to 24 months. The authors concluded that nearly 1/3 to 1/2 of osteoporotic patients were not compliant to medication and that nonadherence starts soon after commencement of therapy. Low adherence to drugs are not only limited to SERM therapy, but it is also observed in other osteoporotic medications.[7,16,26,27] The reported MPR of osteoporotic drugs from 2 meta-analyses range from 67% to 68%,[12,16] which is lower than the suggested optimal level of 80%. This is probably because osteoporosis is asymptomatic before the occurrence of consequent osteoporotic fractures, and the direct benefits are difficult to be recognized by patients.

Low compliance to SERM treatment could be related to its form of administration. Commonly given SERMs in South Korea, namely raloxifene and bazedoxifene, are prescribed in once daily oral form. In previous report by Durden et al. [26], compliance of oral agents (20%–31%) were inferior to compliance of injectable agents (34%–41%) in osteoporosis therapy. Interestingly, the authors reported compliance of raloxifene as 36.6% in 12 months and 28.7% in 24 months. [26] Our findings of low compliance in SERM treatment mostly agree with the previous reports with only minor differences in adherence rates which might be affected by the different threshold of MPR - 66%,[28] 75%,[27] 80%.[7,26] - used to dichotomize the compliant and non-compliant groups. However, approaches to increase the low adherence to osteoporotic medications still require further researches. Kripalani and colleagues [29] conducted a systematic review on diverse measures including behavioral or informative interventions suggested to increase the adherence to drugs for chronic conditions. They reported behavioral interventions increased adherence but only few significantly changed the related clinical outcomes.[29] Even with the effective interventions in similar settings in chronic diseases, methods to increase adherence were reported to lack cost-effectiveness.[30,31]

The osteoporosis fracture risks for the compliant and the non-compliant group were 4.07% and 4.57%, respectively (P=0.21). In 2006, Huybrechts et al. [32] found that only a quarter of the women on osteoporotic drugs are compliant and the low compliance was associated with 17% increase in the fracture rate. This finding was supported by a meta-analysis by Imaz et al. [12], in which they reported the pooled fracture risk was 46% higher in the non-compliant group. In addition, compliant patients are found to experience 16% to 37% less hospitalization in several studies.[32,33] In our study, difference in the fracture risk according to the dichotomized compliance groups did not reach statistical significance. The low compliance to SERMs might, in fact, affect the fracture risk less compared to low compliance in other osteoporotic drugs, especially denosumab. The rebound phenomenon after denosumab discontinuation has been reported to be associated with almost 5-fold higher risk of vertebral, hip, and other osteoporotic fractures.[34,35] Multiple vertebral fractures, or rebound associated vertebral fractures, are specifically increased in patients who discontinue denosumab even compared to those who were not treated for osteoporosis at all.[36] Although similar phenomenon is observed after SERM discontinuation, the bone loss after cessation was not significantly different from the placebo group.[37,38] Idolazzi et al. [39] suggested that after discontinuation, SERM users with low fracture risk should be reassessed after 1 or 2 years without pharmacologic prevention as BP users, while denosumab users should use BPs after cessation.

The risk of osteoporotic fracture was lower in ages of 50 to 60 years and higher in ages over 70 years. It was also related to higher comorbidities represented by higher CCIs in this study. These findings align well with the known risk factors of imminent osteoporotic fractures – previous fractures, low BMD, older age, previous falls, comorbidities that affect physical and cognitive functioning.[4042] In this study, we also evaluated the influence of the level of institutions where the SERMs were prescribed on the subsequent fracture risk, but no significant difference was found. This is in line with the previous reports by Yoon et al. [43] where the knowledge on osteoporosis of prescribers were not related to the level of medical institute. As osteoporotic fracture risk and the knowledge for treatment does not vary among the level of institutions, patients need not be treated from higher level of medical institutions expecting for higher treatment outcomes. Instead, the regular follow-up in clinics and smaller hospitals in the vicinity could be more beneficial.

There are certain limitations in current study. First, difference in osteoporotic fracture risk between 2 groups was marginal in hip and insignificant in other locations. The retrospective sample size analysis on osteoporotic fracture risk in compliant vs. non-compliant group revealed that at least 29,274 patients in each group were required to significantly differentiate between 2 groups (α=0.05, β=0.8). The number of study patients in current study was 11,036 and 4,130 for non-compliant group and compliant group, respectively. When analyzed with the larger population, significant change between 2 groups might be found, especially in hip fractures. Second, data on compliance were derived from claims data involving drug prescription. This approach accompanies the underlying assumption, which patients that fill prescription eventually use the medication. However, patients may not use the drugs prescribed, leading to underestimation or overestimation of the association to fracture risks. Nevertheless, compared to patient self-reported questionnaires where patients might tend to exaggerate the compliance to please physicians, the database-derived approach might have some advantages.[44] Third, data on persistence of the included patients were not available from the database. The notion of adherence usually include both compliance and persistence in numerous studies.[25,45] In further studies, acquiring data on persistence would enable the comparison between adherent group and non-adherent group for more accurate analysis.


Among postmenopausal women with osteoporosis, only 27.2% were compliant to SERM therapy from 2013 to 2014 in South Korea. The overall osteoporotic fracture rate within 2 years of SERM prescription was 4.41%. The difference in hip fracture rate showed marginal difference between non-compliant and compliant group. Older age and more severe comorbidities were related to higher risk of osteoporotic fractures.


This study was supported by Alvogen Korea.


Ethics approval and consent to participate

The approval of the design and protocol of this study was exempted by the Institutional Review Board of our hospital with waived informed consent from all the involved patients as it was a retrospective registry study.

Conflict of interest

Young-Kyun Lee has been the Editor-in-Chief of the Journal of Bone Metabolism since January 1, 2022, but has no role in the decision to publish this article. Except for that, no potential conflict of interest relevant to this article was reported.


1. van Staa TP, Dennison EM, Leufkens HG, et al. Epidemiology of fractures in England and Wales. Bone 2001;29:517–22. https://doi.org/10.1016/s8756-3282(01)00614-7 .
2. Hernlund E, Svedbom A, Ivergård M, et al. Osteoporosis in the European Union: Medical management, epidemiology and economic burden. A report prepared in collaboration with the International Osteoporosis Foundation (IOF) and the European Federation of Pharmaceutical Industry Associations (EFPIA). Arch Osteoporos 2013;8:136. https://doi.org/10.1007/s11657-013-0136-1 .
3. Barrett-Connor E, Mosca L, Collins P, et al. Effects of raloxifene on cardiovascular events and breast cancer in postmenopausal women. N Engl J Med 2006;355:125–37. https://doi.org/10.1056/NEJMoa062462 .
4. Cauley JA, Norton L, Lippman ME, et al. Continued breast cancer risk reduction in postmenopausal women treated with raloxifene: 4-year results from the MORE trial. Multiple outcomes of raloxifene evaluation. Breast Cancer Res Treat 2001;65:125–34. https://doi.org/10.1023/a:1006478317173 .
5. Cummings SR, Ensrud K, Delmas PD, et al. Lasofoxifene in postmenopausal women with osteoporosis. N Engl J Med 2010;362:686–96. https://doi.org/10.1056/NEJMoa0808692 .
6. Silverman SL, Komm BS, Mirkin S. Use of FRAX®-based fracture risk assessments to identify patients who will benefit from osteoporosis therapy. Maturitas 2014;79:241–7. https://doi.org/10.1016/j.maturitas.2014.07.007 .
7. McCombs JS, Thiebaud P, McLaughlin-Miley C, et al. Compliance with drug therapies for the treatment and prevention of osteoporosis. Maturitas 2004;48:271–87. https://doi.org/10.1016/j.maturitas.2004.02.005 .
8. Fardellone P, Lello S, Cano A, et al. Real-world adherence and persistence with bisphosphonate therapy in postmenopausal women: A systematic review. Clin Ther 2019;41:1576–88. https://doi.org/10.1016/j.clinthera.2019.05.001 .
9. Fobelo Lozano MJ, Sánchez-Fidalgo S. Adherence and preference of intravenous zoledronic acid for osteoporosis versus other bisphosphonates. Eur J Hosp Pharm 2019;26:4–9. https://doi.org/10.1136/ejhpharm-2017-001258 .
10. Ko KR, Lee S, Oh SY, et al. Long-term oral bisphosphonate compliance focusing on switching of prescription pattern. Patient Prefer Adherence 2020;14:2009–16. https://doi.org/10.2147/ppa.S266697 .
11. Park CH, Jung KJ, Nho JH, et al. Impact on bisphosphonate persistence and compliance: Daily postprandial administration. J Bone Metab 2019;26:39–44. https://doi.org/10.11005/jbm.2019.26.1.39 .
12. Imaz I, Zegarra P, González-Enríquez J, et al. Poor bisphosphonate adherence for treatment of osteoporosis increases fracture risk: systematic review and meta-analysis. Osteoporos Int 2010;21:1943–51. https://doi.org/10.1007/s00198-009-1134-4 .
13. Akarırmak Ü, Koçyiğit H, Eskiyurt N, et al. Influence of patient training on persistence, compliance, and tolerability of different dosing frequency regimens of bisphosphonate therapy: An observational study in Turkish patients with postmenopausal osteoporosis. Acta Orthop Traumatol Turc 2016;50:415–23. https://doi.org/10.1016/j.aott.2016.07.001 .
14. Kuzmanova SI, Solakov PC, Geneva-Popova MG. Adherence to bisphosphonate therapy in postmenopausal osteoporotic women. Folia Med (Plovdiv) 2011;53:25–31. https://doi.org/10.2478/v10153-011-0053-2 .
15. Ringe JD, Christodoulakos GE, Mellström D, et al. Patient compliance with alendronate, risedronate and raloxifene for the treatment of osteoporosis in postmenopausal women. Curr Med Res Opin 2007;23:2677–87. https://doi.org/10.1185/03007x226357 .
16. Kothawala P, Badamgarav E, Ryu S, et al. Systematic review and meta-analysis of real-world adherence to drug therapy for osteoporosis. Mayo Clin Proc 2007;82:1493–501. https://doi.org/10.1016/s0025-6196(11)61093-8 .
17. Lee S, Yoo JI, Lee YK, et al. Risk of osteoporotic fracture in patients with breast cancer: Meta-analysis. J Bone Metab 2020;27:27–34. https://doi.org/10.11005/jbm.2020.27.1.27 .
18. Shaker JL. Paget’s disease of bone: A review of epidemiology, pathophysiology and management. Ther Adv Musculoskelet Dis 2009;1:107–25. https://doi.org/10.1177/1759720x09351779 .
19. Johansson H, Siggeirsdóttir K, Harvey NC, et al. Imminent risk of fracture after fracture. Osteoporos Int 2017;28:775–80. https://doi.org/10.1007/s00198-016-3868-0 .
20. Mok CC, Ying KY, To CH, et al. Raloxifene for prevention of glucocorticoid-induced bone loss: a 12-month randomised double-blinded placebo-controlled trial. Ann Rheum Dis 2011;70:778–84. https://doi.org/10.1136/ard.2010.143453 .
21. Charlson ME, Pompei P, Ales KL, et al. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis 1987;40:373–83. https://doi.org/10.1016/0021-9681(87)90171-8 .
22. Curtis JR, Mudano AS, Solomon DH, et al. Identification and validation of vertebral compression fractures using administrative claims data. Med Care 2009;47:69–72. https://doi.org/10.1097/MLR.0b013e3181808c05 .
23. Choi S, Han S, Nah S, et al. Effect of ethanol in carbon monoxide poisoning and delayed neurologic sequelae: A prospective observational study. PLoS One 2021;:16. https://doi.org/10.1371/journal.pone.0245265 .
24. Jung HS, Nho JH, Ha YC, et al. Incidence of osteoporotic refractures following proximal humerus fractures in adults aged 50 years and older in Korea. J Bone Metab 2019;26:105–11. https://doi.org/10.11005/jbm.2019.26.2.105 .
25. Cramer JA, Roy A, Burrell A, et al. Medication compliance and persistence: terminology and definitions. Value Health 2008;11:44–7. https://doi.org/10.1111/j.1524-4733.2007.00213.x .
26. Durden E, Pinto L, Lopez-Gonzalez L, et al. Two-year persistence and compliance with osteoporosis therapies among postmenopausal women in a commercially insured population in the United States. Arch Osteoporos 2017;12:22. https://doi.org/10.1007/s11657-017-0316-5 .
27. Faulkner DL, Young C, Hutchins D, et al. Patient noncompliance with hormone replacement therapy: a nationwide estimate using a large prescription claims database. Menopause 1998;5:226–9.
28. Yood RA, Emani S, Reed JI, et al. Compliance with pharmacologic therapy for osteoporosis. Osteoporos Int 2003;14:965–8. https://doi.org/10.1007/s00198-003-1502-4 .
29. Kripalani S, Yao X, Haynes RB. Interventions to enhance medication adherence in chronic medical conditions: a systematic review. Arch Intern Med 2007;167:540–50. https://doi.org/10.1001/archinte.167.6.540 .
30. Bosmans JE, Brook OH, van Hout HP, et al. Cost effectiveness of a pharmacy-based coaching programme to improve adherence to antidepressants. Pharmacoeconomics 2007;25:25–37. https://doi.org/10.2165/00019053-200725010-00004 .
31. Brunenberg DE, Wetzels GE, Nelemans PJ, et al. Cost effectiveness of an adherence-improving programme in hypertensive patients. Pharmacoeconomics 2007;25:239–51. https://doi.org/10.2165/00019053-200725030-00006 .
32. Huybrechts KF, Ishak KJ, Caro JJ. Assessment of compliance with osteoporosis treatment and its consequences in a managed care population. Bone 2006;38:922–8. https://doi.org/10.1016/j.bone.2005.10.022 .
33. Caro JJ, Ishak KJ, Huybrechts KF, et al. The impact of compliance with osteoporosis therapy on fracture rates in actual practice. Osteoporos Int 2004;15:1003–8. https://doi.org/10.1007/s00198-004-1652-z .
34. Lyu H, Yoshida K, Zhao SS, et al. Delayed denosumab injections and fracture risk among patients with osteoporosis : A population-based cohort study. Ann Intern Med 2020;173:516–26. https://doi.org/10.7326/m20-0882 .
35. Tripto-Shkolnik L, Fund N, Rouach V, et al. Fracture incidence after denosumab discontinuation: Real-world data from a large healthcare provider. Bone 2020;130:115150. https://doi.org/10.1016/j.bone.2019.115150 .
36. Cummings SR, Ferrari S, Eastell R, et al. Vertebral fractures after discontinuation of denosumab: A post hoc analysis of the randomized placebo-controlled FREEDOM trial and its extension. J Bone Miner Res 2018;33:190–8. https://doi.org/10.1002/jbmr.3337 .
37. An KC. Selective estrogen receptor modulators. Asian Spine J 2016;10:787–91. https://doi.org/10.4184/asj.2016.10.4.787 .
38. Neele SJ, Evertz R, De Valk-De Roo G, et al. Effect of 1 year of discontinuation of raloxifene or estrogen therapy on bone mineral density after 5 years of treatment in healthy postmenopausal women. Bone 2002;30:599–603. https://doi.org/10.1016/s8756-3282(01)00706-2 .
39. Idolazzi L, Fassio A, Gatti D, et al. Duration of treatment for osteoporosis. Reumatismo 2013;65:22–35. https://doi.org/10.4081/reumatismo.2013.22 .
40. Barron RL, Oster G, Grauer A, et al. Determinants of imminent fracture risk in postmenopausal women with osteoporosis. Osteoporos Int 2020;31:2103–11. https://doi.org/10.1007/s00198-020-05294-3 .
41. Bonafede M, Shi N, Barron R, et al. Predicting imminent risk for fracture in patients aged 50 or older with osteoporosis using US claims data. Arch Osteoporos 2016;11:26. https://doi.org/10.1007/s11657-016-0280-5 .
42. Pinedo-Villanueva R, Charokopou M, Toth E, et al. Imminent fracture risk assessments in the UK FLS setting: implications and challenges. Arch Osteoporos 2019;14:12. https://doi.org/10.1007/s11657-019-0569-2 .
43. Yoon BH, Baek JH, Lee YK, et al. Knowledge on osteoporosis of prescriber according to level of medical institute. Yonsei Med J 2014;55:1058–62. https://doi.org/10.3349/ymj.2014.55.4.1058 .
44. Steiner JF, Prochazka AV. The assessment of refill compliance using pharmacy records: methods, validity, and applications. J Clin Epidemiol 1997;50:105–16. https://doi.org/10.1016/s0895-4356(96)00268-5 .
45. Osterberg L, Blaschke T. Adherence to medication. N Engl J Med 2005;353:487–97. https://doi.org/10.1056/NEJMra050100 .

Article information Continued

Fig. 1

Flowchart of included patients. SERMs, selective estrogen receptor modulators.

Table 1

Patient characteristics of compliant and non-compliant group

Characteristics Non-compliant group (N=11,036) Compliant group (N=4,130) P-value
Age (yr) <0.001
 50–54 961 (8.7) 394 (9.5)
 55–59 1,673 (15.2) 673 (16.3)
 60–64 1,951 (17.7) 765 (18.5)
 65–69 2,313 (21.0) 906 (21.9)
 70–74 1,884 (17.1) 681 (16.5)
 75–79 1,454 (13.2) 437 (10.6)
 ≥80 800 (7.2) 274 (6.6)

Institutions <0.001
 Tertiary hospital 1,292 (11.7) 881 (21.3)
 General hospital 3,012 (27.3) 1,179 (28.5)
 Hospital 2,834 (25.7) 763 (18.5)
 Clinic 3,898 (35.3) 1,307 (31.6)

CCI 0.722
 0 6,292 (57.0) 2,347 (56.8)
 1 3,235 (29.3) 1,191 (28.8)
 2 1,004 (9.1) 389 (9.4)
 ≥3 505 (4.6) 203 (4.9)

CCI, Charlson’s comorbidity index.

Table 2

Osteoporotic fractures after selective estrogen receptor modulator treatment

Location Non-compliant group (N=11,036) Compliant group (N=4,130) P-value
Hip (N=58) 43 (0.4) 15 (0.4) 0.06
Spine (N=437) 331 (3.0) 106 (2.6) 0.16
Distal radius (N=143) 104 (0.9) 39 (0.9) 0.99
Proximal humerus (N=31) 23 (0.2) 8 (0.2) 0.86
Total (N=669) 501 (4.5) 168 (4.1) 0.21

Table 3

Multivariable Cox proportional hazard model of baseline characteristics for osteoporotic fractures

Baseline characteristics HR (95% CI) P-value
Compliant group (MPR ≥80) compared to non-compliant group (MPR<80) 0.93 (0.781–1.108) 0.4183

Age group with age 50–54 years as reference
 Age 55–59 years 0.57 (0.379–0.857) 0.007
 Age 60–64 years 0.858 (0.601–1.226) 0.4007
 Age 65–69 years 1.088 (0.781–1.516) 0.6189
 Age 70–74 years 2.035 (1.485–2.789) <0.0001
 Age 75–79 years 2.197 (1.588–3.041) <0.0001
 Age ≥80 years 3.53 (2.493–4.999) <0.0001

Type of institution with tertiary hospital as reference
 General hospital 0.918 (0.375–2.246) 0.8509
 Hospital 1.053 (0.433–2.561) 0.9098
 Clinic 0.984 (0.407–2.38) 0.9721

CCI with CCI 0 as reference
 CCI 1 1.29 (1.088–1.53) 0.0034
 CCI 2 1.286 (1.002–1.652) 0.0486
 CCI ≥3 1.31 (0.953–1.801) 0.0967

MRP, medication possession ratio; HR, hazard ratio; CI, confidence interval.