1. Patient preferences for Personalized (N-of-1) Trials: A conjoint analysis
- Author
-
Nathalie Moise, Dallas Wood, Ying Kuen K. Cheung, Naihua Duan, Tara St. Onge, Joan Duer-Hefele, Tiffany Pu, Karina W. Davidson, Ian M. Kronish, Carmela Alcantara, Paul Appelbaum, Eileen Carter, Elizabeth Cohn, Richard Kravitz, Scott Kelly, Jose Luchsinger, Ty Ridenour, Michele Romandetto, Jonathan Shaffer, and Steven Shea
- Subjects
N of 1 trial ,Adult ,Male ,medicine.medical_specialty ,Blinding ,Epidemiology ,Computer science ,Article ,03 medical and health sciences ,0302 clinical medicine ,Surveys and Questionnaires ,medicine ,Humans ,Medical physics ,030212 general & internal medicine ,Duration (project management) ,Precision Medicine ,Selection (genetic algorithm) ,Aged ,Discrete choice ,Clinical Trials as Topic ,Evidence-Based Medicine ,030503 health policy & services ,Age Factors ,Patient Preference ,Middle Aged ,Patient preference ,Conjoint analysis ,Standard error ,Cross-Sectional Studies ,Logistic Models ,Socioeconomic Factors ,Female ,Health Expenditures ,0305 other medical science - Abstract
OBJECTIVE: Despite their promise for increasing treatment precision, Personalized Trials (i.e., N-of-1 trials) have not been widely adopted. We aimed to ascertain patient preferences for Personalized Trials. STUDY DESIGN AND SETTING: We recruited 501 adults with ≥2 common chronic conditions from Harris Poll Online. We used Sawtooth Software to generate 45 plausible Personalized Trial designs comprised of combinations of 8 key attributes (treatment selection, treatment type, clinician involvement, blinding, time commitment, self-monitoring frequency, duration, cost) at different levels. Conditional logistic regression was used to assess relative importance of different attributes using a random utility maximization model. RESULTS: Overall, participants preferred Personalized Trials with no costs vs. $100 cost (utility difference 1.52 [standard error 0.07], p
- Published
- 2018