Using the FRAX® model for India, thresholds for osteoporosis evaluation and treatment without bone mineral density measurement were derived and were validated in a cohort of 300 patients. We suggest the use of this newer age and ethnic-specific FRAX®-derived thresholds for management of osteoporosis in India. PURPOSE: Our study aimed to formulate population-specific intervention thresholds for treatment of osteoporosis in India which can be used even without dual X-ray absorptiometry (DXA). METHODS: Using the FRAX® model for India, thresholds for different age groups for men and women were calculated without bone mineral density (BMD) measurement. The lower assessment threshold (LAT) was based on the 10-year probability of a major osteoporosis fracture (MOF) or hip fracture (HF) equivalent to patients without clinical risk factors. The intervention threshold (IT) was based on the 10-year probability equivalent to patients with fracture. The upper assessment threshold (UAT) was set at 1.2 times the IT. Probability-based thresholds for no intervention (LAT), treatment initiation (UAT) and BMD assessment (between LAT and UAT) were derived. The thresholds were validated in a cohort of 300 patients who were referred for BMD testing. RESULTS: Graphs for age, gender, BMI and ethnic-specific LAT, IT and UAT for MOF and HF are derived. In the validation cohort, BMD testing to initiate/defer treatment was required in only 32.3% patients. The intervention thresholds derived without BMD testing were valid in 98.7% patients. Use of National Osteoporosis Foundation (NOF) guidelines would have resulted in overtreatment in 56/300 (18.6%) patients. CONCLUSION: We suggest the use of this newer age and ethnic-specific FRAX®-derived thresholds for management of osteoporosis. Adopting these cut-offs will ensure that those requiring osteoporosis treatment will not be denied of it just because of lack of a DXA machine and will also help avoid overtreatment.
Using the FRAX® model for India, thresholds for osteoporosis evaluation and treatment without bone mineral density measurement were derived and were validated in a cohort of 300 patients. We suggest the use of this newer age and ethnic-specific FRAX®-derived thresholds for management of osteoporosis in India. PURPOSE: Our study aimed to formulate population-specific intervention thresholds for treatment of osteoporosis in India which can be used even without dual X-ray absorptiometry (DXA). METHODS: Using the FRAX® model for India, thresholds for different age groups for men and women were calculated without bone mineral density (BMD) measurement. The lower assessment threshold (LAT) was based on the 10-year probability of a major osteoporosis fracture (MOF) or hip fracture (HF) equivalent to patients without clinical risk factors. The intervention threshold (IT) was based on the 10-year probability equivalent to patients with fracture. The upper assessment threshold (UAT) was set at 1.2 times the IT. Probability-based thresholds for no intervention (LAT), treatment initiation (UAT) and BMD assessment (between LAT and UAT) were derived. The thresholds were validated in a cohort of 300 patients who were referred for BMD testing. RESULTS: Graphs for age, gender, BMI and ethnic-specific LAT, IT and UAT for MOF and HF are derived. In the validation cohort, BMD testing to initiate/defer treatment was required in only 32.3% patients. The intervention thresholds derived without BMD testing were valid in 98.7% patients. Use of National Osteoporosis Foundation (NOF) guidelines would have resulted in overtreatment in 56/300 (18.6%) patients. CONCLUSION: We suggest the use of this newer age and ethnic-specific FRAX®-derived thresholds for management of osteoporosis. Adopting these cut-offs will ensure that those requiring osteoporosis treatment will not be denied of it just because of lack of a DXA machine and will also help avoid overtreatment.
Authors: Alexander Melamed; Eric Vittinghoff; Usha Sriram; Ann V Schwartz; Alka M Kanaya Journal: J Clin Densitom Date: 2010-07-21 Impact factor: 2.617
Authors: A N A Tosteson; L J Melton; B Dawson-Hughes; S Baim; M J Favus; S Khosla; R L Lindsay Journal: Osteoporos Int Date: 2008-02-22 Impact factor: 4.507
Authors: Georgios Kyriakos; Alfonso Vidal-Casariego; María Nélida Fernández-Martínez; María Dolores Blanco-Suárez; María D Ballesteros-Pomar; Isidoro Cano-Rodríguez Journal: J Clin Densitom Date: 2015-09-03 Impact factor: 2.617
Authors: E McCloskey; J A Kanis; H Johansson; N Harvey; A Odén; A Cooper; C Cooper; R M Francis; D M Reid; D Marsh; P Selby; F Thompson; S Hewitt; J Compston Journal: Osteoporos Int Date: 2015-06-16 Impact factor: 4.507