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

Deriving preference-based single indices from non-preference based condition-specific instruments: converting AQLQ into EQ5D indices

Suppose that one has a clinical dataset with only non-preference-based QOL data, and that one nevertheless would like to perform a cost/QALY analysis. This study reports on some efforts to establish a “mapping” relationship between AQLQ (a non-preference-based QOL instrument for asthma) and EQ5D (a preference-based generic instrument). Various methods are described in terms of associated assumptions regarding the measurement properties of the instruments. This is followed by empirical mapping, based on regressing EQ5D on AQLQ. Six main regression models and two supplementary models are identified, and the regressions carried out. Performance of each model is explored in terms of goodness of fit between observed and predicted values, and of robustness of predictions on external data. The results show that it is possible to predict mean EQ5D indices given AQLQ data. The general implications for methods of mapping non-preference-based instruments onto preference-based measures are discussed.EQ5D; AQLQ; mapping

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

Deriving preference-based single indices from non-preference based condition-specific instruments: Converting AQLQ into EQ5D indices

Suppose that one has a clinical dataset with only non-preference-based QOL data, and that one nevertheless would like to perform a cost/QALY analysis. This study reports on some efforts to establish a "mapping" relationship between AQLQ (a non-preference-based QOL instrument for asthma) and EQ5D (a preference-based generic instrument). Various methods are described in terms of associated assumptions regarding the measurement properties of the instruments. This is followed by empirical mapping, based on regressing EQ5D on AQLQ. Six main regression models and two supplementary models are identified, and the regressions carried out. Performance of each model is explored in terms of goodness of fit between observed and predicted values, and of robustness of predictions on external data. The results show that it is possible to predict mean EQ5D indices given AQLQ data. The general implications for methods of mapping non-preference-based instruments onto preference-based measures are discussed

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

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

A Topological Investigation of Phase Transitions of Cascading Failures in Power Grids

Cascading failures are one of the main reasons for blackouts in electric power transmission grids. The economic cost of such failures is in the order of tens of billion dollars annually. The loading level of power system is a key aspect to determine the amount of the damage caused by cascading failures. Existing studies show that the blackout size exhibits phase transitions as the loading level increases. This paper investigates the impact of the topology of a power grid on phase transitions in its robustness. Three spectral graph metrics are considered: spectral radius, effective graph resistance and algebraic connectivity. Experimental results from a model of cascading failures in power grids on the IEEE power systems demonstrate the applicability of these metrics to design/optimize a power grid topology for an enhanced phase transition behavior of the system

Integrating Peer-to-Peer Networking and Computing in the AgentScape Framework

The combination of peer-to-peer networking and agentbased computing seems to be a perfect match. Agents are cooperative and communication oriented, while peerto -peer networks typically support distributed systems in which all nodes have equal roles and responsibilities. AgentScape is a framework designed to support large-scale multi-agent systems. Pole extends this framework with peerto -peer computing. This combination facilitates the development and deployment of new agent-based peer-to-peer applications and services