MGA5 Health Utilities Index: Further Evidence of Responsiveness

Quality adjusted life years (QALYs) are well recognized as a valid measure for outcomes in cost-effectiveness analyses. However, it is difficult to obtain a summary utility score from health status measure such as the SF-36.
OBJECTIVE: To predict a summary utility score (represented by HUI) from the scores on the SF-36.
METHODS: A structural equation framework was applied to data collected from 1992 to 1995 on the Southern California Kaiser Permanente population (n = 5,794). An instrumental variable (IV) method mitigated the endogeneity in estimating the HUI(MarkII). Socioeconomic and disease variables were used as covariates. A split-sample analysis provided cross-validation.
RESULT: This model predicted 33.68% of the observed variance in HUI index scores with an adjusted R²of 0.3335. Observed HUI index scores were distributed with a mean of 0.7963 and std. deviation of 0.1796. Parameter estimates of most of the SF-36 components (except General Health & Social Functioning) showed statistical significance at α= 0.05 level. People with high chronic disease scores were found to have low SF-36 scores, and parameter estimates of this covariate were also found statistically significant at α= 0.05 level in all structural equations. However, all the socioeconomic variables showed statistical insignificance. Comparison of "Forecasting" and "Estimation" sub-samples showed satisfactory results during cross-validation.
CONCLUSION: Result of this study provides a quantitative link between two important measures of health status. The present model can be used to estimate overall health utility summary scores from previous studies using the SF-36.     

A view from the bridge: agreement between the SF-6D utility algorithm and the Health Utilities Index

BACKGROUND: The SF-6D is a new health state classification and utility scoring system based on 6 dimensions ('6D') of the Short Form 36, and permits a "bridging" transformation between SF-36 responses and utilities. The Health Utilities Index, mark 3 (HUI3) is a valid and reliable multi-attribute health utility scale that is widely used. We assessed within-subject agreement between SF-6D utilities and those from HUI3. METHODS: Patients at increased risk of sudden cardiac death and participating in a randomized trial of implantable defibrillator therapy completed both instruments at baseline. Score distributions were inspected by scatterplot and histogram and mean score differences compared by paired t-test. Pearson correlation was computed between instrument scores and also between dimension scores within instruments. Between-instrument agreement was by intra-class correlation coefficient (ICC). RESULTS: SF-6D and HUI3 forms were available from 246 patients. Mean scores for HUI3 and SF-6D were 0.61 (95% CI 0.60-0.63) and 0.58 (95% CI 0.54-0.62) respectively; a difference of 0.03 (p<0.03). Score intervals for HUI3 and SF-6D were (-0.21 to 1.0) and (0.30-0.95). Correlation between the instrument scores was 0.58 (95% CI 0.48-0.68) and agreement by ICC was 0.42 (95% CI 0.31-0.52). Correlations between dimensions of SF-6D were higher than for HUI3. CONCLUSIONS: Our study casts doubt on the whether utilities and QALYs estimated via SF-6D are comparable with those from HUI3. Utility differences may be due to differences in underlying concepts of health being measured, or different measurement approaches, or both. No gold standard exists for utility measurement and the SF-6D is a valuable addition that permits SF-36 data to be transformed into utilities to estimate QALYs. The challenge is developing a better understanding as to why these classification-based utility instruments differ so markedly in their distributions and point estimates of derived utilities.     

Comparing Short Form 6D,Standard Gamble,and Health Utilities Index Mark 2 and Mark 3 utility scores: Results from total hip arthroplasty patients

Objective: The objectives are to compare SF-6D, standard gamble (SG), and Health Utilities Index (HUI) utility scores, compare change scores, and compare responsiveness. Methods: A cohort of osteoarthritis patients referred for total hip arthroplasty (THA) were evaluated at the time of referral and followed until 3months after THA. Patients were assessed using the SF-36, HUI2, HUI3, and the SG. Agreement is assessed using the intra-class correlation (ICC). Responsiveness is assessed using effect size, standardized response mean, and paired t-test. Results: Data was available for 86 patients at baseline and for 63 at both pre- and post-surgery. At baseline mean SF-6D (0.61), SG (0.62), and HUI2 (0.62) scores were similar; the mean HUI3 score (0.52) was lower. Standard deviations were 0.10, 0.32, 0.19, and 0.22. At baseline, agreement between SF-6D and SG scores was 0.13, agreement between SF-6D and HUI2 was 0.47, and agreement between SF-6D and HUI3 was 0.28. Agreement at pre- and post-surgery was similar. The change in scores between post- and pre-surgery was 0.10 for SF-6D, 0.16 for SG, 0.22 for HUI2, and 0.23 for HUI3. Effect sizes were 1.10 for HUI2, 1.08 for HUI3, 1.06 for SF-6D, and 0.48 for the SG. Conclusions: Agreement between SG scores and SF-6D and HUI scores was low. The estimate of change in utility associated with THA was lowest for SF-6D. Additional longitudinal studies to compare utility measures appear to be warranted.     

Comparing short form and RAND physical and mental health summary scores: results from total hip arthroplasty and high-risk primary-care patients

OBJECTIVES: Summary physical health scores for the Short Form (SF) measures are computing using positive weights for physical items and negative weights for mental health items. Mental health summary scores use positive weights for mental items and negative weights for physical. The RAND Health Status Inventory (HSI) measures do not use negative weights. Do these different approaches to scoring matter? The objective was to compare summary scores using both the SF and RAND-HSI. METHODS: SF-36 and the Health Utilities Index Mark 3 (HUI3) were administered to a cohort of patients waiting for elective total hip arthroplasty (THA). SF-12 and HUI3 were administered to a cohort of high-risk primary-care patients. Summary scores were generated and compared. Single-attribute utility scores for emotion in HUI3 were also computed. Canadian and US norms for SF, RAND-HSI, and HUI3 were used to interpret results. RESULTS: For THA patients, mean physical health scores were 28 and 36 for SF and RAND-HSI. Mean mental health scores were 55 and 42. For the primary-care patients, the scores were 34 and 36 for physical and 46 and 40 for mental health. CONCLUSIONS: SF and RAND-HSI provided somewhat similar summary scores in the THA study. However, SF and RAND-HSI mental health scores differed in the primary-care patient cohort and results from HUI3 corroborate the mental health deficits identified by the RAND-HSI. It may be wise for investigators to use both SF and RAND-HSI scoring systems.     

Not all "quality-adjusted life years" are equal

BACKGROUND: There is evidence that utility elicitation methods used in the calculation of quality-adjusted life years (QALYs) yield different results. It is not clear how these differences impact economic evaluations. METHODS: Using a mathematical model incorporating data on efficacy, costs, and utility values, we simulated the experiences of 100,000 hypothetical rheumatoid arthritis patients over 10 years (50,000 exposed to infliximab plus methotrexate [MTX] and 50,000 exposed to MTX alone). QALYs, were derived from the Health Utilities Index 2 and 3 (HUI2 and HUI3), the Short Form 6-D (SF-6D), and the Euroqol 5-D (EQ-5D). Incremental cost-utility ratios were determined using each instrument to calculate QALYs and the results were compared using cost-effectiveness acceptability curves. RESULTS: Using the different utility measurement methods, the mean difference in QALYs between the infliximab plus MTX and MTX groups ranged from a high of 1.95 QALYs (95% CI=1.93-1.97) using the HUI3 to 0.89 QALYs (95% CI=0.88-0.91) using the SF-6D. Adopting the commonly cited value of society's willingness to pay for a QALY of $50,000, 91% of the simulations favored the cost utility of infliximab plus MTX when using the HUI3 to calculate QALYs. However, when using the EQ-5D, HUI2, or the SF-6D utility values to calculate QALYS, the proportion of simulations that favored the cost utility of infliximab were 63%, 45%, and 12%, respectively. CONCLUSION: Depending on the method for determining utility values used in the calculation of QALYs, very different incremental cost-utility ratios are generated.     

Responsiveness of generic health-related quality of life measures in stroke

Objective: To compare five preference-based generic measures of health-related quality of life (HRQOL) in terms of change scores, correlations among change scores, responsiveness, and quality adjusted life-years (QALYs) gained. Design: Observational longitudinal cohort study where clinical measures and self-assessed HRQOL measures were administered to stroke patients at baseline and at 6 months. Patients were categorized as ‘stable’, ‘some improvement’ and ‘large improvement’ using the Barthel Index, Modified Rankin Scale (MRS), and Center for Epidemiologic Studies Depression Scale (CES-D). For each group, paired t -tests and variants of effect size were used to compare the responsiveness of preference-based HRQOL summary scores, including the EQ-5D VAS and index-based score, SF-6D, and Health Utilities Index (HUI) Mark 2 (HUI2) and Mark 3 (HUI3) overall utility scores. Results: Ninety-eight of 124 (79%) patients completed the 6-month follow-up. Change scores of the EQ-Index, HUI2, and HUI3 were strongly correlated with changes in the Barthel Index and MRS, while the EQ-5D VAS had higher correlation with CES-D change scores than the other measures. The SF-6D, HUI3, and EQ-Index were generally more responsive than the HUI2 and EQ-5D Visual analogue scale (EQ-VAS). QALY estimates based on the EQ-5D index and HUI3 were twice as large as estimates based on the SF-6D and HUI2. Conclusions : The results of this study may assist in informing the selection of a preference-based generic HRQOL measure, although choice will also depend on study goals and context. We would caution against the generalization of the study results on responsiveness to conditions when more subtle change is expected.     

A cohort study found the RAND-12 and Health Utilities Index Mark 3 demonstrated construct validity in high-risk primary care patients

OBJECTIVE: The Short Form 12 (SF-12) is widely used in primary care settings. The RAND-12 Health Status Inventory (HSI) and the Health Utilities Index Mark 3 (HUI3) have not been as widely used in such settings. The objective of this study was to examine the construct validity of the RAND-12 and HUI3 in the context of high-risk primary care patients. STUDY DESIGN AND SETTING: The SF-12, HUI2, and HUI3 were administered to a cohort of high-risk primary care patients. RAND-12 summary scores for physical and mental health were generated. Single-attribute utility scores for each dimension of health status and overall health in HUI3 were computed. A priori hypotheses were specified. RESULTS: In general, the relationships among RAND-12 and HUI3 scores were consistent with construct validity. Twelve of 24 a priori predictions were confirmed. However, predictions about the correlations between the number of medical conditions and the number of medications and the measures of health-related quality of life were, in general, not confirmed. CONCLUSIONS: The RAND-12 and HUI3 seem to be useful among primary care patients with diverse chronic conditions. Further investigation is warranted.     

The feasibility and responsiveness of the health utilities index in patients with early-stage breast cancer: A prospective longitudinal study

Background The health utilities index (HUI3) is a health measurement instrument based on individuals’ preferences for different health states. Breast cancer (BC) is common, with a high proportion of long-term survivors, making evaluation of treatment effects important. Feasibility and responsiveness of HUI3 was compared to the short-form 36 (SF-36) in patients with BC. Methods HUI3 and SF-36 were administered eight times: at initial surgical consultation, 1 week before surgery; 1 week, 3, 6, 12, 18, and 24 months after surgery. Effect size, analysis of variance, and Pearson product moment correlations were calculated. BC data were compared to normative values. Results Eighty-five patients were enrolled. Ninety-one percent of planned assessments were completed. HUI3 showed significant responsiveness (P < 0.01) after surgery and during recovery. HUI3 scores correlated with SF-36 scores. Comparison to normative data demonstrated the significant detrimental effect of BC diagnosis. Results showed long-term effects of treatment on physical health and positive effects on mental/emotional health in BC survivors. Conclusion(s) HUI3 was found to be feasible and responsive in our cohort of BC patients. Changes in HUI3 values over time, and compared to normative data, paralleled SF-36 scores. HUI3 is a valuable tool in health-related quality of life and cost-utility studies in patients with BC.     

Comparison of preference-based utilities of the Short-Form 36 Health Survey and Health Utilities Index before and after treatment of patients with intermittent claudication.

The authors compared SF-36 utilities with Health Utilities Index (HUI) utilities (HUI2 and HUI3) assessed in patients with intermittent claudication. A total of 87 patients with intermittent claudication completed the SF-36 and HUI before and 1, 3, and 12 months after revascularization. Utilities were estimated using SF-36 and HUI published algorithms (i.e., both algorithms were based on standard-gamble utilities assessed in random samples of the general population). The utilities were compared using repeated-measures multivariate analysis of variance, paired t tests, and univariate linear regression analyses. Before treatment, the mean SF-36 and HUI3 utilities were the same (0.66 vs. 0.66, P = 0.92) and less than the mean HUI2 utility (0.70, P = 0.02). After treatment, all utilities showed improvement from before treatment (P < 0.05); the gain in utilities from treatment was lowest when using the SF-36 (e.g., 0.74, 0.80, 0.77 at 3 months for the SF-36, HUI2, and HUI3, respectively). The correlations of changes over time of the SF-36 with HUI2 utilities and of the SF-36 with HUI3 utilities were 0.39 and 0.49, respectively. The relationships between the SF-36 and HUI2 or HUI3 utilities were moderate to good (i.e., range-adjusted R2 = 31% to 72%). The results suggest that SF-36 data can be transformed to preference-based utilities and be used for economic evaluation in health care. The gain in utilities from treatment, however, was less for SF-36 utilities than for HUI utilities.     

Relationship between health status and utility measures in older claudicants

The purpose of this study was to examine the relationship between health status and health utility measures in 34 older claudicants and to determine which attributes of health status were significant predictors of health state valuation/preference. The MOS SF-36 was used to assess health status and the rating scale and multiattribute Health Utility Index (HUI) were used to assess utility scores. With regard to health status, the bodily pain and physical functioning subscales contributed the most to reductions in quality of life (QoL) with mean subscale scores substantially lower than reported population norms. Patients rated their health status approximately one-third below a state of perfect health on both utility measures. Moderate correlations were observed between the MOS SF-36 subscale scores and the HUI and rating scale scores. In multivariable regression models, physical functioning and mental health were the best predictors of HUI scores, whereas general health and vitality were the best predictors of rating scale scores. Approximately 50% of the variance in utility scores was explained by these attributes. This study provides further documentation that bodily pain and reductions in physical function contribute to reductions in QoL in older patients with intermittent claudication. Other attributes of health status, however, notably psychological distress, were predictive of patients' preference for health states. Recognized constructs of physical and mental health explained the substantial variation in the utility/preference assessment in this population. Furthermore, these data are consistent with those reported in the Dutch Iliac Stent Trial.     

Comparing the Health Utilities Index Mark 3 (HUI3) with the Short Form-36 Preference-Based SF-6D in Chronic Kidney Disease

Objective:  Assess within-subject agreement and compare discriminative abilities between the SF-6D and the Health Utilities Index Mark 3 (HUI3) in patients with chronic kidney disease (CKD).
Methods:  The HUI3 and Short Form-36 were self-completed by 185 CKD patients enrolled in a prospective study of incident patients with stage 4 and 5 CKD.
Results:  The mean preference-based score for the SF-6D was 0.67 ± 0.13 compared to 0.58 ± 0.26 for the HUI3 ( P  < 0.01). There was a strong association between SF-6D and HUI3 scores (Pearson correlation coefficient 0.55, 95% CI 0.43–0.65) and moderate agreement with an intraclass correlation coefficient of 0.44. The HUI3 was better able to capture more severe burden of illness with fewer floor effects. The SF-6D was better at capturing differences among patients at the top range of the scale with fewer ceiling effects. Both the HUI3 and SF-6D were able to discriminate between patient groups differing in disease severity defined as predialysis versus dialysis dependent and depressive symptoms using a Beck Depression Inventory II score of ≥14 as the cutoff. The HUI3 was better able to discriminate greater depressive symptoms.
Conclusion:  The SF-6D and the HUI3 generate different preference-based scores for patients with CKD and any comparison between their scores should be made with caution. The HUI3 appears more suitable for measuring the health of populations with greater disability such as patients with CKD. It remains to be determined whether these differences will remain when one compares within-instrument differences in preference scores over time.     

Predicting the Short Form-6D Preference-Based Index Using the Eight Mean Short Form-36 Health Dimension Scores: Estimating Preference-Based Health-Related Utilities When Patient Level Data Are not Available

Objective:  The objective is to derive an algorithm to predict a cohort preference-based short form-6D (short form-6D) score using the eight mean health dimension scores from the short form-36 (SF-36) when patient level data are not available.
Methods:  Health-related quality of life data (N = 6890) covering a wide range of health conditions was used to explore the relationship between the SF-6D and the eight health dimension scores. Models obtained using ordinary least square regressions were compared for goodness of fit and predictive abilities on both within-sample subgroups and out-of-sample published data sets.
Results:  The models explained more than 83% of the variance in the individual SF-6D scores with a mean absolute error of 0.040. When using mean health dimension scores from within-sample subgroups and out-of-sample published data sets, the majority of predicted scores were well within the minimal important difference (0.041) for the SF-6D.
Conclusions:  This article presents a mechanism to estimate a mean cohort preference-based SF-6D score using the eight mean health dimension scores of the SF-36. Using published summary statistics, the out-of-sample validation demonstrates that the algorithms can be used to inform both clinical and economic research. Further research is required in different health conditions.     

Is the Health Utilities Index responsive in total hip arthroplasty patients?

OBJECTIVE: The purpose is to examine the responsiveness of the Health Utilities Index Mark 2 (HUI2), Mark 3 (HUI3), and other generic and disease-specific measures in osteoarthritis patients undergoing total hip arthroplasty (THA). METHODS: Ninety patients (mean age=68.13; SD=8.15) on a waiting list for THA completed measures that included the standard gamble, HUI2, HUI3, SF-36, Harris Hip Scale, WOMAC, and MACTAR. before and after THA. Responsiveness statistics (effect size, standardized response mean, Guyatt's responsiveness statistic, paired-sample t-tests, and relative efficiency statistic) were calculated. RESULTS: The disease-specific measures were more responsive than the generic measures. Rankings of the degree of responsiveness varied depending on the responsiveness statistic used. CONCLUSIONS: Disease-specific measures are the most responsive in THA patients. However, the SF-36, HUI2, and HUI3 had summary scores and domain/attributes scores that were also responsive and provided additional information. Among the generic measures, HUI3 was the most responsive.     

Using the Multiple Sclerosis Impact Scale to Estimate Health State Utility Values: Mapping from the MSIS-29, Version 2, to the EQ-5D and the SF-6D

ObjectivesThe 29-item Multiple Sclerosis Impact Scale (MSIS-29) is a psychometrically validated patient-reported outcome measure increasingly used in trials of treatments for multiple sclerosis. However, it is non–preference-based and not amenable for use across policy decision-making contexts. Our objective was to statistically map from the MSIS-29, version 2, to the EuroQol five-dimension (EQ-5D) and the six-dimension health state short form (derived from short form 36 health survey) (SF-6D) to estimate algorithms for use in cost-effectiveness analyses.MethodsThe relationships between MSIS-29, version 2, and EQ-5D and SF-6D scores were estimated by using data from a cohort of people with multiple sclerosis in South West England (n=672). Six ordinary least squares (OLS), Tobit, and censored least adjusted deviation (CLAD) regression analyses were conducted on estimation samples, including the use of subscale and item scores, squared and interaction terms, and demographics. Algorithms from models with the smallest estimation errors (mean absolute error [MAE], root mean square error [RMSE], normalized RMSE) were then assessed by using separate validation samples.ResultsTobit and CLAD. For the EQ-5D, the OLS models including subscale squared terms, and item scores and demographics performed comparably (MAE 0.147, RMSE 0.202 and MAE 0.147, RMSE 0.203, respectively), and estimated scores well up to 3 years post-baseline. Estimation errors for the SF-6D were smaller (OLS model including squared terms: MAE 0.058, RMSE 0.073; OLS model using item scores and demographics: MAE 0.059, RMSE 0.08), and the errors for poorer health states found with the EQ-5D were less pronounced.ConclusionsWe have provided algorithms for the estimation of health state utility values, both the EQ-5D and SF-6D, from scores on the MSIS-29, version 2. Further research is now needed to determine how these algorithms perform in practical decision-making contexts, when compared with observed EQ-5D and SF-6D values.     

A Study of the Construct Validity of the Health Utilities Index Mark 3 (HUI3) in Patients with Schizophrenia

This study assessed the construct validity of the Health Utilities Index Mark 3 (HUI3) in patients with schizophrenia. Patients with schizophrenia recruited from a tertiary mental hospital in Singapore completed the HUI3, the Short-Form 36 Health Survey (SF-36) and the Schizophrenia Quality of Life Scale (SQLS). Patients were assessed for presence and absence of 22 common psychiatric symptoms. Construct validity was assessed using 6 a priori hypotheses. Two hundred and two patients (mean age: 37.8 years, female: 52%) completed the survey. As hypothesized, overall HUI3 utility scores were correlated with SF-36 measures (Spearman’s rho: 0.19 to 0.51), SQLS scales (Spearman’s rho: −0.56 to −0.36), and the number of psychiatric symptoms (Spearman’s rho: −0.49). The HUI3 emotion attribute was moderately correlated with SF-36 mental health (Spearman’s rho: 0.45) and SQLS psychosocial scales (Spearman’s rho: −0.43), and HUI3 pain attribute was strongly correlated with SF-36 bodily pain scale (Spearman’s rho: 0.58). The mean HUI3 overall, emotion, cognition, and speech scores for patients with schizophrenia were 0.07, 0.09, 0.04 and 0.04 points lower than respective age-, sex- and ethnicity-adjusted population norms (p<0.001 for all, ANCOVA). This study provides evidence for the construct validity of the HUI3 in patients with schizophrenia.     

The Impact of Differences in EQ-5D and SF-6D Utility Scores on the Acceptability of Cost–Utility Ratios: Results across Five Trial-Based Cost–Utility Studies

ObjectiveThis article investigates whether differences in utility scores based on the EQ-5D and the SF-6D have impact on the incremental cost–utility ratios in five distinct patient groups.MethodsWe used five empirical data sets of trial-based cost–utility studies that included patients with different disease conditions and severity (musculoskeletal disease, cardiovascular pulmonary disease, and psychological disorders) to calculate differences in quality-adjusted life-years (QALYs) based on EQ-5D and SF-6D utility scores. We compared incremental QALYs, incremental cost–utility ratios, and the probability that the incremental cost–utility ratio was acceptable within and across the data sets.ResultsWe observed small differences in incremental QALYs, but large differences in the incremental cost–utility ratios and in the probability that these ratios were acceptable at a given threshold, in the majority of the presented cost–utility analyses. More specifically, in the patient groups with relatively mild health conditions the probability of acceptance of the incremental cost–utility ratio was considerably larger when using the EQ-5D to estimate utility. While in the patient groups with worse health conditions the probability of acceptance of the incremental cost–utility ratio was considerably larger when using the SF-6D to estimate utility.ConclusionsMuch of the appeal in using QALYs as measure of effectiveness in economic evaluations is in the comparability across conditions and interventions. The incomparability of the results of cost–utility analyses using different instruments to estimate a single index value for health severely undermines this aspect and reduces the credibility of the use of incremental cost–utility ratios for decision-making.     

Development and testing of the UK SF-12 (short form health survey)

OBJECTIVES: The 36 item short form health survey (SF-36) has proved to be of use in a variety of settings where a short generic health measure of patient-assessed outcome is required. This measure can provide an eight dimension profile of health status, and two summary scores assessing physical function and mental well-being. The developers of the SF-36 in America have developed algorithms to yield the two summary component scores in a questionnaire containing only one-third of the original 36 items, the SF-12. This paper documents the construction of the UK SF-12 summary measures from a large-scale dataset from the UK in which the SF-36, together with other questions on health and lifestyles, was sent to randomly selected members of the population. Using these data we attempt here to replicate the findings of the SF-36 developers in the UK setting, and then to assess the use of SF-12 summary scores in a variety of clinical conditions. METHODS: Factor analytical methods were used to derive the weights used to construct the physical and mental component scales from the SF-36. Regression methods were used to weight the 12 items recommended by the developers to construct the SF-12 physical and mental component scores. This analysis was undertaken on a large community sample (n = 9332), and then the results of the SF-36 and SF-12 were compared across diverse patient groups (Parkinson's disease, congestive heart failure, sleep apnoea, benign prostatic hypertrophy). RESULTS: Factor analysis of the SF-36 produced a two factor solution. The factor loadings were used to weight the physical component summary score (PCS-36) and mental component summary score (MCS-36). Results gained from the use of these measures were compared with results gained from the PCS-12 and MCS-12, and were found to be highly correlated (PCS: rho = 0.94, p < 0.001; MCS: rho = 0.96, p < 0.001), and produce remarkably similar results, both in the community sample and across a variety of patient groups. CONCLUSIONS: The SF-12 is able to produce the two summary scales originally developed from the SF-36 with considerable accuracy and yet with far less respondent burden. Consequently, the SF-12 may be an instrument of choice where a short generic measure providing summary information on physical and mental health status is required.     

How should we evaluate health status? A comparison of three methods in patients presenting with obstructive sleep apnoea

The purpose of this paper is to compare three approaches to the measurement of patient-reported health status which produce summary scales of health status: the Patient-generated Index (PGI) is a measure of individual quality of life (QoL), the EuroQol is a measure of QoL the results of which are weighted by utility values gained from community surveys and the SF-36 which produces two summary scales of health status (the physical component summary (PCS) and the mental component summary (MCS) scores). A follow-up interview survey of patients with obstructive sleep apnoea (OSA) was conducted. The patients received continuous positive airways pressure therapy (CPAP) between the two administrations of the questionnaires. One hundred patients presenting with OSA and who were suitable for CPAP therapy were asked if they would take part in the study. The results on the PGI, EuroQol EQ-5D utility weighted scores and thermometer scores and SF-36 physical and mental summary scores were measured. Eighty-nine respondents provided sufficient data to calculate PGI and EuroQol scores and 86 patients provided sufficient data to calculate SF-36 summary scores. The PGI indicated substantial improvement after CPAP treatment whereas the EuroQol indicated little or no improvement on either utility weighted or thermometer scores. The SF-36 PCS and MCS scores were lower than those of the general population at baseline, but had improved to the normative levels after treatment. The EuroQol provided a substantially different picture of change to either of the ones gained from the SF-36 or PGI. It is suggested that the EuroQol does not contain questions which relate to important aspects of health and well-being and may not accurately reflect the health state of individuals. Consequently, caution must be exercised to assure that an appropriate instrument has been employed when using health outcomes data to assess or prioritize available health care treatments.     

The effect of weight loss on changes in health-related quality of life among overweight and obese women with urinary incontinence

Objective

To estimate the effect of change in weight and change in urinary incontinence (UI) frequency on changes in preference-based measures of health-related quality of life (HRQL) among overweight and obese women with UI participating in a weight loss trial.

Methods

We conducted a longitudinal cohort analysis of 338 overweight and obese women with UI enrolled in a randomized clinical trial comparing a behavioral weight loss intervention to an educational control condition. At baseline, 6, and 18?months, health utilities were estimated using the Health Utilities Index Mark 3 (HUI3), a transformation of the SF-36 to the preference-based SF-6D, and the estimated Quality of Well-Being (eQWB) score (a summary calculated from the SF-36 physical functioning, mental health, bodily pain, general health perceptions, and role limitations?Cphysical subscale scores). Potential predictors of changes in these outcomes were examined using generalized estimating equations.

Results

In adjusted multivariable models, weight loss was associated with improvement in HUI3, SF-6D, and eQWB at 6 and 18?months (P?<?0.05). Increases in physical activity also were independently associated with improvement in HUI3 (P?=?0.01) and SF-6D (P?=?0.006) scores at 18?months. In contrast, reduction in UI frequency did not predict improvements in HRQL at 6 or 18?months.

Conclusion

Weight loss and increased physical activity, but not reduction in UI frequency, were strongly associated with improvements in health utilities measured by the HUI3, SF-6D, and eQWB. These findings provide important information that can be used to inform cost?Cutility analyses of weight loss interventions.