A N A Tosteson1, L J Melton, B Dawson-Hughes, S Baim, M J Favus, S Khosla, R L Lindsay. 1. Multidisciplinary Clinical Research Center in Musculoskeletal Diseases and The Dartmouth Institute for Health Policy and Clinical Practice, Dartmouth Medical School, Lebanon, NH 03756, USA. anna.tosteson@dartmouth.edu
Abstract
UNLABELLED: A United States-specific cost-effectiveness analysis, which incorporated the cost and health consequences of clinical fractures of the hip, spine, forearm, shoulder, rib, pelvis and lower leg, was undertaken to identify the 10-year hip fracture probability required for osteoporosis treatment to be cost-effective for cohorts defined by age, sex, and race/ethnicity. A 3% 10-year risk of hip fracture was generally required for osteoporosis treatment to cost less than $60,000 per QALY gained. INTRODUCTION: Rapid growth of the elderly United States population will result in so many at risk of osteoporosis that economically efficient approaches to osteoporosis care warrant consideration. METHODS: A Markov-cohort model of annual United States age-specific incidence of clinical hip, spine, forearm, shoulder, rib, pelvis and lower leg fractures, costs (2005 US dollars), and quality-adjusted life years (QALYs) was used to assess the cost-effectiveness of osteoporosis treatment ($600/yr drug cost for 5 years with 35% fracture reduction) by gender and race/ethnicity groups. To determine the 10-year hip fracture probability at which treatment became cost-effective, average annual age-specific probabilities for all fractures were multiplied by a relative risk (RR) that was systematically varied from 0 to 10 until a cost of $60,000 per QALY gained was observed for treatment relative to no intervention. RESULTS: Osteoporosis treatment was cost-effective when the 10-year hip fracture probability reached approximately 3%. Although the RR at which treatment became cost-effective varied markedly between genders and by race/ethnicity, the absolute 10-year hip fracture probability at which intervention became cost-effective was similar across race/ethnicity groups, but tended to be slightly higher for men than for women. CONCLUSIONS: Application of the WHO risk prediction algorithm to identify individuals with a 3% 10-year hip fracture probability may facilitate efficient osteoporosis treatment.
UNLABELLED: A United States-specific cost-effectiveness analysis, which incorporated the cost and health consequences of clinical fractures of the hip, spine, forearm, shoulder, rib, pelvis and lower leg, was undertaken to identify the 10-year hip fracture probability required for osteoporosis treatment to be cost-effective for cohorts defined by age, sex, and race/ethnicity. A 3% 10-year risk of hip fracture was generally required for osteoporosis treatment to cost less than $60,000 per QALY gained. INTRODUCTION: Rapid growth of the elderly United States population will result in so many at risk of osteoporosis that economically efficient approaches to osteoporosis care warrant consideration. METHODS: A Markov-cohort model of annual United States age-specific incidence of clinical hip, spine, forearm, shoulder, rib, pelvis and lower leg fractures, costs (2005 US dollars), and quality-adjusted life years (QALYs) was used to assess the cost-effectiveness of osteoporosis treatment ($600/yr drug cost for 5 years with 35% fracture reduction) by gender and race/ethnicity groups. To determine the 10-year hip fracture probability at which treatment became cost-effective, average annual age-specific probabilities for all fractures were multiplied by a relative risk (RR) that was systematically varied from 0 to 10 until a cost of $60,000 per QALY gained was observed for treatment relative to no intervention. RESULTS:Osteoporosis treatment was cost-effective when the 10-year hip fracture probability reached approximately 3%. Although the RR at which treatment became cost-effective varied markedly between genders and by race/ethnicity, the absolute 10-year hip fracture probability at which intervention became cost-effective was similar across race/ethnicity groups, but tended to be slightly higher for men than for women. CONCLUSIONS: Application of the WHO risk prediction algorithm to identify individuals with a 3% 10-year hip fracture probability may facilitate efficient osteoporosis treatment.
Authors: J A Kanis; D Black; C Cooper; P Dargent; B Dawson-Hughes; C De Laet; P Delmas; J Eisman; O Johnell; B Jonsson; L Melton; A Oden; S Papapoulos; H Pols; R Rizzoli; A Silman; A Tenenhouse Journal: Osteoporos Int Date: 2002-07 Impact factor: 4.507
Authors: S E Gabriel; A N A Tosteson; C L Leibson; C S Crowson; G R Pond; C S Hammond; L J Melton Journal: Osteoporos Int Date: 2002 Impact factor: 4.507
Authors: Ann Cranney; George Wells; Andrew Willan; Lauren Griffith; Nicole Zytaruk; Vivian Robinson; Dennis Black; Jonathan Adachi; Beverley Shea; Peter Tugwell; Gordon Guyatt Journal: Endocr Rev Date: 2002-08 Impact factor: 19.871
Authors: B Dawson-Hughes; A N A Tosteson; L J Melton; S Baim; M J Favus; S Khosla; R L Lindsay Journal: Osteoporos Int Date: 2008-02-22 Impact factor: 4.507
Authors: Patrick Haentjens; Philippe Autier; John Collins; Brigitte Velkeniers; Dirk Vanderschueren; Steven Boonen Journal: J Bone Joint Surg Am Date: 2003-10 Impact factor: 5.284
Authors: Alexandra Papaioannou; Suzanne Morin; Angela M Cheung; Stephanie Atkinson; Jacques P Brown; Sidney Feldman; David A Hanley; Anthony Hodsman; Sophie A Jamal; Stephanie M Kaiser; Brent Kvern; Kerry Siminoski; William D Leslie Journal: CMAJ Date: 2010-10-12 Impact factor: 8.262
Authors: Kristine E Ensrud; Li-Yung Lui; Brent C Taylor; John T Schousboe; Meghan G Donaldson; Howard A Fink; Jane A Cauley; Teresa A Hillier; Warren S Browner; Steven R Cummings Journal: Arch Intern Med Date: 2009-12-14