Cost-Utility Analyses of Diagnostic Laboratory Tests: A Systematic Review

AbstractObjectiveTo review and evaluate the literature of cost-utility analyses (CUAs) regarding diagnostic laboratory testing.MethodsWe reviewed all articles related to diagnostic laboratory testing in the Tufts Medical Center Cost-Effectiveness Analysis Registry (www.cearegistry.org), which contains detailed information on over 2000 published CUAs through 2008. We analyzed the extent to which the studies adhered to recommended practices for conducting and reporting cost-effectiveness analyses. We also recorded whether the studies contained information on diagnostic test accuracy and costs, and whether any account was taken of potential benefits or harms of testing that are unrelated to subsequent treatment, such as the reassurance value of testing.ResultsWe identified 141 published CUAs pertaining to diagnostic laboratory testing published through 2008 which contained 433 separate incremental cost-effectiveness ratios. Prior to 2000, there were only 20 CUAs published, but the number averaged 13.4 annually thereafter. Most studies focused on hematology/oncology (n = 42, 30%) and obstetrics/gynecology (n = 36, 26%) applications. Approximately 63% (n = 89) of studies clearly reported information about the accuracy of the test, but only 10% (n = 14) mentioned test safety or possible risks. A small number (n = 10, 7%) mentioned or considered the potential value or harm of testing unrelated to treatment consequences. Over 55% of the reported incremental cost-effectiveness ratios (ICERs) were either dominant (more quality-adjusted life years for less cost), or below $50,000 per quality-adjusted life years gained (in 2008 US dollars).ConclusionThe number of CUAs investigating laboratory diagnostic testing has increased substantially with applications to diverse clinical areas. The literature reveals many areas in which testing represents good value for money. The vast majority of studies have not considered preferences for test information unrelated to treatment consequences

Willingness to pay for predictive tests with no immediate treatment implications : a survey of U.S. residents

International audienceWe assessed how much, if anything, people would pay for a laboratory test that predicted their future disease status. A questionnaire was administered via an internet-based survey to a random sample of adult U.S. respondents. Each respondent answered questions about two different scenarios, each of which specified: one of four randomly selected diseases (Alzheimer’s, arthritis, breast cancer, or prostate cancer); an ex ante risk of developing the disease (randomly designated 10% or 25%); and test accuracy (randomly designated perfect or “not perfectly accurate”). Willingness to pay (WTP) was elicited with a double-bounded, dichotomous-choice approach. Of 2,223 respondents who completed the survey, most (70-88%, depending on the scenario) were inclined to take the test. WTP was lower for Alzheimer’s and higher for prostate cancer compared with arthritis, and rose somewhat with disease prevalence and for the perfect vs. imperfect test. Median WTP varied from $109 for the imperfect arthritis test to$263 for the perfect prostate cancer test. Respondents’ preferences for predictive testing, even in the absence of direct treatment consequences, reflected health and non-health related factors, and suggests that conventional cost-effectiveness analyses may underestimate the value of testing