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Disparities in osteoporosis treatments

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Abstract

Summary

Osteoporosis treatment rates within 2 years following an index event (fragility fracture, osteoporotic bone mineral density (BMD) T-score, or osteoporosis ICD-9 codes) were determined from 2005 to 2011. Most patients were not treated. Fracture patients had the lowest treatment rate. Low treatment rates also occurred in patients that were male, black, or had non-commercial insurance.

Introduction

Clinical recognition of osteoporosis (osteoporotic BMD, assignment of an ICD-9 code, or the occurrence of fragility fractures) provides opportunities to treat patients at risk for future fracture.

Methods

A cohort of 36,965 patients was identified from 2005 to 2011 in the Indiana Health Information Exchange, with index events after age 50 of either non-traumatic fractures, an osteoporosis ICD-9 code, or a BMD T-score ≤ −2.5. Patients with osteoporosis treatment in the preceding year were excluded. Medication records during the ensuing 2 years were extracted to identify osteoporosis treatments, demographics, comorbidities, and co-medications. Predictors of treatment were evaluated in a multivariable logistic regression model.

Results

The cohort was 78 % female, 11 % black, 91 % urban-dwelling, and 53 % commercially insured. The index events were as follows: osteoporosis diagnosis (47 % of patients), fragility fracture (44 %), and osteoporotic T-scores (9 %). Within 2 years after the index event, 23.3 % received osteoporosis medications (of which, 82.2 % were oral bisphosphonates). Treatment rates were higher after osteoporosis diagnosis codes (29.3 %) or osteoporotic T-score (53.9 %) than after fracture index events (10.5 %) (p < 0.001). Age had an inverted U-shaped effect for women with highest odds around 60–65 years. Women (OR 1.86) and non-black patients (OR 1.52) were more likely to be treated (p < 0.001). Patients with public (versus commercial) insurance (OR 0.86, p < 0.001) or chronic comorbidities (ORs about 0.7–0.9, p < 0.001) were less likely to be treated.

Conclusion

Most osteoporosis treatment candidates remained untreated. Men, black patients, and patients with fracture or chronic comorbidities were less likely to receive treatment, representing disparity in the recognition and treatment of osteoporosis.

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References

  1. Wright NC, Looker AC, Saag KG, Curtis JR, Delzell ES, Randall S, Dawson-Hughes B (2014) The recent prevalence of osteoporosis and low bone mass in the United States based on bone mineral density at the femoral neck or lumbar spine. J Bone Miner Res :Off J Am Soc Bone Miner Res 29:2520–2526

    Article  Google Scholar 

  2. Stevens JA, Rudd RA (2013) The impact of decreasing U.S. hip fracture rates on future hip fracture estimates. Osteoporos Int : J Estab Result Coop Between European Found Osteoporos Natl Osteoporos Found USA 24:2725–2728

    Article  CAS  Google Scholar 

  3. Burge R, Dawson-Hughes B, Solomon DH, Wong JB, King A, Tosteson A (2007) Incidence and economic burden of osteoporosis-related fractures in the United States, 2005–2025. J Bone Miner Res : Official J Am Soc Bone Miner Res 22:465–475

    Article  Google Scholar 

  4. Solomon DH, Johnston SS, Boytsov NN, McMorrow D, Lane JM, Krohn KD (2014) Osteoporosis medication use after hip fracture in U.S. patients between 2002 and 2011. J Bone Miner Res : Off J Am Soc Bone Miner Res 29:1929–1937

    Article  Google Scholar 

  5. Colon-Emeric C, Lyles KW, Levine DA et al (2007) Prevalence and predictors of osteoporosis treatment in nursing home residents with known osteoporosis or recent fracture. Osteoporos Int : J Estab Result Coop Between European Found Osteoporos Natl Osteoporos Found USA 18:553–559

    Article  CAS  Google Scholar 

  6. Parikh S, Mogun H, Avorn J, Solomon DH (2008) Osteoporosis medication use in nursing home patients with fractures in 1 US state. Arch Intern Med 168:1111–1115

    Article  PubMed  Google Scholar 

  7. Bessette L, Jean S, Davison KS, Roy S, Ste-Marie LG, Brown JP (2009) Factors influencing the treatment of osteoporosis following fragility fracture. Osteoporos Int : J Estab Result Coop Between European Found Osteoporos Natl Osteoporos Found USA 20:1911–1919

    Article  CAS  Google Scholar 

  8. McGowan BM, Bennett K, Marry J, Walsh JB, Casey MC (2011) Primary-care prescribing of anti-osteoporotic-type medications following hospitalisation for fractures. Eur J Clin Pharmacol 67:301–308

    Article  CAS  PubMed  Google Scholar 

  9. Greenspan SL, Wyman A, Hooven FH et al (2012) Predictors of treatment with osteoporosis medications after recent fragility fractures in a multinational cohort of postmenopausal women. J Am Geriatr Soc 60:455–461

    Article  PubMed Central  PubMed  Google Scholar 

  10. Beaton DE, Dyer S, Jiang D, Sujic R, Slater M, Sale JE, Bogoch ER, Osteoporosis Fracture Clinic Screening Program Evaluation T (2014) Factors influencing the pharmacological management of osteoporosis after fragility fracture: results from the Ontario Osteoporosis Strategy’s fracture clinic screening program. Osteoporos Int : J Estab Result Coop Between European Found Osteoporos Natl Osteoporos Found USA 25:289–296

    Article  CAS  Google Scholar 

  11. Giangregorio L, Papaioannou A, Cranney A, Zytaruk N, Adachi JD (2006) Fragility fractures and the osteoporosis care gap: an international phenomenon. Semin Arthritis Rheum 35:293–305

    Article  CAS  PubMed  Google Scholar 

  12. Jennings LA, Auerbach AD, Maselli J, Pekow PS, Lindenauer PK, Lee SJ (2010) Missed opportunities for osteoporosis treatment in patients hospitalized for hip fracture. J Am Geriatr Soc 58:650–657

    Article  PubMed Central  PubMed  Google Scholar 

  13. Kung AW, Fan T, Xu L et al (2013) Factors influencing diagnosis and treatment of osteoporosis after a fragility fracture among postmenopausal women in Asian countries: a retrospective study. BMC Womens health 13:7

    Article  PubMed Central  PubMed  Google Scholar 

  14. Jean S, Candas B, Belzile E, Morin S, Bessette L, Dodin S, Brown JP (2012) Algorithms can be used to identify fragility fracture cases in physician-claims databases. Osteoporos Int 23:483–501

    Article  CAS  PubMed  Google Scholar 

  15. Lix LM, Azimaee M, Osman BA, Caetano P, Morin S, Metge C, Goltzman D, Kreiger N, Prior J, Leslie WD (2012) Osteoporosis-related fracture case definitions for population-based administrative data. Bmc Public Health 12:

  16. Curtis JR, Mudano AS, Solomon DH, Xi J, Melton E, Saag KG (2009) Identification and validation of vertebral compression fractures using administrative claims data. Med Care 47:69–72

    Article  PubMed Central  PubMed  Google Scholar 

  17. Charlson ME, Pompei P, Ales KL, MacKenzie CR (1987) A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis 40:373–383

    Article  CAS  PubMed  Google Scholar 

  18. MacLean C, Newberry S, Maglione M et al (2008) Systematic review: comparative effectiveness of treatments to prevent fractures in men and women with low bone density or osteoporosis. Ann Intern Med 148:197–213

    Article  PubMed  Google Scholar 

  19. Grossman JM, Gordon R, Ranganath VK et al (2010) American College of Rheumatology 2010 recommendations for the prevention and treatment of glucocorticoid-induced osteoporosis. Arthritis Care Res 62:1515–1526

    Article  Google Scholar 

  20. Cosman F, de Beur SJ, LeBoff MS, Lewiecki EM, Tanner B, Randall S, Lindsay R (2014) Clinician’s guide to prevention and treatment of osteoporosis. Osteoporos Int 25:2359–2381

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  21. Diez-Perez A, Hooven FH, Adachi JD et al (2011) Regional differences in treatment for osteoporosis. The global longitudinal study of osteoporosis in women (GLOW). Bone 49:493–498

    Article  PubMed  Google Scholar 

  22. Antonelli M, Einstadter D, Magrey M (2014) Screening and treatment of osteoporosis after hip fracture: comparison of sex and race. J Clin Densitom 17:479–483

    Article  PubMed  Google Scholar 

  23. Shibli-Rahhal A, Vaughan-Sarrazin MS, Richardson K, Cram P (2011) Testing and treatment for osteoporosis following hip fracture in an integrated US healthcare delivery system. Osteoporos Int 22:2973–2980

    Article  CAS  PubMed  Google Scholar 

  24. Harper CM, Fitzpatrick SK, Zurakowski D, Rozental TD (2014) Distal radial fractures in older men. A missed opportunity? J Bone Joint Surg Am 96:1820–1827

    Article  PubMed  Google Scholar 

  25. Cunningham TD, Di Pace BS, Ullal J (2014) Osteoporosis treatment disparities: a 6-year aggregate analysis from national survey data. Osteoporos Int 25:2199–2208

    Article  CAS  PubMed  Google Scholar 

  26. Wright NC, Saag KG, Curtis JR, Smith WK, Kilgore ML, Morrisey MA, Yun H, Zhang J, Delzell ES (2012) Recent trends in hip fracture rates by race/ethnicity among older US adults. J Bone Min Res : Off J Am Soc Bone Miner Res 27:2325–2332

    Article  Google Scholar 

  27. Halpern R, Becker L, Iqbal SU, Kazis LE, Macarios D, Badamgarav E (2011) The association of adherence to osteoporosis therapies with fracture, all-cause medical costs, and all-cause hospitalizations: a retrospective claims analysis of female health plan enrollees with osteoporosis. J Manag Care pharm 17:25–39

    PubMed  Google Scholar 

  28. Armstrong ME, Cairns BJ, Banks E, Green J, Reeves GK, Beral V, Million Women Study C (2012) Different effects of age, adiposity and physical activity on the risk of ankle, wrist and hip fractures in postmenopausal women. Bone 50:1394–1400

    Article  PubMed Central  PubMed  Google Scholar 

  29. Moura C, Bernatsky S, Abrahamowicz M et al (2014) Antidepressant use and 10-year incident fracture risk: the population-based Canadian multicentre osteoporosis study (CaMoS). Osteoporos Int : J Established Result Coop Between European Found Osteoporos Natl Osteoporos Found USA 25:1473–1481

    Article  CAS  Google Scholar 

  30. Mazziotti G, Canalis E, Giustina A (2010) Drug-induced osteoporosis: mechanisms and clinical implications. Am J Med 123:877–884

    Article  CAS  PubMed  Google Scholar 

  31. Osteoporosis testing and management in older women. National Committee for Quality Assurance (NCQA). http://www.ncqa.org/ReportCards/HealthPlans/StateofHealthCareQuality/2014TableofContents/Osteoporosis.aspx

  32. Wysowski DK, Greene P (2013) Trends in osteoporosis treatment with oral and intravenous bisphosphonates in the United States, 2002–2012. Bone 57:423–428

    Article  CAS  PubMed  Google Scholar 

  33. Reid IR (Accepted) Efficacy, effectiveness and side effects of medications used to prevent fractures. Journal of Internal Medicine

  34. Marx RE (2003) Pamidronate (Aredia) and zoledronate (Zometa) induced avascular necrosis of the jaws: a growing epidemic. J Oral Maxillofac Surg : Off J Am Assoc Oral Maxillofac Surgeons 61:1115–1117

    Article  Google Scholar 

  35. Shane E, Burr D, Ebeling PR et al (2010) Atypical subtrochanteric and diaphyseal femoral fractures: report of a task force of the American Society for Bone and Mineral Research. J Bone Min Res : Off J Am Soc Bone Min Res 25:2267–2294

    Article  Google Scholar 

  36. Neuner JM, Schapira MM (2014) Patient perceptions of osteoporosis treatment thresholds. J Rheumatol 41:516–522

    Article  PubMed Central  PubMed  Google Scholar 

Download references

Funding source

This research was funded by a grant under the Merck-Regenstrief Program in Personalized Health Care Research and Innovation, a collaboration between Merck, Sharp & Dohme and the Regenstrief Institute.

Conflicts of interest

ZL, SH, and EAI have received research funding from Merck, Sharpe & Dohme. JW and AdP are employed by Merck, Sharpe & Dohme. Zhuokai Li, Joel Martin, and Katie Allen declare that they have no conflict of interest.

Author information

Authors and Affiliations

  1. Department of Biostatistics, Indiana University Schools of Medicine and Public Health, Health Information and Translational Sciences Building, 410 W 10th Street, Suite 3000, Indianapolis, IN, 46202-5111, USA

    Z. Liu

  2. Merck & Co, Whitehouse Station, New Jersey, NJ, 08889, USA

    J. Weaver & A. de Papp

  3. Duke Clinical Research Institute, Duke University School of Medicine, Durham, NC, USA

    Z. Li

  4. Regenstrief Institute, Indianapolis, IN, USA

    J. Martin, K. Allen & S. Hui

  5. Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, USA

    E. A. Imel

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  1. Z. Liu
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  2. J. Weaver
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  3. A. de Papp
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  4. Z. Li
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  7. S. Hui
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Correspondence to Z. Liu.

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Liu, Z., Weaver, J., de Papp, A. et al. Disparities in osteoporosis treatments. Osteoporos Int 27, 509–519 (2016). https://doi.org/10.1007/s00198-015-3249-0

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  • DOI: https://doi.org/10.1007/s00198-015-3249-0

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