We estimated EQ-5D index scores using the PROMIS global items and selected domain scores. Using different sets of the global items, we were able to account for 65% of the variance in preference scores. By comparison, about 57% of the variance in EQ-5D index scores was explained by the global item summary scores or selected PROMIS domain scores. These results are consistent with previous research in predicting health preference scores from HRQL profile measures [8
]. For example, Lawrence and Fleishman [14
] were able to explain 61–63% of the variance in EQ-5D index scores using SF-12 summary scores. Other researchers explained 58–63% of EQ-5D index scores using different HRQL measures [15
]. The availability of preference-based scores based on the PROMIS global items and domain scores enables potential application of these measures to population-based studies and economic evaluations. The main advantage of the PROMIS measures over other static health status measures is that the PROMIS domain item banks and scores allow flexibility in administration using either targeted short forms or computerized adaptive testing.
The estimated EQ-5D index scores based on PROMIS global items were comparable to those directly assessed using the EQ-5D in this sample. Based on the Bland-Altman and other analyses, there was evidence of some overestimation for EQ-5D scores under 0.40; however, the ICCs indicated good agreement (0.77). Differences between the predicted and actual index scores were between 0 and 0.02 points by gender and age groups. Most of the observed deviations were less than 0.01 points. These findings are encouraging and suggest that the predicted EQ-5D index scores may be applied to future studies. More importantly, the predicted EQ-5D index scores varied by presence of physical or mental conditions and were most impaired in those with both mental and physical conditions. The predicted EQ-5D scores based on the PROMIS domains were also comparable to the actual measured EQ-5D scores, and demonstrated similar levels of agreement to the PROMIS global items.
The general pattern of predicted EQ-5D index scores by gender and age groups seen in the PROMIS sample was comparable to those in other recent studies [2
]. There is a general decline in index scores by age, although the oldest age group (65–74 years) showed a small increase in preference scores compared with those aged 55–64 years. These findings are consistent with the observed EQ-5D index scores reported in Fryback et al. [2
There were few differences between the PROMIS sample and the Luo et al. [10
] study sample on preference scores. However, in the PROMIS sample women reported somewhat lower index scores, and those aged 65 years and older reported higher index scores compared to those in Luo et al. [10
] study. The Luo et al. [10
] study used self-completion, as did the PROMIS study, and this may explain the comparability in mean scores. We found some differences by gender and age groups between the predicted EQ-5D index scores from the PROMIS sample and those in the NHMS [2
]. The largest differences between the PROMIS and NHMS samples were for women aged 35–44 years and 45–54 years. The preference scores for the younger men and older men and women were comparable between the two samples. These observed differences may be due to different sampling strategies; the Fryback et al. [2
] study over-sampled the elderly and ethnic minorities, while the PROMIS study attempted to recruit a representative national sample through an internet panel. Fryback et al. [2
] weighted to account for this oversampling, but differences in response patterns and mode of administration (telephone interview vs. internet self-completion) may also have contributed to observed variability. Future research is needed to more carefully examine differences in the PROMIS-predicted EQ-5D index scores by ethnicity, gender, and age groups.
We recommend the PROMIS global item–based prediction equation as best for estimating EQ-5D scores if only one approach is considered. However, future application of these prediction equations depends on the incorporation of either the PROMIS global items or domain measures in future clinical and health services research studies. Given the flexibility of multi-domain short forms and computerized adaptive testing, the PROMIS domain item banks and domain scores may be very useful in clinical studies. The PROMIS global items have potential applications for large population-based and epidemiologic studies. The existing prediction equations allow flexibility to researchers depending on the PROMIS instruments included in their studies.
In general, if a researcher needs to include a preference-based health outcome measure in a study, the most recommended approach is to include one of the direct (i.e., time trade-off, standard gamble) or indirect (i.e., EQ-5D, HUI) measures of health preferences. As we have demonstrated, it is possible to estimate a preference-based score using the PROMIS global items or domain scores in the absence of a preference-based instrument, for example, because of respondent burden or other issues. However, the researcher should recognize that this is a second-best approach and that primary data collection is recommended.
There are several limitations associated with these analyses. First, for analyses involving PROMIS global items, the ordinal nature of these measures may impact the coefficient estimation in the regression analyses. Second, the PROMIS data were all collected using a web-based survey, and there may be differences between the PROMIS sample and the US general population that may limit generalizability of these results. However, Liu et al. (submitted) found that the PROMIS sample was comparable in demographic characteristics and health status to samples from the US general population.
In summary, we predicted EQ-5D index scores based on the PROMIS global items and selected domain scores, and these predicted preference scores varied as expected by demographic characteristics and presence of mental or physical conditions in the PROMIS sample. The predicted index scores were generally comparable to other national samples by age and gender groups. Additional research is needed to further evaluate the validity of the predicted index scores and should also examine other possible approaches to mapping the PROMIS item banks, perhaps through item response theory analysis and the resultant theta scores or through health preference measures such as the EQ-5D, HUI, or direct utility measures. This study suggests that useful preference scores can be derived from the PROMIS measures, and these predicted EQ-5D index scores have applications in measuring the health of populations and estimating quality-adjusted life years for economic evaluations.