## Abstract

Background. Lead time tradeoff (L-TTO) is a variant of the time tradeoff (TTO). L-TTO introduces a lead period in full health before illness onset, avoiding the need to use 2 different procedures for states better and worse than dead. To estimate utilities, additive separability is assumed. We tested to what extent violations of this assumption can bias utilities estimated with L-TTO.

Methods. A sample of 500 members of the Spanish general population evaluated 24 health states, using face-to-face interviews. A total of 188 subjects were interviewed with L-TTO and the rest with TTO. Both samples evaluated the same set of 24 health states, divided into 4 groups with 6 health states per set. Each subject evaluated 1 of the sets. A random effects regression model was fitted to

our data. Only health states better than dead were included in the regression since it is in this subset where additive separability can be tested clearly. Results.

Utilities were higher in L-TTO in relation to TTO (on average L-TTO adds about 0.2 points to the utility of health states), suggesting that additive separability is violated. The difference between methods increased with the severity of the health state. Thus, L-TTO adds about 0.14 points to the average utility of the less severe states, 0.23 to the intermediate states, and 0.28 points to the

more severe estates. Conclusions. L-TTO produced higher utilities than TTO. Health problems are perceived as less severe if a lead period in full health is added upfront, implying that there are interactions between disjointed

time periods. The advantages of this method have to be compared with the cost of modeling the interaction between periods. Key words: cost utility analysis;

lead time trade off; states better than dead; additive separability; random effects regression.

Methods. A sample of 500 members of the Spanish general population evaluated 24 health states, using face-to-face interviews. A total of 188 subjects were interviewed with L-TTO and the rest with TTO. Both samples evaluated the same set of 24 health states, divided into 4 groups with 6 health states per set. Each subject evaluated 1 of the sets. A random effects regression model was fitted to

our data. Only health states better than dead were included in the regression since it is in this subset where additive separability can be tested clearly. Results.

Utilities were higher in L-TTO in relation to TTO (on average L-TTO adds about 0.2 points to the utility of health states), suggesting that additive separability is violated. The difference between methods increased with the severity of the health state. Thus, L-TTO adds about 0.14 points to the average utility of the less severe states, 0.23 to the intermediate states, and 0.28 points to the

more severe estates. Conclusions. L-TTO produced higher utilities than TTO. Health problems are perceived as less severe if a lead period in full health is added upfront, implying that there are interactions between disjointed

time periods. The advantages of this method have to be compared with the cost of modeling the interaction between periods. Key words: cost utility analysis;

lead time trade off; states better than dead; additive separability; random effects regression.

Original language | English |
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Pages (from-to) | 305-315 |

Number of pages | 11 |

Journal | Medical Decision Making |

Volume | 35 |

Issue number | 3 |

DOIs | |

Publication status | Published - Apr 2015 |

## Keywords

- cost utility analysis
- lead time trade off
- states better than dead
- additive separability
- random effects regression