EuroQol Research Foundation, Rotterdam, The Netherlands.
Radboud University Medical Center, Radboud Institute for Health Sciences, Nijmegen, The Netherlands.
Qual Life Res. 2022 Sep;31(9):2753-2761. doi: 10.1007/s11136-022-03155-6. Epub 2022 May 27.
Recent studies concluded that for health states considered worse than dead (WTD), as measured with the time trade-off (cTTO) method, negative mean values were insensitive to health state severity, which represents a validity problem for the cTTO. However, the aforementioned studies analysed negative values in isolation, which causes selection bias as the value distribution is truncated.
To investigate the validity of aforementioned studies and of negative values in general.
The 'threshold explanation' was formulated: beyond a certain severity threshold, preferences change from better than dead (BTD) to WTD. This threshold differs between respondents. Thus, negative values across severity are obtained from different respondents, and responses added for higher severity contribute negative values close to zero, explaining the aforementioned insensitivity. This explanation was tested using data from the Dutch EQ-5D-5L valuation study. Respondents valued 10 health states. Based on respondents' number of WTD preferences, segments were constructed, containing respondents with similar severity thresholds. Using regression models for each individual respondent, we examined the relation between values and severity and compared respondents between segments.
Negative values, when analysed in isolation, were insensitive to severity. However, for individual respondents and within most segments, cTTO values and severity were negatively related. For individual respondents, negative slopes were steeper for segments with more WTD preferences, as predicted by the threshold explanation.
Analysing negative values in isolation leads to biased estimates. Analyses of cTTO values for individual respondents refute the insensitivity of negative cTTO values.
最近的研究得出结论，对于用时间权衡（cTTO）方法衡量的比死亡状态还差（WTD）的健康状态，负的平均值对健康状态的严重程度不敏感，这代表了 cTTO 的有效性问题。然而，上述研究分析了孤立的负值，这会导致选择偏差，因为值分布被截断了。
调查上述研究和负值的有效性。
提出了“阈值解释”：超过一定的严重程度阈值，偏好会从比死亡状态更好（BTD）转变为 WTD。这个阈值因人而异。因此，不同严重程度的负数值是从不同的受访者中获得的，而对更高严重程度的响应则增加了接近零的负数值，解释了上述的不敏感性。使用来自荷兰 EQ-5D-5L 估值研究的数据来测试这一解释。受访者对 10 个健康状态进行了评估。根据受访者的 WTD 偏好数量，构建了包含相似严重程度阈值的受访者的段。使用每个个体受访者的回归模型，我们检查了值与严重程度之间的关系，并比较了段之间的受访者。
孤立地分析负数值时，它们对严重程度不敏感。然而，对于个体受访者和大多数段内，cTTO 值和严重程度呈负相关。对于个体受访者，WTD 偏好较多的段中，cTTO 的负斜率更陡峭，正如阈值解释所预测的那样。
孤立地分析负数值会导致有偏差的估计。对个体受访者的 cTTO 值进行分析，反驳了负 cTTO 值不敏感的说法。
