A method for the early health technology assessment of novel biomarker measurement in primary prevention programs.
Many promising biomarkers for stratifying individuals at risk of developing a chronic disease or subsequent complications have been identified. Research into the potential cost-effectiveness of applying these biomarkers in actual clinical settings has however been lacking. Investors and analysts may improve their venture decision making should they have indicative estimates of the potential costs and effects associated with a new biomarker technology already at the early stages of its development. To assist in obtaining such estimates, this paper presents a general method for the early health technology assessment of a novel biomarker technology. The setting considered is that of primary prevention programs where initial screening to select high-risk individuals eligible for a subsequent intervention occurs, for example, prevention of type 2 diabetes. The method is based on quantifying the health outcomes and downstream healthcare consumption of all individuals who get reclassified as a result of moving from a screening variant based on traditional risk factors to a screening variant based on traditional risk factors plus a novel biomarker. As these individuals form well-defined subpopulations, a combination of disease progression modeling and sensitivity analysis can be used to perform an initial assessment of the maximum increase in screening cost for which the use of the new biomarker technology is still likely to be cost effective.
Department of Epidemiology, University Medical Center Groningen, University of Groningen, The Netherlands. d.postmus@umcg.nl
Douwe
D
Postmus
Gimon
G
de Graaf
Hans L
HL
Hillege
Ewout W
EW
Steyerberg
Erik
E
Buskens
D015415:Biomarkers / Q000032:analysis*; D020811:Biomedical Technology / Q000191:economics*; D003362:Cost-Benefit Analysis / Q000191:economics; D003924:Diabetes Mellitus, Type 2 / Q000191:economics / Q000517:prevention & control; D006801:Humans; D018803:Models, Economic; D015233:Models, Statistical; D011322:Primary Prevention / Q000191:economics*; D013673:Technology Assessment, Biomedical / Q000191:economics*
D015415:Biomarkers