title: Cost-effectiveness of bone densitometry among Caucasian women and men without a prior fracture according to age and body weight.
abstract: We used a microsimulation model to estimate the threshold body weights at which screening bone densitometry is cost-effective. Among women aged 55-65 years and men aged 55-75 years without a prior fracture, body weight can be used to identify those for whom bone densitometry is cost-effective.
  
  
  BACKGROUND
  Bone densitometry may be more cost-effective for those with lower body weight since the prevalence of osteoporosis is higher for those with low body weight. Our purpose was to estimate weight thresholds below which bone densitometry is cost-effective for women and men without a prior clinical fracture at ages 55, 60, 65, 75, and 80 years.
  
  
  METHODS
  We used a microsimulation model to estimate the costs and health benefits of bone densitometry and 5 years of fracture prevention therapy for those without prior fracture but with femoral neck osteoporosis (T-score ≤ -2.5) and a 10-year hip fracture risk of ≥3%. Threshold pre-test probabilities of low BMD warranting drug therapy at which bone densitometry is cost-effective were calculated. Corresponding body weight thresholds were estimated using data from the Study of Osteoporotic Fractures (SOF), the Osteoporotic Fractures in Men (MrOS) study, and the National Health and Nutrition Examination Survey (NHANES) for 2005-2006.
  
  
  RESULTS
  Assuming a willingness to pay of $75,000 per quality adjusted life year (QALY) and drug cost of $500/year, body weight thresholds below which bone densitometry is cost-effective for those without a prior fracture were 74, 90, and 100 kg, respectively, for women aged 55, 65, and 80 years; and were 67, 101, and 108 kg, respectively, for men aged 55, 75, and 80 years.
  
  
  CONCLUSIONS
  For women aged 55-65 years and men aged 55-75 years without a prior fracture, body weight can be used to select those for whom bone densitometry is cost-effective.
authors.affiliation: Park Nicollet Institute, Minneapolis, MN, USA. john.schousboe@parknicollet.com
authors.forename: J T
authors.initials: JT
authors.lastname: Schousboe
authors.forename: M
authors.initials: M
authors.lastname: Gourlay
authors.forename: H A
authors.initials: HA
authors.lastname: Fink
authors.forename: B C
authors.initials: BC
authors.lastname: Taylor
authors.forename: E S
authors.initials: ES
authors.lastname: Orwoll
authors.forename: E
authors.initials: E
authors.lastname: Barrett-Connor
authors.forename: L J
authors.initials: LJ
authors.lastname: Melton
authors.forename: S R
authors.initials: SR
authors.lastname: Cummings
authors.forename: K E
authors.initials: KE
authors.lastname: Ensrud
mesh_terms: D015502:Absorptiometry, Photon / Q000191:economics; D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D001835:Body Weight / Q000502:physiology*; D015519:Bone Density / Q000502:physiology; D003362:Cost-Benefit Analysis; D005260:Female; D017048:Health Care Costs / Q000706:statistics & numerical data; D006801:Humans; D008297:Male; D008875:Middle Aged; D017059:Models, Econometric; D010024:Osteoporosis / Q000175:diagnosis* / Q000191:economics / Q000503:physiopathology; D058866:Osteoporotic Fractures / Q000191:economics / Q000503:physiopathology / Q000517:prevention & control*; D018579:Patient Selection; D019057:Quality-Adjusted Life Years; D018570:Risk Assessment / Q000379:methods