S Nayak1, D L Edwards, A A Saleh, S L Greenspan. 1. Swedish Center for Research and Innovation, Swedish Health Services, Swedish Medical Center, 747 Broadway, Seattle, WA, 98122-4307, USA, smita.nayak@swedish.org.
Abstract
UNLABELLED: We performed a systematic review and meta-analysis of the performance of clinical risk assessment instruments for screening for DXA-determined osteoporosis or low bone density. Commonly evaluated risk instruments showed high sensitivity approaching or exceeding 90% at particular thresholds within various populations but low specificity at thresholds required for high sensitivity. Simpler instruments, such as OST, generally performed as well as or better than more complex instruments. INTRODUCTION: The purpose of the study is to systematically review the performance of clinical risk assessment instruments for screening for dual-energy X-ray absorptiometry (DXA)-determined osteoporosis or low bone density. METHODS: Systematic review and meta-analysis were performed. Multiple literature sources were searched, and data extracted and analyzed from included references. RESULTS: One hundred eight references met inclusion criteria. Studies assessed many instruments in 34 countries, most commonly the Osteoporosis Self-Assessment Tool (OST), the Simple Calculated Osteoporosis Risk Estimation (SCORE) instrument, the Osteoporosis Self-Assessment Tool for Asians (OSTA), the Osteoporosis Risk Assessment Instrument (ORAI), and body weight criteria. Meta-analyses of studies evaluating OST using a cutoff threshold of <1 to identify US postmenopausal women with osteoporosis at the femoral neck provided summary sensitivity and specificity estimates of 89% (95%CI 82-96%) and 41% (95%CI 23-59%), respectively. Meta-analyses of studies evaluating OST using a cutoff threshold of 3 to identify US men with osteoporosis at the femoral neck, total hip, or lumbar spine provided summary sensitivity and specificity estimates of 88% (95%CI 79-97%) and 55% (95%CI 42-68%), respectively. Frequently evaluated instruments each had thresholds and populations for which sensitivity for osteoporosis or low bone mass detection approached or exceeded 90% but always with a trade-off of relatively low specificity. CONCLUSIONS: Commonly evaluated clinical risk assessment instruments each showed high sensitivity approaching or exceeding 90% for identifying individuals with DXA-determined osteoporosis or low BMD at certain thresholds in different populations but low specificity at thresholds required for high sensitivity. Simpler instruments, such as OST, generally performed as well as or better than more complex instruments.
UNLABELLED: We performed a systematic review and meta-analysis of the performance of clinical risk assessment instruments for screening for DXA-determined osteoporosis or low bone density. Commonly evaluated risk instruments showed high sensitivity approaching or exceeding 90% at particular thresholds within various populations but low specificity at thresholds required for high sensitivity. Simpler instruments, such as OST, generally performed as well as or better than more complex instruments. INTRODUCTION: The purpose of the study is to systematically review the performance of clinical risk assessment instruments for screening for dual-energy X-ray absorptiometry (DXA)-determined osteoporosis or low bone density. METHODS: Systematic review and meta-analysis were performed. Multiple literature sources were searched, and data extracted and analyzed from included references. RESULTS: One hundred eight references met inclusion criteria. Studies assessed many instruments in 34 countries, most commonly the Osteoporosis Self-Assessment Tool (OST), the Simple Calculated Osteoporosis Risk Estimation (SCORE) instrument, the Osteoporosis Self-Assessment Tool for Asians (OSTA), the Osteoporosis Risk Assessment Instrument (ORAI), and body weight criteria. Meta-analyses of studies evaluating OST using a cutoff threshold of <1 to identify US postmenopausal women with osteoporosis at the femoral neck provided summary sensitivity and specificity estimates of 89% (95%CI 82-96%) and 41% (95%CI 23-59%), respectively. Meta-analyses of studies evaluating OST using a cutoff threshold of 3 to identify US men with osteoporosis at the femoral neck, total hip, or lumbar spine provided summary sensitivity and specificity estimates of 88% (95%CI 79-97%) and 55% (95%CI 42-68%), respectively. Frequently evaluated instruments each had thresholds and populations for which sensitivity for osteoporosis or low bone mass detection approached or exceeded 90% but always with a trade-off of relatively low specificity. CONCLUSIONS: Commonly evaluated clinical risk assessment instruments each showed high sensitivity approaching or exceeding 90% for identifying individuals with DXA-determined osteoporosis or low BMD at certain thresholds in different populations but low specificity at thresholds required for high sensitivity. Simpler instruments, such as OST, generally performed as well as or better than more complex instruments.
Authors: Russel Burge; Bess Dawson-Hughes; Daniel H Solomon; John B Wong; Alison King; Anna Tosteson Journal: J Bone Miner Res Date: 2007-03 Impact factor: 6.741
Authors: Laura Gonzalez-Lopez; Jorge I Gamez-Nava; Anahi Vega-Lopez; N Alejandra Rodriguez-Jimenez; Norma Gonzalez-Montoya; Erika Aguilar-Chavez; M Fabiola Alcaraz-Lopez; Alberto D Rocha-Muñoz; Natasha Castro-Lizano; Jaime Morales-Romero; Mario Salazar-Paramo; Maria E Suarez-Almazor Journal: J Rheumatol Date: 2011-12-15 Impact factor: 4.666
Authors: J Steuart Richards; Justin Peng; Richard L Amdur; Ted R Mikuls; Roderick S Hooker; Kaleb Michaud; Andreas M Reimold; Grant W Cannon; Liron Caplan; Dannette Johnson; Anne E Hines; Gail S Kerr Journal: J Clin Densitom Date: 2009-09-23 Impact factor: 2.617
Authors: H S Lynn; J Woo; P C Leung; E L Barrett-Connor; M C Nevitt; J A Cauley; R A Adler; E S Orwoll Journal: Osteoporos Int Date: 2008-02-01 Impact factor: 4.507
Authors: William D Leslie; Lisa M Lix; Helena Johansson; Anders Oden; Eugene McCloskey; John A Kanis Journal: J Clin Densitom Date: 2013-02-26 Impact factor: 2.617
Authors: S T Williams; P T Lawrence; K L Miller; J L Crook; J LaFleur; G W Cannon; R E Nelson Journal: Osteoporos Int Date: 2017-07-30 Impact factor: 4.507
Authors: Susan J Diem; Katherine W Peters; Margaret L Gourlay; John T Schousboe; Brent C Taylor; Eric S Orwoll; Jane A Cauley; Lisa Langsetmo; Carolyn J Crandall; Kristine E Ensrud Journal: J Gen Intern Med Date: 2017-08-16 Impact factor: 5.128
Authors: M Kastner; L Perrier; S E P Munce; C C Adhihetty; A Lau; J Hamid; V Treister; J Chan; Y Lai; S E Straus Journal: Osteoporos Int Date: 2017-10-18 Impact factor: 4.507
Authors: John A Kanis; Nicholas C Harvey; Cyrus Cooper; Helena Johansson; Anders Odén; Eugene V McCloskey Journal: Arch Osteoporos Date: 2016-07-27 Impact factor: 2.617
Authors: Margaret L Gourlay; Victor S Ritter; Jason P Fine; Robert A Overman; John T Schousboe; Peggy M Cawthon; Eric S Orwoll; Tuan V Nguyen; Nancy E Lane; Steven R Cummings; Deborah M Kado; Jodi A Lapidus; Susan J Diem; Kristine E Ensrud Journal: Arch Osteoporos Date: 2017-10-20 Impact factor: 2.617