HOW HETEROGENEOUS ARE PREFERENCES FOR DELAYING ONSET OF ALZHEIMER'S DISEASE: IT DEPENDS ON HOW YOU LOOK

Purpose:

To investigate how two approaches to taste heterogeneity modeling affect inferences about relative-importance weights that US elderly placed on treatment benefits and risks for delaying the onset of Alzheimer’s disease (AD).

Method:

1004 US individuals aged between 60 and 85 completed a web-enabled discrete-choice survey instrument in which they were to suppose that they would develop AD in the future without medication.  Survey tasks presented the option of no medication or a hypothetical AD treatment, using either a 12 or 16-year timeframe with progression from normal memory to cognitive impairment to AD to death.  AD treatments were defined by reductions in the number of years with cognitive impairment or AD but with daily nausea and increased risks of disabling stroke and of death in the first year of treatment.  Choice tasks were based on predetermined statistical properties using SAS.  Choice data were analyzed using a random parameters logit (RPL) model in Stata and a scale-adjusted latent-class analysis (LCA) model in Latent GOLD.  Model parameters were rescaled to a common metric to facilitate comparison between RPL and LCA.

Result:

LCA revealed three distinct classes of respondents based on survey timeframe, respondent age, current health status, and whether the respondent was a current AD caregiver.  Class one (42% of study sample) generally preferred medication, traded between all benefits and risks, was relatively younger, and was not a current AD caregiver.  Class two (30% of sample) preferred no medication, was more concerned about treatment risks than benefit, had no self-reported illnesses, and was a current AD caregiver.  Class three (28% of sample) strongly preferred medication, was more concerned about treatment benefit than risks, was relatively older, and was a current AD caregiver.  The relative importance of treatment benefit and risks from RPL was similar to that of the largest class (class one).

Conclusion:

Most respondents (70%) were willing to accept treatment risks to reduce time with cognitive impairment or AD.  However, the LCA identified 30% of respondents that were more risk averse with a strong preference for no AD treatment.  While RPL model results may be informative for the “average” respondent and general policymaking, results from the LCA may hold the key to identifying heterogeneity of preferences and guiding treatment decision making in a clinical setting.