CAN PREFERENCE SCORES FOR DISCRETE STATES BE USED TO DERIVE PREFERENCE SCORES FOR AN ENTIRE PATH OF EVENTS - AN APPLICATION TO PRENATAL-DIAGNOSIS

The authors conducted a study exploring whether preferences for sequen ces of events can be approximated by preferences for component discret e states. Visual-analog-scale (VAS) and standard-gamble (SG) scores fo r a subset of the possible sequences of events (path states) and compo nent temporary and chronic outcomes (discrete states) that can follow prenatal diagnostic decisions were elicited from 121 pregnant women fa cing a choice between chorionic villus sampling and amniocentesis. For individuals, preference scores for path states could not be predicted easily from discrete-state scores. Mean path-state VAS scores, howeve r, were predicted reasonably accurately by multiple regression models (R(2) = 0.85 and 0.82 for two different anchoring schemes), with most measured scores lying within the 95% confidence intervals of the deriv ed scores. It is concluded that, for individual patient decision makin g, preferences for path states should be elicited. When mean preferenc e values for a population are sought, however, it may be reasonable to derive regression weights from a subset of respondents and then to ap ply those weights to preferences for discrete states elicited from a l arger group.