Variation in the Estimation of Quality-adjusted Life-years by Different Preference-based Instruments

Conner‐Spady, Barbara; Suarez‐Almazor, María E.

doi:10.1097/00005650-200307000-00003

Cited by 132 publications

(154 citation statements)

References 34 publications

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“…When we compared the study by Kaplan et al with our data, we observed very similar correlations between the preferences obtained by the tested algorithms and those of the EQ-5D 27 . In the studies that have evaluated other diseases, we also observed good correlations between different indirect measures of preference when compared to measures derived from the SF-36 28,29,30 . Generally, the methods presented very similar behaviors when compared with one another and with the EQ-5D, which suggests the good validity of the construct.…”

Section: Discussionsupporting

confidence: 56%

O questionário SF-6D Brasil: modelos de construção e aplicações em economia da saúde

Campolina¹,

Bortoluzzo²,

Ferraz³

et al. 2010

Rev. Assoc. Med. Bras.

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objectIve. Compare the preference measures derived from the SF-36, based on the two Brazilian versions of the Short Form 6 Dimensions questionnaire -Brazil (SF-6D Brazil). Methods. Observational and transversal study. The following quality of life assessment instruments were applied: HAQ, SF-36, EQ-5D and SF-6D (1998 and 2002 versions). Descriptive statistics and correlation coefficients were used for data analysis. results. The study assessed 200 patients suffering from rheumatoid arthritis, with a mean age of 49.22 years, mean time with the disease of 11.16 years and mean HAQ score of 1.02. Preferences measured by the two versions of the SF-6D and by the EQ-5D showed significant correlations with one another, and Pearson coefficients ranged from 0.59 to 0.88 (p<0.01). conclusIon. The most current version of the SF-6D, based on the 2002 model, was found to be valid when compared to the version initially validated to Brazil and is a questionnaire alternative to assess preferences in economic analyses carried out in health care.

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Section: Discussionsupporting

confidence: 56%

O questionário SF-6D Brasil: modelos de construção e aplicações em economia da saúde

Campolina¹,

Bortoluzzo²,

Ferraz³

et al. 2010

Rev. Assoc. Med. Bras.

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“…These findings are consistent with some studies that report that interventions are associated with similar mean change scores on the EQ-5D and SF-6D, 40,41 although other studies have found that the mean change scores on the two measures do not concur. [21][22][23]39 Thus, we have shown that, even though the EQ-5D has fewer health states with which to describe a person's HRQL, there is no evidence that it is less sensitive than the SF-6D when measuring the loss of HRQL associated with obesity.…”

Section: Discussionmentioning

confidence: 86%

“…These utility measures are based on different health state descriptions and different underlying valuation systems such that there is the potential for each utility measure to assign a different utility score to the same patient, as has been shown previously. [21][22][23] This in turn means that the choice of utility measure is likely to be influential in determining estimates of the effectiveness, and thereby cost-effectiveness, of the same intervention. As a result, it has been suggested that further comparative work be undertaken, particularly in previously less well researched areas, in order to understand better the implications of the choice of utility measure.…”

Section: Introductionmentioning

confidence: 99%

The relationship between body mass index and health-related quality of life: comparing the EQ-5D, EuroQol VAS and SF-6D

et al. 2006

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Background: No other studies have compared the relationship between body mass index (BMI) and health-related quality of life (HRQL) on more than one utility measure. Estimating the HRQL effects of obesity on a (common) utility scale enables the relative cost-effectiveness of interventions designed to alleviate obesity to be estimated. Objective: To examine the relationship between BMI and HRQL according to the EQ-5D, EuroQol visual analogue scale (EQ-VAS) and SF-6D. Methods: Patients aged X45 years at one UK general practice were asked to complete the EQ-5D, EQ-VAS, SF-36 questionnaire (used to derive the SF-6D), and information on their characteristics and co-morbidity. Body mass index was categorized according to the World Health Organization (WHO) recommendations. Regression analysis was used to compare the HRQL of normal BMI patients to the HRQL of patients in other BMI categories, while controlling for patient characteristics and comorbidity. Results: A total of 1865 patients responded (67%), mean BMI 26.0 kg/m 2 , 16% obese (BMIX30). Patients with back pain, hip pain, knee pain, asthma, diabetes or osteoarthritis were also significantly more likely to be obese. After controlling for other factors, compared to normal BMI patients, obese patients had a lower HRQL according to the EQ-5D (Po0.01), EQ-VAS (Po0.001) and SF-6D (Po0.001). Pre-obese patients were not estimated to have a significantly lower HRQL, and underweight patients were only estimated to have a significantly lower HRQL according to the SF-6D. These results arose because, on the EQ-5D, obese patients were found to have significantly more problems with mobility and pain, compared to physical functioning, social functioning and role limitations on the SF-6D. Whereas, according to the SF-6D, underweight patients had significantly more problems on the dimension of role limitation. Conclusion: The EQ-5D, EQ-VAS and SF-6D were in agreement that, relative to a normal BMI, obesity is associated with a lower HRQL, even after controlling for patient characteristics and co-morbidity. These three measures are thereby sensitive to the HRQL effects of obesity and can be used to estimate the cost-effectiveness of interventions designed to alleviate obesity.

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“…3,7,10,26,35,36 This has been found to be true even in patients with low-back pain 7,24,25,27 or in patients with neck pain. 35 Theoretical causes for these differences in- clude dissimilarities in the descriptive components leading to the measurement of distinct constructs, variation in the period of recall, and the use of different valuation methods (time tradeoff for the EQ-5D and chained standard gamble for the SF-6D).…”

Section: Discussionmentioning

confidence: 94%

Estimating EQ-5D values from the Neck Disability Index and numeric rating scales for neck and arm pain

Carreon¹,

Bratcher²,

Das³

et al. 2014

SPI

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Object The Neck Disability Index (NDI) and numeric rating scales (0 to 10) for neck pain and arm pain are widely used cervical spine disease–specific measures. Recent studies have shown that there is a strong relationship between the SF-6D and the NDI such that using a simple linear regression allows for the estimation of an SF-6D value from the NDI alone. Due to ease of administration and scoring, the EQ-5D is increasingly being used as a measure of utility in the clinical setting. The purpose of this study is to determine if the EQ-5D values can be estimated from commonly available cervical spine disease–specific health-related quality of life measures, much like the SF-6D. Methods The EQ-5D, NDI, neck pain score, and arm pain score were prospectively collected in 3732 patients who presented to the authors' clinic with degenerative cervical spine disorders. Correlation coefficients for paired observations from multiple time points between the NDI, neck pain and arm pain scores, and EQ-5D were determined. Regression models were built to estimate the EQ-5D values from the NDI, neck pain, and arm pain scores. Results The mean age of the 3732 patients was 53.3 ± 12.2 years, and 43% were male. Correlations between the EQ-5D and the NDI, neck pain score, and arm pain score were statistically significant (p < 0.0001), with correlation coefficients of −0.77, −0.62, and −0.50, respectively. The regression equation 0.98947 + (−0.00705 × NDI) + (−0.00875 × arm pain score) + (−0.00877 × neck pain score) to predict EQ-5D had an R-square of 0.62 and a root mean square error (RMSE) of 0.146. The model using NDI alone had an R-square of 0.59 and a RMSE of 0.150. The model using the individual NDI items had an R-square of 0.46 and an RMSE of 0.172. The correlation coefficient between the observed and estimated EQ-5D scores was 0.79. There was no statistically significant difference between the actual EQ-5D score (0.603 ± 0.235) and the estimated EQ-5D score (0.603 ± 0.185) using the NDI, neck pain score, and arm pain score regression model. However, rounding off the coefficients to fewer than 5 decimal places produced less accurate results. Conclusions The regression model estimating the EQ-5D from the NDI, neck pain score, and arm pain score accounted for 60% of the variability of the EQ-5D with a relatively large RMSE. This regression model may not be sufficient to accurately or reliably estimate actual EQ-5D values.

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Variation in the Estimation of Quality-adjusted Life-years by Different Preference-based Instruments

Cited by 132 publications

References 34 publications

O questionário SF-6D Brasil: modelos de construção e aplicações em economia da saúde

O questionário SF-6D Brasil: modelos de construção e aplicações em economia da saúde

The relationship between body mass index and health-related quality of life: comparing the EQ-5D, EuroQol VAS and SF-6D

Estimating EQ-5D values from the Neck Disability Index and numeric rating scales for neck and arm pain

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