TY - JOUR
T1 - Making Composite Time Trade-Off Sensitive for Worse-than-Dead Health States
AU - Jakubczyk, Michał
AU - Roudijk, Bram
AU - Lipman, Stefan A.
AU - Stalmeier, Peep
N1 - Publisher Copyright:
© The Author(s) 2025.
PY - 2025/2/26
Y1 - 2025/2/26
N2 - Objective: The utilities elicited with the composite time trade-off (cTTO) method for health states worse-than-dead (WTD) often correlate poorly with other severity measures, indicating a poor sensitivity of cTTO. We aimed to explore modifications to cTTO to better understand this phenomenon and identify potential improvements. Methods: A total of 480 respondents completed an online TTO interview, each valuing 12 EQ-5D-5L health states. The participants were randomized into four arms, A–D. Arm A followed the standard cTTO, serving as a reference. In arm B, we removed the sorting question comparing immediate death versus 10 years in a valued state. Arm C allowed for utility values <-1 by reducing the time in the valued state in the lead-time TTO (LT-TTO) part of cTTO. In arm D, we randomly selected the starting negative utility in LT-TTO. Utility value distributions, correlations between utilities and level sum score (LSS), and inconsistencies between Pareto-ordered states were analyzed. Results: Arm A replicated the lack of significant correlation between LSS and the negative utility observed in previous work. Of the experimental arms, only arm B exhibited a significant negative correlation. Compared with arm A, arm B produced a higher proportion of WTD states (46.5% versus 26.3%), less negative utility for WTD states on average (-0.571 versus -0.752), and a lower mean censored utility for 55555 (-0.486 versus -0.406). Conclusions: The observed lack of correlation between LSS and utility for WTD states appears linked to the use of comparison with immediate death in the sorting question. LT-TTO is capable of eliciting utility values in a way that is sensitive to severity. Modifying the initial questions in cTTO to identify whether health states are BTD or WTD should be considered.
AB - Objective: The utilities elicited with the composite time trade-off (cTTO) method for health states worse-than-dead (WTD) often correlate poorly with other severity measures, indicating a poor sensitivity of cTTO. We aimed to explore modifications to cTTO to better understand this phenomenon and identify potential improvements. Methods: A total of 480 respondents completed an online TTO interview, each valuing 12 EQ-5D-5L health states. The participants were randomized into four arms, A–D. Arm A followed the standard cTTO, serving as a reference. In arm B, we removed the sorting question comparing immediate death versus 10 years in a valued state. Arm C allowed for utility values <-1 by reducing the time in the valued state in the lead-time TTO (LT-TTO) part of cTTO. In arm D, we randomly selected the starting negative utility in LT-TTO. Utility value distributions, correlations between utilities and level sum score (LSS), and inconsistencies between Pareto-ordered states were analyzed. Results: Arm A replicated the lack of significant correlation between LSS and the negative utility observed in previous work. Of the experimental arms, only arm B exhibited a significant negative correlation. Compared with arm A, arm B produced a higher proportion of WTD states (46.5% versus 26.3%), less negative utility for WTD states on average (-0.571 versus -0.752), and a lower mean censored utility for 55555 (-0.486 versus -0.406). Conclusions: The observed lack of correlation between LSS and utility for WTD states appears linked to the use of comparison with immediate death in the sorting question. LT-TTO is capable of eliciting utility values in a way that is sensitive to severity. Modifying the initial questions in cTTO to identify whether health states are BTD or WTD should be considered.
UR - http://www.scopus.com/inward/record.url?scp=85218777476&partnerID=8YFLogxK
U2 - 10.1007/s40273-025-01471-6
DO - 10.1007/s40273-025-01471-6
M3 - Article
C2 - 40009331
AN - SCOPUS:85218777476
SN - 1170-7690
JO - PharmacoEconomics
JF - PharmacoEconomics
ER -