Family Lifestyle Dynamics and Childhood Obesity: Evidence from the Millennium Cohort Study

Using data from the Millennium Cohort Study, we investigate the dynamic relationship between underlying family lifestyle and childhood obesity during early childhood. We use a dynamic latent factor model, an approach that allows us to identify family lifestyle, its evolution over time and its influence on childhood obesity and other observable outcomes. We find that family lifestyle is persistent and has a significant influence on childhood weight status as well as other outcomes for all family members. Interventions should therefore be prolonged and persuasive and target the underlying lifestyle of a family as early as possible during childhood in order to have the greatest cumulative influence. Furthermore, the results indicate that to reduce inequalities in childhood obesity, policy makers should target disadvantaged families and design interventions specifically for these families

Fitting adjusted limited dependent variable mixture models to EQ-5D

In this article, we describe the aldvmm command for fitting adjusted limited dependent variable mixture models to either UK or U.S. tariff EQ-5D data. We present and explain the command and postestimation command through examples. The aldvmm command requires use of Stas Kolenikov’s simulated annealing package (simann()), which can be easily installed by typing net install simann.pkg, from(http://web.missouri.edu/~kolenikovs/stata)

Mapping the EORTC QLQ-C30 to EQ-5D-3L in patients with breast cancer

Background The types of outcomes measured collected in clinical studies and those required for cost-effectiveness analysis often differ. Decision makers routinely use quality adjusted life years (QALYs) to compare the benefits and costs of treatments across different diseases and treatments using a common metric. QALYs can be calculated using preference-based measures (PBMs) such as EQ-5D-3L, but clinical studies often focus on objective clinician or laboratory measured outcomes and non-preference-based patient outcomes, such as QLQ-C30. We model the relationship between the generic, preference-based EQ-5D-3L and the cancer specific quality of life questionnaire, QLQ-C30 in patients with breast cancer. This will result in a mapping that allows users to convert QLQ-C30 scores into EQ-5D-3L scores for the purposes of cost-effectiveness analysis or economic evaluation. Methods We use data from a randomized trial of 602 patients with HER2-positive advanced breast cancer provided 3766 EQ-5D-3L observations. Direct mapping using adjusted, limited dependent variable mixture models (ALDVMM) is compared to a random effects linear regression and indirect mapping using seemingly unrelated ordered probit models. EQ-5D-3L was estimated as a function of the summary scales of the QLQ-C30 and other patient characteristics. Results A four component mixture model outperformed other models in terms of summary fit statistics. A close fit to the observed data was observed across the range of disease severity. Simulated data from the model closely aligned to the original data and showed that mapping did not significantly underestimate uncertainty. In the simulated data, 22.15% were equal to 1 compared to 21.93% in the original data. Variance was 0.0628 in the simulated data versus 0.0693 in the original data. The preferred mapping is provided in Excel and Stata files for the ease of users. Conclusion A four component adjusted mixture model provides reliable, non-biased estimates of EQ-5D-3L from the QLQ-C30, to link clinical studies to economic evaluation of health technologies for breast cancer. This work adds to a growing body of literature demonstrating the appropriateness of mixture model based approaches in mapping

The EQ-5D-5L value set for England: Findings of a quality assurance program

Objectives Five-level EuroQol 5-dimensional questionnaire (EQ-5D-5L) values for several countries now exist. Decision makers require confidence in the underlying data and statistical analyses before advocating their use. Independent quality assurance of the published English value set is reported here. Methods Data from 996 participants, and code to run published statistical models, were provided for inspection. The main elements of the study were 10 lead-time trade-off (TTO) experiments and 7 discrete choice experiments (DCEs). Data quality was examined and tested with respect to subsequent assumptions made in the statistical analysis. We examined the statistical analysis including model specification and estimation methods. Results The TTO experiments covered less than 3% of the possible 3125 5-level health states. There is strong evidence, both direct (self-reported) and indirect (poor data quality), that many participants found tasks difficult or did not engage effectively. Forty-seven percent of respondents valued more than 20% of states inconsistently, which is double the 3-level rate. The DCEs covered 12.5% of possible states and 0.01% of possible 2-state comparisons. The design precludes examination of inconsistent responses. Several aspects of the statistical model conflict with the data and underlying experimental design. The model is unidentified. The Bayesian approach relies on unjustified, informative priors. There is a clear failure to achieve convergence. Conclusion Significant limitations are identified with the quality of the valuation data and the subsequent statistical analysis that underpin the English EQ-5D-5L value set. A new program of further development, including a new data collection initiative, should be considered to put the EQ-5D-5L on a sufficiently firm evidential basis for healthcare decision making

The Impact of Moving from EQ-5D-3L to -5L in NICE Technology Appraisals

Background: The EuroQol-5 Dimension (EQ-5D) instrument is the National Institute for Health and Care Excellence (NICE)’s preferred measure of health-related quality of life (QoL) in adults. The three-level (3L) value set is currently recommended for use, but the five-level (5L) set is increasingly being used in practice. Objective: We aimed to explore the impact of moving from 3L to 5L in NICE appraisals. Methods: We adapted our existing mapping for use with health state utility values derived from a population where the original distribution of utilities was unknown. We used this mapping to estimate 5L utilities for 21 comparisons of interventions from models used in NICE technology appraisal decision making, covering a range of disease areas. Results: All utilities increased using 5L, and the differences between highest and lowest utilities decreased. In ten oncology comparisons, using 5L generally increased the incremental quality-adjusted life-years (QALYs) as the benefit from improving survival increased. In four non-oncology comparisons where the intervention improved QoL only, the incremental QALYs decreased as the benefit of improving QoL was reduced. In seven non-oncology comparisons where interventions improved survival and QoL, there was a trade-off between increasing the benefit from survival and decreasing the benefit from improving QoL. Conclusion: 3L and 5L lead to substantially different estimates of incremental QALYs and cost effectiveness. The direction and magnitude of the change is not consistent across case studies. Using 5L instead of 3L may lead to different reimbursement decisions. NICE will face inconsistencies in decision making if it uses 3L and 5L concurrently

EQ-5D-5L versus 3L: the impact on cost-effectiveness

Objectives To model the relationship between EQ-5D-3L and EQ-5D-5L and examine how differences impact on cost-effectiveness in case studies. Methods We used two datasets that included both EQ-5D-3L and EQ-5D-3L from the same respondents. The EuroQoL dataset (n=3551) included patients with different diseases and a healthy cohort. The National Databank (NDB) dataset included patients with rheumatoid disease (n=5205). We estimated a system of ordinal regressions in each dataset using copula models, to link responses to the 3L instrument to 5L and its tariff, and vice versa. Results were applied to nine cost-effectiveness studies. Results Best-fitting models differed between EuroQoL and NDB datasets in terms of the explanatory variables, copulas and coefficients. In both cases the coefficients of the covariates and latent factor between -3L and -5L were significantly different, indicating that the two instruments are not a uniform realignment of the response levels for most dimensions. In the case studies, moving from 3L to 5L caused a decrease of up to 87% in incremental QALYs gained from effective technologies in almost all cases. ICERs increased, often substantially. Conversely, one technology with a significant mortality gain saw increased incremental QALYs. Conclusion 5L shifts mean utility scores up the utility scale towards full health and compresses them into a smaller range, compared to -3L. Improvements in quality of life are valued less using 5L than with 3L. 3L and 5L can produce substantially different estimates of cost effectiveness. There is no simple proportional adjustment that can be made to reconcile these differences

Situated drinking: the association between eating and alcohol consumption in Great Britain

Aims. This paper examines the co-occurrence of drinking alcohol and eating in Great Britain. Applying a practice-theoretical framework, it attends primarily to the nature and characteristics of events – to social situations. It asks whether drinking events involving food are significantly different from those without?, whether differences are the same at home as on commercial public premises?, and whether differences are the same for men and women? The focus is especially on episodes of drinking with meals at home, an infrequently explored context for a substantial proportion of contemporary alcohol consumption. Data. Employing a secondary analysis of commercial data about the British population in 2016, we examine reports of 47,645 drinking events, on commercial premises and at other locations, to explore how eating food and consumption of alcoholic beverages affect one another. Three types of event are compared – drinking with meals, with snacks and without any food. Variables describing situations include group size and composition, temporal and spatial parameters, beverages, purposes and simultaneous activities. Basic socio-demographic characteristics of respondents are also examined, with a special focus on the effects of gender. Results. Behaviours differ between settings. The presence of food at a drinking episode is associated with different patterns of participation, orientations, and quantities and types of beverage consumed. Gender, age and class differences are apparent. Conclusions. Patterns of alcohol consumption are significantly affected by the accompaniment of food. This is a much neglected topic which would benefit from further comparative and time series studies to determine the consequences for behaviour and intervention

Cost effectiveness of difelikefalin compared to standard care for treating chronic kidney disease associated pruritus (CKD-aP) in people with kidney failure receiving haemodialysis

Background: Chronic kidney disease-associated pruritus (CKD-aP) is associated with an increased risk of depression, poor sleep and reduced health-related quality of life. Two phase III studies (KALM-1 and KALM-2) of difelikefalin showed reduced CKD-aP severity and improved itch-related health-related quality of life in patients with moderate and severe CKD-aP receiving haemodialysis for kidney failure. Objective: We aimed to estimate the cost effectiveness of difelikefalin for patients with CKD-aP receiving haemodialysis for kidney failure compared to standard care from a UK National Health Service perspective. Methods: A cohort model was developed with four health states representing levels of pruritus intensity over time, based on the KALM trials augmented with longer term CKD-aP severity data from another haemodialysis trial (SHAREHD) for standard care. Utilities were estimated from a mapping study of 5-D Itch to EQ-5D-5L in 487 patients receiving haemodialysis, costs were estimated based on resource use alongside the SHAREHD and 2018 unit costs, and inflated to 2021 costs. Costs and quality-adjusted life-years were discounted at 3.5% per annum. A de novo economic model was developed in Microsoft Excel with scenario analyses performed using a range of assumptions. Results: In the base-case analysis over a time horizon of 64 weeks, using a placeholder cost of £75 per 28-days for difelikefalin, the incremental cost-effectiveness ratio of difelikefalin compared with standard care was £19,558/quality-adjusted life-year (QALY). Scenario analyses resulted in incremental cost-effectiveness ratios that ranged from £10,154/QALY (severe only) to £16,957/QALY (5-year horizon) for difelikefalin compared to standard care. Probabilistic sensitivity analyses suggested difelikefalin has a 48.6% probability of being cost effective at a threshold of £20,000/QALY and a 57.2% probability of being cost effective at a threshold of £30,000/QALY. Conclusions: The cost effectiveness of difelikefalin in a range of scenarios could make it an important pharmacotherapy to address the high burden of disease and unmet need for treatments associated with CKD-aP in the UK

Transport on percolation clusters with power-law distributed bond strengths: when do blobs matter?

The simplest transport problem, namely maxflow, is investigated on critical percolation clusters in two and three dimensions, using a combination of extremal statistics arguments and exact numerical computations, for power-law distributed bond strengths of the type $P(\sigma) \sim \sigma^{-\alpha}$. Assuming that only cutting bonds determine the flow, the maxflow critical exponent \ve is found to be \ve(\alpha)=(d-1) \nu + 1/(1-\alpha). This prediction is confirmed with excellent accuracy using large-scale numerical simulation in two and three dimensions. However, in the region of anomalous bond capacity distributions ($0\leq \alpha \leq 1$) we demonstrate that, due to cluster-structure fluctuations, it is not the cutting bonds but the blobs that set the transport properties of the backbone. This ``blob-dominance'' avoids a cross-over to a regime where structural details, the distribution of the number of red or cutting bonds, would set the scaling. The restored scaling exponents however still follow the simplistic red bond estimate. This is argued to be due to the existence of a hierarchy of so-called minimum cut-configurations, for which cutting bonds form the lowest level, and whose transport properties scale all in the same way. We point out the relevance of our findings to other scalar transport problems (i.e. conductivity).Comment: 9 pages + Postscript figures. Revtex4+psfig. Submitted to PR

The Use Of Mapping To Estimate Health State Utility Values

Mapping functions are estimated using regression analyses and are frequently used to predict health state utility values (HSUVs) in decision analytic models. Mapping functions are used when evidence on the required preference-based measure (PBM) is not available, or where modelled values are required for a decision analytic model, for example to control for important sociodemographic variables (such as age or gender). This article provides an overview of the latest recommendations including pre-mapping considerations, the mapping process including data requirements for undertaking the estimation of mapping functions, regression models for estimating mapping functions, assessing performance and reporting standards for mapping studies. Examples in rheumatoid arthritis are used for illustration. When reporting the results of mapping standards the following should be reported: a description of the dataset used (including distributions of variables used) and any analysis used to inform the selection of the model type and model specification. The regression method and specification should be justified, and as summary statistics may mask systematic bias in errors, plots comparing observed and predicted HSUVs. The final model (coefficients, error term(s), variance and covariance) should be reported together with a worked example. It is important to ensure that good practice is followed as any mapping functions will only be as appropriate and accurate as the method used to obtain them; for example, mapping should not be used if there is no overlap between the explanatory and target variables