What is the relationship between the minimally important difference and health state utility values? The case of the SF-6D

BACKGROUND: The SF-6D is a new single summary preference-based measure of health derived from the SF-36. Empirical work is required to determine what is the smallest change in SF-6D scores that can be regarded as important and meaningful for health professionals, patients and other stakeholders. OBJECTIVES: To use anchor-based methods to determine the minimally important difference (MID) for the SF-6D for various datasets. METHODS: All responders to the original SF-36 questionnaire can be assigned an SF-6D score provided the 11 items used in the SF-6D have been completed. The SF-6D can be regarded as a continuous outcome scored on a 0.29 to 1.00 scale, with 1.00 indicating "full health". Anchor-based methods examine the relationship between an health-related quality of life (HRQoL) measure and an independent measure (or anchor) to elucidate the meaning of a particular degree of change. One anchor-based approach uses an estimate of the MID, the difference in the QoL scale corresponding to a self-reported small but important change on a global scale. Patients were followed for a period of time, then asked, using question 2 of the SF-36 as our global rating scale, (which is not part of the SF-6D), if there general health is much better (5), somewhat better (4), stayed the same (3), somewhat worse (2) or much worse (1) compared to the last time they were assessed. We considered patients whose global rating score was 4 or 2 as having experienced some change equivalent to the MID. In patients who reported a worsening of health (global change of 1 or 2) the sign of the change in the SF-6D score was reversed (i.e. multiplied by minus one). The MID was then taken as the mean change on the SF-6D scale of the patients who scored (2 or 4). RESULTS: This paper describes the MID for the SF-6D from seven longitudinal studies that had previously used the SF-36. CONCLUSIONS: From the seven reviewed studies (with nine patient groups) the MID for the SF-6D ranged from 0.010 to 0.048, with a weighted mean estimate of 0.033 (95% CI: 0.029 to 0.037). The corresponding Standardised Response Means (SRMs) ranged from 0.11 to 0.48, with a mean of 0.30 and were mainly in the "small to moderate" range using Cohen's criteria, supporting the MID results. Using the half-standard deviation (of change) approach the mean effect size was 0.051 (range 0.033 to 0.066). Further empirical work is required to see whether or not this holds true for other patient groups and populations

Exploring the consistency of the SF-6D

Objective: The six dimensional health state short form (SF-6D) was designed to be derived from the short-form 36 health survey (SF-36). The purpose of this research was to compare the SF-6D index values generated from the SF 36 (SF-6D(SF-36)) with those obtained from the SF-6D administered as an independent instrument (SF-6D(Ind)). The goal was to assess the consistency of respondents answers to these two methods of deriving the SF-6D. Methods: Data were obtained from a sample of the Portuguese population (n = 414). Agreement between the instruments was assessed on the basis of a descriptive system and their indexes. The analysis of the descriptive system was performed by using a global consistency index and an identically classified index. Agreement was also explored by using correlation coefficients. Parametric tests were used to identify differences between the indexes. Regression models were estimated to understand the relationship between them. Results: The SF-6D(Ind) generates higher values than does the SF-6D(SF-36), There were significant differences between the indexes across sociodemographic groups. There was a significant ceiling effect in the SF-6D(Ind) a but not in the SF-6D(SF-36). The correlation between the indexes was high but less than what was anticipated. The global consistency index identified the dimensions with larger differences. Considerable differences were found in two dimensions, possibly as a result of different item contexts. Further research is needed to fully understand the role of the different layouts and the length of the questionnaires in the respondents' answers. Conclusions: The results show that as the SF-6D was designed to derive utilities from the SF-36 it should be used in this way and not as an independent instrument.Fundacao para a Ciencia e a Tecnologia (FCT

Estimating a preference-based index from the Japanese SF-36

Objective: The main objective of the study was to estimate a preference-bascd Short Form (SF)-6D index from the SF-36 for Japan and compare it with the UK results. Study Design and Setting: The SF-6D was translated into Japanese. Two hundred and forty-nine health states defined by this version of the SF-6D were then valued by a representative sample of 600 members of the Japanese general population using standard gamble (SG). These health-state values were modeled using classical parametric random-effect methods with individual-level data and ordinary least squares (OLS) on mean health-state values, together with a new nonparametric approach using Bayesian methods of estimation. Results: All parametric models estimated on Japanese data were found to perform less well than their UK counterparts in terms of poorer goodness of fit, more inconsistencies, larger prediction errors and bias, and evidence of systematic bias in the predictions. Nonparametric models produce a substantial improvement in out-of-sample predictions. The physical, role, and social dimensions have relatively larger decrements than pain and mental health compared with those in the United Kingdom. Conclusion: The differences between Japanese and UK valuations of the SF-6D make it important to use the Japanese valuation data set estimated using the nonparametric Bayesian technique presented in this article. (C) 2009 Elsevier Inc. All rights reserved

Using Rasch analysis to form plausible health states amenable to valuation: the development of CORE-6D from CORE-OM in order to elicit preferences for common mental health problems

Purpose: To describe a new approach for deriving a preference-based index from a condition specific measure that uses Rasch analysis to develop health states. Methods: CORE-OM is a 34-item instrument monitoring clinical outcomes of people with common mental health problems. CORE-OM is characterised by high correlation across its domains. Rasch analysis was used to reduce the number of items and response levels in order to produce a set of unidimensionally-behaving items, and to generate a credible set of health states corresponding to different levels of symptom severity using the Rasch item threshold map. Results: The proposed methodology resulted in the development of CORE-6D, a 2-dimensional health state description system consisting of a unidimensionally-behaving 5-item emotional component and a physical symptom item. Inspection of the Rasch item threshold map of the emotional component helped identify a set of 11 plausible health states, which, combined with the physical symptom item levels, will be used for the valuation of the instrument, resulting in the development of a preference-based index. Conclusions: This is a useful new approach to develop preference-based measures where the domains of a measure are characterised by high correlation. The CORE-6D preference-based index will enable calculation of Quality Adjusted Life Years in people with common mental health problems

Carbon loss by water erosion in drylands: Implications from a study of vegetation change in the south-west USA

Journal ArticleSoil organic carbon (SOC) is an important component of the global carbon cycle yet is rarely quantified adequately in terms of its spatial variability resulting from losses of SOC due to erosion by water. Furthermore, in drylands, little is known about the effect of widespread vegetation change on changes in SOC stores and the potential for water erosion to redistribute SOC around the landscape especially during high-magnitude run-off events (flash floods). This study assesses the change in SOC stores across a shrub-encroachment gradient in the Chihuahuan Desert of the south-west USA. A robust estimate of SOC storage in surface soils is presented, indicating that more SOC is stored beneath vegetation than in bare soil areas. In addition, the change in SOC storage over a shrub-encroachment gradient is shown to be nonlinear and highly variable within each vegetation type. Over the gradient of vegetation change, the heterogeneity of SOC increases, and newer carbon from C3 plants becomes dominant. This increase in the heterogeneity of SOC is related to an increase in water erosion and SOC loss from inter-shrub areas, which is self-reinforcing. Shrub-dominated drylands lose more than three times as much SOC as their grass counterparts. The implications of this study are twofold: (1) quantifying the effects of vegetation change on carbon loss via water erosion and the highly variable effects of land degradation on soil carbon stocks is critical. (2) If landscape-scale understanding of carbon loss by water erosion in drylands is required, studies must characterize the heterogeneity of ecosystem structure and its effects on ecosystem function across ecotones subject to vegetation change. © 2013 John Wiley & Sons, Ltd.NS

Biotic and abiotic changes in ecosystem structure over a shrub-encroachment gradient in the southwestern USA.

publication-status: Publishedtypes: Article© 2010 Springer Verlag. This is a post print version of the article. The final publication is available at link.springer.comIn this study, we investigate changes in ecosystem structure that occur over a gradient of land-degradation in the southwestern USA, where shrubs are encroaching into native grassland. We evaluate a conceptual model which posits that the development of biotic and abiotic structural connectivity is due to ecogeomorphic feedbacks. Three hypotheses are evaluated: 1. Over the shrub-encroachment gradient, the difference in soil properties under each surface-cover type will change non-linearly, becoming increasingly different; 2. There will be a reduction in vegetation cover and an increase in vegetation-patch size that is concurrent with an increase in the spatial heterogeneity of soil properties over the shrub-encroachment gradient; and 3. Over the shrub-encroachment gradient, the range at which soil properties are autocorrelated will progressively exceed the range at which vegetation is autocorrelated. Field-based monitoring of vegetation and soil properties was carried out over a shrub-encroachment gradient at the Sevilleta National Wildlife Refuge in New Mexico, USA. Results of this study show that vegetation cover decreases over the shrub-encroachment gradient, but vegetation-patch size increases, with a concurrent increase in the spatial heterogeneity of soil properties. Typically, there are significant differences in soil properties between non-vegetated and vegetated surfaces, but for grass and shrub patches, there are only significant differences for the biotic soil properties. Results suggest that it is the development of larger, well-connected, non-vegetated patches that is most important in driving the overall behavior of shrub-dominated sites. Results of this study support the hypothesis that feedbacks of functional connectivity reinforce the development of structural connectivity, which increases the resilience of the shrub-dominated state, and thus makes it harder for grasses to re-establish and reverse the vegetation change

Mapping onto Eq-5 D for patients in poor health

<p>Abstract</p> <p>Background</p> <p>An increasing amount of studies report mapping algorithms which predict EQ-5 D utility values using disease specific non-preference-based measures. Yet many mapping algorithms have been found to systematically overpredict EQ-5 D utility values for patients in poor health. Currently there are no guidelines on how to deal with this problem. This paper is concerned with the question of why overestimation of EQ-5 D utility values occurs for patients in poor health, and explores possible solutions.</p> <p>Method</p> <p>Three existing datasets are used to estimate mapping algorithms and assess existing mapping algorithms from the literature mapping the cancer-specific EORTC-QLQ C-30 and the arthritis-specific Health Assessment Questionnaire (HAQ) onto the EQ-5 D. Separate mapping algorithms are estimated for poor health states. Poor health states are defined using a cut-off point for QLQ-C30 and HAQ, which is determined using association with EQ-5 D values.</p> <p>Results</p> <p>All mapping algorithms suffer from overprediction of utility values for patients in poor health. The large decrement of reporting 'extreme problems' in the EQ-5 D tariff, few observations with the most severe level in any EQ-5 D dimension and many observations at the least severe level in any EQ-5 D dimension led to a bimodal distribution of EQ-5 D index values, which is related to the overprediction of utility values for patients in poor health. Separate algorithms are here proposed to predict utility values for patients in poor health, where these are selected using cut-off points for HAQ-DI (> 2.0) and QLQ C-30 (< 45 average of QLQ C-30 functioning scales). The QLQ-C30 separate algorithm performed better than existing mapping algorithms for predicting utility values for patients in poor health, but still did not accurately predict mean utility values. A HAQ separate algorithm could not be estimated due to data restrictions.</p> <p>Conclusion</p> <p>Mapping algorithms overpredict utility values for patients in poor health but are used in cost-effectiveness analyses nonetheless. Guidelines can be developed on when the use of a mapping algorithms is inappropriate, for instance through the identification of cut-off points. Cut-off points on a disease specific questionnaire can be identified through association with the causes of overprediction. The cut-off points found in this study represent severely impaired health. Specifying a separate mapping algorithm to predict utility values for individuals in poor health greatly reduces overprediction, but does not fully solve the problem.</p

Development and validation of a preference based measure derived from the Cambridge Pulmonary Hypertension Outcome Review (CAMPHOR) for use in cost utility analyses

<p>Abstract</p> <p>Background</p> <p>Pulmonary Hypertension is a severe and incurable disease with poor prognosis. A suite of new disease-specific measures – the Cambridge Pulmonary Hypertension Outcome Review (CAMPHOR) – was recently developed for use in this condition. The purpose of this study was to develop and validate a preference based measure from the CAMPHOR that could be used in cost-utility analyses.</p> <p>Methods</p> <p>Items were selected that covered major issues covered by the CAMPHOR QoL scale (activities, travelling, dependence and communication). These were used to create 36 health states that were valued by 249 people representative of the UK adult population, using the time trade-off (TTO) technique. Data from the TTO interviews were analysed using both aggregate and individual level modelling. Finally, the original CAMPHOR validation data were used to validate the new preference based model.</p> <p>Results</p> <p>The predicted health state values ranged from 0.962 to 0.136. The mean level model selected for analyzing the data had good explanatory power (0.936), did not systematically over- or underestimate the observed mean health state values and showed no evidence of auto correlation in the prediction errors. The value of less than 1 reflects a background level of ill health in state 1111, as judged by the respondents. Scores derived from the new measure had excellent test-retest reliability (0.85) and construct validity. The CAMPHOR utility score appears better able to distinguish between WHO functional classes (II and III) than the EQ-5D and SF-6D.</p> <p>Conclusion</p> <p>The tariff derived in this study can be used to classify an individual into a health state based on their responses to the CAMPHOR. The results of this study widen the evidence base for conducting economic evaluations of interventions designed to improve QoL for patients with PH.</p

Streambed scour and fill in low‐order dryland channels

Reproduced with permission of the publisher. ©2005. American Geophysical UnionDistributions of scour and fill depths recorded in three low‐order sand bed dryland rivers were compared with the Weibull, gamma, exponential, and lognormal probability density functions to determine which model best describes the reach‐scale variability in scour and fill. Goodness of fit tests confirm that the majority of scour distributions conform to the one‐parameter exponential model at the 95% significance level. The positive relationship between exponential model parameters and flow strength provides a means to estimate streambed scour depths, at least to a first approximation, in comparable streams. In contrast, the majority of the fill distributions do not conform to the exponential model even though depths of scour and fill are broadly similar. The disparities between the distributions of scour and fill raise questions about notions of channel equilibrium and about the role of scour and fill in effecting channel change

Deriving a Preference-Based Measure for Myelofibrosis from the EORTC QLQ-C30 and the MF-SAF

AbstractBackgroundUtility values are required for economic evaluation using cost-utility analyses. Often, generic measures such as the EuroQol five-dimensional questionnaire are used, but this may not appropriately reflect the health-related quality of life of patients with cancer including myelofibrosis.ObjectiveTo derive a condition-specific preference-based measure for myelofibrosis using appropriate existing measures, the Myelofibrosis-Symptom Assessment Form and the European Organisation for Research and Treatment of Cancer Quality of Life 30 Questionnaire.MethodsData from the Controlled Myelofibrosis Study with Oral JAK Inhibitor Treatment trial (n = 309) were used to derive the health state classification system. Psychometric and factor analyses were used to determine the dimensions of the classification system. Psychometric and Rasch analyses were then used to select an item to represent each dimension. Item selection was validated with experts. A selection of health states was valued by members of the general population using time trade-off. Finally, health state values were modeled using regression analysis to produce utility values for every state.ResultsThe Myelofibrosis 8 dimensions has eight dimensions: physical functioning, emotional functioning, fatigue, itchiness, pain under ribs on the left side, abdominal discomfort, bone or muscle pain, and night sweats. Regression models were estimated using time trade-off data from 246 members of the general population valuing a total of 33 states. The best performing model was a random effects maximum likelihood model producing utility values ranging from 0.089 to 1.ConclusionsThe Myelofibrosis 8 dimensions is a condition-specific preference-based measure for myelofibrosis. This measure can be used to generate utility values for myelofibrosis for any data set containing the Myelofibrosis-Symptom Assessment Form and the European Organisation for Research and Treatment of Cancer Quality of Life 30 Questionnaire data