Clinical trials often produce mixed results in which the primary and secondary outcomes are conflicting. Such results are difficult to transform into straightforward treatment recommendations or patient information. To overcome this decision problem, additional decision analytic strategies can be applied. One strategy is to measure disease-specific or generic health-related Quality of Life [1
]. An alternative strategy is to measure explicitly the patient's (and/or expert's) preferences regarding the interventions and the full set of consequences following each of the interventions. A typical preference study derives weights on real life health states and the relevant aspects and consequences of each of the decisions based on valuation or choice experiments.
Situations in which outcomes of clinical studies are conflicting often arise in the field of obstetrics. Although often treated as a single unit, mother and child are two entities that may have conflicting interests, thus complicating the choice between alternative treatments. For example, in a pregnancy complicated by fetal growth retardation at term, theoretically it is better for the baby to be delivered. Induced delivery, however, is thought to increase the risk of requiring a caesarean section, thus harming the mother. Information on the (possible) outcomes alone is insufficient, since a clinical decision has to be made – which implies the weighing of relevant outcomes.
The present study involves two clinical dilemmas common in the third trimester of pregnancy: pregnancy-induced hypertension or pre-eclampsia (HYPITAT, ISRCT08132825) and suspected growth retardation (DIGTAT, ISRCT10363217). Whenever one of these complications occurs, a choice has to be made between either expectant management and induction of labour. Induction of labour can result in a lower risk of pregnancy complications and intrauterine death, but a higher risk of prematurity, assisted vaginal delivery and caesarean section. Expectant management involves the reverse. This choice is difficult for both physicians and parents because of the multidimensionality of the alternative treatment strategies. For instance, at least two people rather than one person bear the weight of the outcome – both mother and child. Also, the usual outcome risk is a mix of rare but very severe outcomes (e.g. mortality) and frequent but moderately important procedural and clinical outcomes. Finally, the time axis of occurrence and impact differs considerably between temporary short term and long-term health profiles.
The main objective of the present study is to compare different existing methodologies in the field of preference and utility measurement in order to arrive at a method that is feasible, reliable and valid for the analysis of multidimensional outcomes. The comparisons will be between 'attitude'-based methods that measure people's valuation of specific health states, such as the Visual Analogue Scale (VAS), Time Trade-Off (TTO) and Willingness To Pay (WTP), and 'preference'-based methods that involves a choice between two alternative health states, such as Discrete Choice Experiment (DCE). The methods have been well-described, but as yet a head-to-head comparison in this context has not been made [2