Dataset Information

Modeling SF-6D Health Utilities: Is Bayesian Approach Appropriate?

ABSTRACT: Valuation studies of preference-based health measures like SF6D have been conducted in many countries. However, the cost of conducting such studies in countries with small populations or low- and middle-income countries (LMICs) can be prohibitive. There is potential to use results from readily available countries' valuations to produce better valuation estimates. Data from Lebanon and UK SF-6D value sets were analyzed, where values for 49 and 249 health states were extracted from samples of Lebanon and UK populations, respectively, using standard gamble techniques. A nonparametric Bayesian model was used to estimate a Lebanon value set using the UK data as informative priors. The resulting estimates were then compared to a Lebanon value set obtained using Lebanon data by itself via various prediction criterions. The findings permit the UK evidence to contribute potential prior information to the Lebanon analysis by producing more precise valuation estimates than analyzing Lebanon data only under all criterions used. The positive findings suggest that existing valuation studies can be merged with a small valuation set in another country to produce value sets, thereby making own country value sets more attainable for LMICs.

SUBMITTER: Kharroubi SA

PROVIDER: S-EPMC8392468 | biostudies-literature | 2021 Aug

REPOSITORIES: biostudies-literature

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Modeling SF-6D Health Utilities: Is Bayesian Approach Appropriate?

Kharroubi Samer A SA

International journal of environmental research and public health 20210809 16

<h4>Background</h4>Valuation studies of preference-based health measures like SF6D have been conducted in many countries. However, the cost of conducting such studies in countries with small populations or low- and middle-income countries (LMICs) can be prohibitive. There is potential to use results from readily available countries' valuations to produce better valuation estimates.<h4>Methods</h4>Data from Lebanon and UK SF-6D value sets were analyzed, where values for 49 and 249 health states w ...[more]

PMID: 34444157

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Project description:The parameter uncertainty in the six-dimensional health state short form (SF-6D) value sets is commonly ignored. There are two sources of parameter uncertainty: uncertainty around the estimated regression coefficients and uncertainty around the model's specification. This study explores these two sources of parameter uncertainty in the value sets using probabilistic sensitivity analysis (PSA) and a Bayesian approach. We used data from the original UK/SF-6D valuation study to evaluate the extent of parameter uncertainty in the value set. First, we re-estimated the Brazier model to replicate the published estimated coefficients. Second, we estimated standard errors around the predicted utility of each SF-6D state to assess the impact of parameter uncertainty on these estimated utilities. Third, we used Monte Carlo simulation technique to account for the uncertainty on these estimates. Finally, we used a Bayesian approach to quantifying parameter uncertainty in the value sets. The extent of parameter uncertainty in SF-6D value sets was assessed using data from the Hong Kong valuation study. Including parameter uncertainty results in wider confidence/credible intervals and improved coverage probability using both approaches. Using PSA, the mean 95% confidence intervals widths for the mean utilities were 0.1394 (range: 0.0565-0.2239) and 0.0989 (0.0048-0.1252) with and without parameter uncertainty whilst, using the Bayesian approach, this was 0.1478 (0.053-0.1665). Upon evaluating the impact of parameter uncertainty on estimates of a population's mean utility, the true standard error was underestimated by 79.1% (PSA) and 86.15% (Bayesian) when parameter uncertainty was ignored. Parameter uncertainty around the SF-6D value set has a large impact on the predicted utilities and estimated confidence intervals. This uncertainty should be accounted for when using SF-6D utilities in economic evaluations. Ignoring this additional information could impact misleadingly on policy decisions.

Project description:Background/purposeHealth state utilities (HSU) are a subjective measure of an individual's health-related quality of life (HRQoL), adjusted by societal or patient relative preference weights for living in different states of health-related quality of life (HRQoL), derived from patient-reported responses to multi-attribute utility instrument (MAUI), and can be used as inputs for cost-utility analyses and in clinical assessment. This research assessed associations of diet with subsequent HSU in a large international cohort of people living with multiple sclerosis (MS), a progressive autoimmune condition of the central nervous system.MethodsHSUs were generated from responses to Short-Form Six-Dimension (SF-6D) MAUI, and quality-of-the-diet by Diet Habits Questionnaire (DHQ). Cross-sectional, and short- and long-term prospective associations of DHQ with HSU evaluated by linear regression at 2.5- and 5-years. Pooled prospective associations between DHQ and HSU evaluated using linear and quantile regression. Analyses adjusted for relevant demographic and clinical covariates.ResultsAmong 839 participants, baseline DHQ scores showed short- and long-term associations with subsequent HSU, each 10-unit increase in total DHQ score associated with 0.008-0.012 higher HSU (out of 1.00). These associations were dose-dependent, those in the top two quartiles of baseline DHQ scores having 0.01-0.03 higher HSU at follow-up, 0.03 being the threshold for a minimally clinically important difference. Fat, fiber, and fruit/vegetable DHQ subscores were most strongly and consistently associated with better HSU outcomes. However, baseline meat and dairy consumption were associated with 0.01-0.02 lower HSU at subsequent follow-up.ConclusionsA higher quality-of-the-diet showed robust prospective relationships with higher HSUs 2.5- and 5-years later, substantiating previous cross-sectional relationships in this cohort. Subject to replication, these results suggest interventions to improve the quality-of-the-diet may be effective to improve HRQoL in people living with MS.

Project description:PurposeTo assess construct validity and responsiveness of the Expanded Prostate Cancer Index Composite Instrument (EPIC-26) relative to the Short-Form Six-Dimension (SF-6D) and Assessment of Quality of Life 6-Dimension (AQoL-6D) in patients following treatment for prostate cancer.MethodsRetrospective prostate cancer registry data were used. The SF-6D, AQoL-6D, and EPIC-26 were collected at baseline and one year post treatment. Analyses were based on Spearman's correlation coefficient, Bland-Altman plots and intra-class correlation coefficient, Kruskal Wallis, and Effect Size and the Standardised Response Mean for responsiveness.ResultsThe study sample was comprised of 1915 patients. Complete case analysis of 3,697 observations showed moderate evidence of convergent validity between EPIC-26 vitality/hormonal domain and AQoL-6D (r = 0.45 and 0.54) and SF-6D (r = 0.52 and 0.56) at both timepoints. Vitality/hormonal domain also showed moderate convergent validity with coping domain of AQoL-6D (r = 0.45 and 0.54) and with role (r = 0.41 and 0.49) and social function (r = 0.47 and 0.50) domains of SF-6D at both timepoints, and with independent living (r = 0.40) and mental health (r = 0.43) of AQoL-6D at one year. EPIC-26 sexual domain had moderate convergent validity with relationship domain (r = 0.42 and 0.41) of AQoL-6D at both timepoints. Both AQoL-6D and SF-6D did not discriminate between age groups and tumour stage at both timepoints but AQoL-6D discriminated between outcomes for different treatments at one year. All EPIC-26 domains discriminated between age groups and treatment at both timepoints. The EPIC-26 was more responsive than AQoL-6D and SF-6D between baseline and one year following treatment.ConclusionsAQoL-6D can be used in combination with EPIC-26 in place of SF-12. Although EPIC-26 is not utility based, its popularity amongst clinicians and ability to discriminate between disease-specific characteristics and post-treatment outcomes in clinical trials makes it a candidate for use within cost-effectiveness analyses. The generic measure provides a holistic assessment of quality of life and is suitable for generating quality adjusted life years (QALYs).

Project description:BackgroundPatients with β-thalassemia major (β-TM), predominantly adult patients, are associated with physical, mental, and social problems, that result in decreased quality of life (QoL). However, there is a paucity of data on QoL and health status utility (HSU) among adult patients with β-TM in mainland China. Our study aimed to evaluate the QoL by short form 36 questionnaire (SF-36) of adult patients with β-TM in mainland China and to estimate their HSU by SF-6D. In addition, we aimed to identify predictors of HSU.MethodsIn this cross-sectional descriptive study, a total of 75 adult patients with β-TM were included by the snowball sampling method that applied involving seven provinces with a relatively high prevalence of thalassemia across mainland China between September 1, 2021 and January 31, 2022. The collected information included social-demographic characteristics, health conditions, treatment, social support (social support rating scale), caregiver burden (Zarit burden interview), and QoL (SF-36). HSU scores were calculated for each adult patient from their SF-36 responses using the SF-6D algorithm with Hong Kong's tariff. The frequency of participants' responses to the SF-6D for each item of the options was described. Mean HSU scores between different subgroups were calculated. Ordinary least squares (OLS) regression modeling was performed to identify factors associated with HSU.ResultsA total of 75 adult patients with β-TM were included in this study. The mean SF-36 score was 50.2 ± 10.70, of which physical and mental scores were 47.57 ± 11.28 and 52.85 ± 14.21, respectively. In addition, the mean SF-6D utility score was estimated to be 0.598 ± 0.112, ranging from 0.391 to 0.962. Univariate analyses showed that interruption of iron chelation treatment significantly affected HSU values (P = 0.038); diagnosis with comorbidity very slightly affected HSU values (P = 0.0996). In the multivariate analysis, diagnosis with comorbidity (P = 0.042) was significantly negatively associated with HSU values; the minimum pre-transfusion hemoglobin concentration (P = 0.047) and social support (P = 0.068) were positively associated with HSU values.ConclusionThis study presents poor QoL and HSU outcomes in Chinese adult patients with β-TM. The study also highlights the importance of social support and treatment compliance, which can increase hemoglobin content and reduce comorbidities, further to ensure the QoL of patients. These findings can be used for future clinical and economic studies.

Project description:Background and objectiveMapping algorithms can be used for estimating quality-adjusted life years (QALYs) when studies apply non-preference-based instruments. In this study, we estimate a regression-based algorithm for mapping between the World Health Organization Disability Assessment Schedule (WHODAS 2.0) and the preference-based instrument SF-6D to obtain preference estimates usable in health economic evaluations. This was done separately for the working and non-working populations, as WHODAS 2.0 discriminates between these groups when estimating scores.MethodsUsing a dataset including 2258 participants from the general Swedish population, we estimated the statistical relationship between SF-6D and WHODAS 2.0. We applied three regression methods, i.e., ordinary least squares (OLS), generalized linear models (GLM), and Tobit, in mapping onto SF-6D from WHODAS 2.0 at the overall-score and domain levels. Root mean squared error (RMSE) and mean absolute error (MAE) were used for validation of the models; R2 was used to assess model fit.ResultsThe best-performing models for both the working and non-working populations were GLM models with RMSE ranging from 0.084 to 0.088, MAE ranging from 0.068 to 0.071, and R2 ranging from 0.503 to 0.608. When mapping from the WHODAS 2.0 overall score, the preferred model also included sex for both the working and non-working populations. When mapping from the WHODAS 2.0 domain level, the preferred model for the working population included the domains mobility, household activities, work/study activities, and sex. For the non-working population, the domain-level model included the domains mobility, household activities, participation, and education.ConclusionsIt is possible to apply the derived mapping algorithms for health economic evaluations in studies using WHODAS 2.0. As conceptual overlap is incomplete, we recommend using the domain-based algorithms over the overall score. Different algorithms must be applied depending on whether the population is working or non-working, due to the characteristics of WHODAS 2.0.

Project description:BackgroundHealth-related quality of life (HRQoL) and health state utility value (HSUV) measurements are vital components of healthcare clinical and economic evaluations. Accurate measurement of HSUV and HRQoL require validated instruments. The 12-item Short-Form Health Survey (SF-12) is one of few instruments that can evaluate both HRQoL and HSUV, but its validity has not been assessed in people living with HIV/AIDS (PLWHA) in east Africa, where the burden of HIV is high.MethodsThis cross-sectional study used baseline data from a randomized trial involving PLWHA in Kenya. Data included responses from a translated and adapted SF-12 survey as well as key demographic and clinical data. Construct validity of the survey was examined by testing the SF-12's ability to distinguish between groups known in advance to have differences in their health based on their disease severity. We classified disease severity based on established definitions from the US Center for Disease Control (CDC) and WHO, as well as a previously studied viral load threshold. T-tests and ANOVA were used to test for differences in HRQoL and HSUV scores. Area under the receive operator curve (AUC) was used to test the discriminative ability of the HRQoL and HSUV instruments.ResultsDifferences in physical component scores met the minimum clinically important difference among participants with more advanced HIV when defined by CD4 count (4.3 units) and WHO criteria (compared to stage 1, stages 2, 3 and 4 were 2.0, 7.2 and 9.8 units lower respectively). Mental score differences met the minimum clinically important difference between WHO stage 1 and stage 4 patients (4.4). Differences in the HSUV were statistically lower in more advanced HIV by all three definitions of severity. The AUC showed poor to weak discriminatory ability in most analyses, but had fair discriminatory ability between WHO clinical stage 1 and clinical stage 4 individuals (AUC = 0.71).ConclusionOur findings suggest that the Kiswahili translated and adapted version of the SF-12 could be used as an assessment tool for physical health, mental health and HSUV for Kiswahili-speaking PLHWA.Trial registrationClinical trials.gov identifier: NCT00830622 . Registered 26 January 2009.

Dataset Information

Modeling SF-6D Health Utilities: Is Bayesian Approach Appropriate?

Publications

Modeling SF-6D Health Utilities: Is Bayesian Approach Appropriate?

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