Abstract
Summary
Premenopausal bone loss increases fracture risk later in life. Depending on peak values, varying degrees of bone mass and microarchitectural loss can be tolerated. We suggest that risk-benefit assessments of drugs that cause premenopausal bone loss be individualized considering baseline status and subsequent BMD and TBS loss.
Introduction
It is logical that drug-induced loss of bone mass and microarchitecture in young adults increase fracture risk later in life. However, no existing data quantify how drug-induced bone loss in younger adults impacts fracture risk later in life. As such, no guidance exists to address the question “How much, if any, drug-induced bone loss in premenopausal women is acceptable?” Thus, we performed a systematic fracture risk modeling exercise examining various degrees of bone loss, and estimated the impact on 10-year major osteoporosis-related fracture risk later in life.
Methods
The FRAX® tool was used in conjunction with BMD and trabecular bone score (TBS) adjustment to estimate major osteoporotic fracture probability later in life resulting from varying degrees of hypothetical premenopausal drug-induced BMD and TBS loss. The resulting 10-year fracture probabilities were assessed against the US and the UK treatment guidance to determine the amount of premenopausal BMD and TBS loss that would result in a recommendation to initiate medical treatment to reduce fracture risk later in life that would not otherwise have been recommended in the absence of premenopausal bone loss.
Results
For women whose peak bone mass is between the 5th and 50th percentiles, varying degrees of BMD and TBS loss could be tolerated without reaching treatment thresholds. The degree of tolerable bone loss was primarily dependent on baseline bone status. Those whose peak BMD and TBS are in the 50th percentile or above could tolerate a 10% reduction in BMD and TBS without reaching treatment thresholds by age 75, whereas those in the 5th percentile would reach treatment thresholds by age 75 with no drug-induced reduction in BMD or TBS. Women in the 25th percentile could tolerate a 4% BMD loss and 2% TBS decline without reaching treatment thresholds by age 75.
Conclusions
For clinicians and regulatory bodies to assess the consequence of drug-induced premenopausal bone loss, we propose an individualized approach considering both loss of BMD and TBS in concert with baseline bone status and the resultant effect on fracture risk in later life using the assumption that such losses are irreversible.
References
Consensus development conference: diagnosis, prophylaxis, and treatment of osteoporosis (1993) Am J Med 94(6):646–650
Kanis JA, Johansson H, Oden A, Johnell O, de Laet C, Melton IL, Tenenhouse A, Reeve J, Silman AJ, Pols HA, Eisman JA, McCloskey EV, Mellstrom D (2004) A meta-analysis of prior corticosteroid use and fracture risk. J Bone Miner Res 19(6):893–899. https://doi.org/10.1359/jbmr.040134
Dawood MY, Ramos J, Khan-Dawood FS (1995) Depot leuprolide acetate versus danazol for treatment of pelvic endometriosis: changes in vertebral bone mass and serum estradiol and calcitonin. Fertil Steril 63(6):1177–1183
Briot K, Kolta S, Flandre P, Boue F, Ngo Van P, Cohen-Codar I, Norton M, Delfraissy JF, Roux C (2011) Prospective one-year bone loss in treatment-naive HIV+ men and women on single or multiple drug HIV therapies. Bone 48(5):1133–1139. https://doi.org/10.1016/j.bone.2011.01.015
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(10):2359–2381. https://doi.org/10.1007/s00198-014-2794-2
Kanis JA, McCloskey EV, Johansson H, Cooper C, Rizzoli R, Reginster JY (2013) European guidance for the diagnosis and management of osteoporosis in postmenopausal women. Osteoporos Int 24(1):23–57. https://doi.org/10.1007/s00198-012-2074-y
Silva BC, Leslie WD, Resch H, Lamy O, Lesnyak O, Binkley N, McCloskey EV, Kanis JA, Bilezikian JP (2014) Trabecular bone score: a noninvasive analytical method based upon the DXA image. J Bone Miner Res 29(3):518–530. https://doi.org/10.1002/jbmr.2176
Muschitz C, Kocijan R, Haschka J, Pahr D, Kaider A, Pietschmann P, Hans D, Muschitz GK, Fahrleitner-Pammer A, Resch H (2015) TBS reflects trabecular microarchitecture in premenopausal women and men with idiopathic osteoporosis and low-traumatic fractures. Bone 79:259–266. https://doi.org/10.1016/j.bone.2015.06.007
Harvey NC, Gluer CC, Binkley N, McCloskey EV, Brandi ML, Cooper C, Kendler D, Lamy O, Laslop A, Camargos BM, Reginster JY, Rizzoli R, Kanis JA (2015) Trabecular bone score (TBS) as a new complementary approach for osteoporosis evaluation in clinical practice. Bone 78:216–224. https://doi.org/10.1016/j.bone.2015.05.016
Silva BC, Broy SB, Boutroy S, Schousboe JT, Shepherd JA, Leslie WD (2015) Fracture risk prediction by non-BMD DXA measures: the 2015 ISCD official positions part 2: trabecular bone score. J Clin Densitom 18(3):309–330. https://doi.org/10.1016/j.jocd.2015.06.008
McCloskey EV, Oden A, Harvey NC, Leslie WD, Hans D, Johansson H, Barkmann R, Boutroy S, Brown J, Chapurlat R, Elders PJ, Fujita Y, Gluer CC, Goltzman D, Iki M, Karlsson M, Kindmark A, Kotowicz M, Kurumatani N, Kwok T, Lamy O, Leung J, Lippuner K, Ljunggren O, Lorentzon M, Mellstrom D, Merlijn T, Oei L, Ohlsson C, Pasco JA, Rivadeneira F, Rosengren B, Sornay-Rendu E, Szulc P, Tamaki J, Kanis JA (2016) A meta-analysis of trabecular bone score in fracture risk prediction and its relationship to FRAX. J Bone Miner Res 31(5):940–948. https://doi.org/10.1002/jbmr.2734
McCloskey EV, Oden A, Harvey NC, Leslie WD, Hans D, Johansson H, Kanis JA (2015) Adjusting fracture probability by trabecular bone score. Calcif Tissue Int 96(6):500–509. https://doi.org/10.1007/s00223-015-9980-x
Fryar CD, Gu Q, Ogden CL (2012) Anthropometric reference data for children and adults: United States, 2007–2010. Vital Health Stat 11(252):1–48
Looker AC, Borrud LG, Hughes JP, Fan B, Shepherd JA, Melton LJ 3rd (2012) Lumbar spine and proximal femur bone mineral density, bone mineral content, and bone area: United States, 2005–2008. Vital Health Stat 11(251):1–132
Compston J, Bowring C, Cooper A, Cooper C, Davies C, Francis R, Kanis JA, Marsh D, McCloskey EV, Reid DM, Selby P, National Osteoporosis Guideline G (2013) Diagnosis and management of osteoporosis in postmenopausal women and older men in the UK: National Osteoporosis Guideline Group (NOGG) update 2013. Maturitas 75(4):392–396. https://doi.org/10.1016/j.maturitas.2013.05.013
Assessment of fracture risk and its application to screening for postmenopausal osteoporosis. Report of a WHO Study Group (1994) World Health Organ Tech Rep Ser 843:1–129
Kanis JA, Johnell O, Oden A, Dawson A, De Laet C, Jonsson B (2001) Ten year probabilities of osteoporotic fractures according to BMD and diagnostic thresholds. Osteoporos Int 12(12):989–995. https://doi.org/10.1007/s001980170006
Kanis JA, Harvey NC, Cooper C, Johansson H, Oden A, EV MC, Advisory Board of the National Osteoporosis Guideline G (2016) A systematic review of intervention thresholds based on FRAX : a report prepared for the National Osteoporosis Guideline Group and the International Osteoporosis Foundation. Arch Osteoporos 11(1):25. https://doi.org/10.1007/s11657-016-0278-z
McCloskey E, Kanis JA, Johansson H, Harvey N, Oden A, Cooper A, Cooper C, Francis RM, Reid DM, Marsh D, Selby P, Thompson F, Hewitt S, Compston J (2015) FRAX-based assessment and intervention thresholds—an exploration of thresholds in women aged 50 years and older in the UK. Osteoporos Int 26(8):2091–2099. https://doi.org/10.1007/s00198-015-3176-0
Acknowledgments
The authors acknowledge medical writing support provided by Succinct Choice Medical Communications (Chicago, IL) and funded by Astellas Pharma Inc. Authors’ roles: Study design: NB, RB, TF, LS, and DH. Study conduct: NB, RB, TF, LS, DH. Data collection: RB and DH. Data analysis: NB, RB, TF, LS, DH. Data interpretation: NB, RB, TF, LS, DH. Drafting manuscript: NB, RB, TF, LS, DH. Revising manuscript content: NB, RB, TF, LS, DH. Approving final version of manuscript: NB, RB, TF, LS, DH. Takes responsibility for the integrity of the data analysis: NB, RB, TF, LS, DH.
Funding
No funding was provided for this research; medical writing support was provided by Succinct Choice Medical Communications (Chicago, IL) and funded by Astellas Pharma Inc.
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Neil Binkley declares no conflict of interest. Robin Besuyen is a contractor assigned to Astellas projects. Thomas Fuerst is an employee of Bioclinica, Inc. and provides central reading services, including those related to bone mineral density monitoring. Laurence Skillern is an employee of Astellas. Didier Hans is co-owner of the TBS patent and has corresponding ownership shares and position in Medimaps Group and reports fees from Astellas to Medimaps Group for TBS central analysis during the conduct of the study.
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This article does not contain studies with human participants or animals by any of the authors.
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Binkley, N., Besuyen, R., Fuerst, T. et al. Is drug-induced bone loss acceptable in premenopausal women? A practical fracture risk modeling exercise. Osteoporos Int 28, 3501–3513 (2017). https://doi.org/10.1007/s00198-017-4258-y
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DOI: https://doi.org/10.1007/s00198-017-4258-y