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 <InlineEquation ID="IEq1"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="40273_2025_1471_Article_IEq1.gif" Format="GIF" Height="14" Rendition="HTML" Resolution="72" Type="Linedraw" Width="41" /> </InlineMediaObject> <EquationSource Format="TEX">$<-1$</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mo><</mo> <mo>-</mo> <mn>1</mn> </mrow> </math></EquationSource> </InlineEquation> 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 (<InlineEquation ID="IEq2"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="40273_2025_1471_Article_IEq2.gif" Format="GIF" Height="16" Rendition="HTML" Resolution="72" Type="Linedraw" Width="43" /> </InlineMediaObject> <EquationSource Format="TEX">$46.5\%$</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mn>46.5</mn> <mo>%</mo> </mrow> </math></EquationSource> </InlineEquation> versus <InlineEquation ID="IEq3"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="40273_2025_1471_Article_IEq3.gif" Format="GIF" Height="16" Rendition="HTML" Resolution="72" Type="Linedraw" Width="43" /> </InlineMediaObject> <EquationSource Format="TEX">$26.3\%$</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mn>26.3</mn> <mo>%</mo> </mrow> </math></EquationSource> </InlineEquation>), less negative utility for WTD states on average (<InlineEquation ID="IEq4"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="40273_2025_1471_Article_IEq4.gif" Format="GIF" Height="14" Rendition="HTML" Resolution="72" Type="Linedraw" Width="52" /> </InlineMediaObject> <EquationSource Format="TEX">$-0.571$</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mo>-</mo> <mn>0.571</mn> </mrow> </math></EquationSource> </InlineEquation> versus <InlineEquation ID="IEq5"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="40273_2025_1471_Article_IEq5.gif" Format="GIF" Height="14" Rendition="HTML" Resolution="72" Type="Linedraw" Width="52" /> </InlineMediaObject> <EquationSource Format="TEX">$-0.752$</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mo>-</mo> <mn>0.752</mn> </mrow> </math></EquationSource> </InlineEquation>), and a lower mean censored utility for 55555 (<InlineEquation ID="IEq6"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="40273_2025_1471_Article_IEq6.gif" Format="GIF" Height="14" Rendition="HTML" Resolution="72" Type="Linedraw" Width="52" /> </InlineMediaObject> <EquationSource Format="TEX">$-0.486$</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mo>-</mo> <mn>0.486</mn> </mrow> </math></EquationSource> </InlineEquation> versus <InlineEquation ID="IEq7"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="40273_2025_1471_Article_IEq7.gif" Format="GIF" Height="14" Rendition="HTML" Resolution="72" Type="Linedraw" Width="52" /> </InlineMediaObject> <EquationSource Format="TEX">$-0.406$</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mo>-</mo> <mn>0.406</mn> </mrow> </math></EquationSource> </InlineEquation>). 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.

Making Composite Time Trade-Off Sensitive for Worse-than-Dead Health States

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2025年2月26日

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Michał Jakubczyk,
Bram Roudijk,
Stefan A. Lipman,
Peep Stalmeier

摘要

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 $<-1$ $< - 1$ 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 ( $46.5\%$ $46.5 %$ versus $26.3\%$ $26.3 %$ ), less negative utility for WTD states on average ( $-0.571$ $- 0.571$ versus $-0.752$ $- 0.752$ ), and a lower mean censored utility for 55555 ( $-0.486$ $- 0.486$ versus $-0.406$ $- 0.406$ ).

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.