title: Risk assessment to guide prostate cancer screening decisions: a cost-effectiveness analysis.
abstract: OBJECTIVE
  To apply the most recent evidence from randomised trials of prostate-specific antigen (PSA) screening and explore the potential value of risk assessments to guide the use of PSA screening in practice.
  
  
  METHODS
  A decision model that incorporated a Markov process was developed in 2012 to estimate the net benefit and cost of PSA screening versus no screening as a function of baseline risk.
  
  
  METHODS
  Quality-adjusted life-2013s (QALYs) and costs.
  
  
  RESULTS
  The harms of screening outweighed the benefits under a number of plausible scenarios. Conclusions were sensitive to the estimated quality-of-life impacts of prostate cancer treatment as well as the incidence of cancers not detected by screening tests (poorer prognosis) and those that were detected by screening tests (better prognosis). The base-case incremental cost-effectiveness ratio of PSA screening was $168,611 per QALY for men with average risk, $73,452 per QALY for men with two times the average risk, and $22,938 [corrected] per QALY for men with five times the average risk.
  
  
  CONCLUSIONS
  PSA screening was not found to be cost-effective for men at an average-to-high risk of prostate cancer, but may be cost-effective for men at very high risk. Inexpensive approaches for identifying men at very high risk are needed, as is further research on the size of clinical benefit of early detection in this population. The potential for the costs of risk assessment to be offset by reduced costs of PSA screening also warrants investigation.
authors.affiliation: NHMRC Clinical Trials Centre, University of Sydney, Sydney, NSW, Australia. andrew.martin@ctc.usyd.edu.au
authors.forename: Andrew J
authors.initials: AJ
authors.lastname: Martin
authors.forename: Sarah J
authors.initials: SJ
authors.lastname: Lord
authors.forename: Hannah E
authors.initials: HE
authors.lastname: Verry
authors.forename: Martin R
authors.initials: MR
authors.lastname: Stockler
authors.forename: Jon D
authors.initials: JD
authors.lastname: Emery
mesh_terms: D001315:Australia; D015415:Biomarkers / Q000097:blood; D003198:Computer Simulation; D003362:Cost-Benefit Analysis; D003661:Decision Support Techniques; D055088:Early Detection of Cancer / Q000009:adverse effects / Q000191:economics / Q000379:methods; D017048:Health Care Costs; D006801:Humans; D007610:Kallikreins / Q000097:blood*; D008297:Male; D008390:Markov Chains; D008875:Middle Aged; D017430:Prostate-Specific Antigen / Q000097:blood*; D011471:Prostatic Neoplasms / Q000097:blood / Q000175:diagnosis* / Q000191:economics; D019057:Quality-Adjusted Life Years; D018570:Risk Assessment
chemical_list: D015415:Biomarkers; C549870:KLK3 protein, human; D007610:Kallikreins; D017430:Prostate-Specific Antigen