Personalized Mammography Screening and Screening Adherence—A Simulation and Economic Evaluation

Jul 1, 2018, 00:00 AM
10.1016/j.jval.2017.12.022
https://www.valueinhealthjournal.com/article/S1098-3015(18)30180-3/fulltext
Section Title : ECONOMIC EVALUATIONS
Section Order : 7
First Page : 799

Objective

Personalized breast cancer screening has so far been economically evaluated under the assumption of full screening adherence. This is the first study to evaluate the effects of nonadherence on the evaluation and selection of personalized screening strategies.

Methods

Different adherence scenarios were established on the basis of findings from the literature. A Markov microsimulation model was adapted to evaluate the effects of these adherence scenarios on three different personalized strategies.

Results

First, three adherence scenarios describing the relationship between risk and adherence were identified: 1) a positive association between risk and screening adherence, 2) a negative association, or 3) a curvilinear relationship. Second, these three adherence scenarios were evaluated in three personalized strategies. Our results show that it is more the absolute adherence rate than the nature of the risk-adherence relationship that is important to determine which strategy is the most cost-effective. Furthermore, probabilistic sensitivity analyses showed that there are risk-stratified screening strategies that are more cost-effective than routine screening if the willingness-to-pay threshold for screening is below US $60,000.

Conclusions

Our results show that “nonadherence” affects the relative performance of screening strategies. Thus, it is necessary to include the true adherence level to evaluate personalized screening strategies and to select the best strategy.

https://www.valueinhealthjournal.com/action/showCitFormats?pii=S1098-3015(18)30180-3&doi=10.1016/j.jval.2017.12.022
HEOR Topics :
Tags :
  • adherence
  • breast cancer screening
  • decision analysis
  • economic evaluation
  • mammography
  • Markov model
  • personalized medicine
Regions :