Accounting for increased non-target-disease-specific mortality in decision-analytic screening models for economic...

Positive screening results are often associated not only with target-disease-specific but also with non-target-disease-specific mortality. In general, this association is due to joint risk factors. Cost-effectiveness estimates based on decision-analytic models may be biased if this association is not reflected appropriately.

To develop a procedure for quantifying the degree of bias when an increase in non-target-disease-specific mortality is not considered.

We developed a family of parametric functions that generate hazard ratios (HRs) of non-target-disease-specific mortality between subjects screened positive and negative, with the HR of target-disease-specific mortality serving as the input variable. To demonstrate the efficacy of this procedure, we fitted a function within the context of coronary artery disease (CAD) risk screening, based on HRs related to different risk factors extracted from published studies. Estimates were embedded into a decision-analytic model, and the impact of 'modelling increased non-target-disease-specific mortality' was assessed.

In 55-year-old German men, based on a risk screening with 5% positively screened subjects, and a CAD risk ratio of 6 within the first year after screening, incremental quality-adjusted life-years were 19% higher and incremental costs were 8% lower if no adjustment was made. The effect varied depending on age, gender, the explanatory power of the screening test and other factors.

Some bias can occur when an increase in non-target-disease-specific mortality is not considered when modelling the outcomes of screening tests.