The PHEM-B toolbox of methods for incorporating the influences on Behaviour into Public Health Economic Models.

BACKGROUND: It is challenging to predict long-term outcomes of interventions without understanding how they work. Health economic models of public health interventions often do not incorporate the many determinants of individual and population behaviours that influence long term effectiveness. The aim of this paper is to draw on psychology, sociology, behavioural economics, complexity science and health economics to: (a) develop a toolbox of methods for incorporating the influences on behaviour into public health economic models (PHEM-B); and (b) set out a research agenda for health economic modellers and behavioural/ social scientists to further advance methods to better inform public health policy decisions. METHODS: A core multidisciplinary group developed a preliminary toolbox from a published review of the literature and tested this conceptually using a case study of a diabetes prevention simulation. The core group was augmented by a much wider group that covered a broader range of multidisciplinary expertise. We used a consensus method to gain agreement of the PHEM-B toolbox. This included a one-day workshop and subsequent reviews of the toolbox. RESULTS: The PHEM-B toolbox sets out 12 methods which can be used in different combinations to incorporate influences on behaviours into public health economic models: collaborations between modellers and behavioural scientists, literature reviewing, application of the Behaviour Change Intervention Ontology, systems mapping, agent-based modelling, differential equation modelling, social network analysis, geographical information systems, discrete event simulation, theory-informed statistical and econometric analyses, expert elicitation, and qualitative research/process tracing. For each method, we provide a description with key references, an expert consensus on the circumstances when they could be used, and the resources required. CONCLUSIONS: This is the first attempt to rigorously and coherently propose methods to incorporate the influences on behaviour into health economic models of public health interventions. It may not always be feasible or necessary to model the influences on behaviour explicitly, but it is essential to develop an understanding of the key influences. Changing behaviour and maintaining that behaviour change could have different influences; thus, there could be benefits in modelling these separately. Future research is needed to develop, collaboratively with behavioural scientists, a suite of more robust health economic models of health-related behaviours, reported transparently, including coding, which would allow model reuse and adaptation.

Does EQ-5D Tell the Whole Story? Statistical Methods for Comparing the Thematic Coverage of Clinical and Generic Outcome Measures, With Application to Breast Cancer.

OBJECTIVES: This study aimed to develop the following: (1) methods for assessing claims in any specific application that a generic outcome measure, such as EQ-5D is deficient in its coverage of 1 or more specified domains, and (2) a simple method of judging whether any such deficiency is likely to be quantitatively important enough to call into question evaluations based on the generic instrument. Also to demonstrate the applicability of the methods in the important area of breast cancer. METHODS: The methodology requires a data set with observations from a generic instrument (eg, EQ-5D) and also a more comprehensive clinical instrument (eg, FACT-B [Functional Assessment of Cancer Therapy - Breast]). A standardized 3-component statistical analysis is proposed for investigating the claim that the generic measure inadequately captures some specified dimension covered by the latter instrument. A theoretically based upper bound on the bias induced by deficient coverage is derived based on the assumption that the designers of the (k-dimensional) generic instrument did succeed in identifying the k most important domains. RESULTS: Data from the MARIANNE breast cancer trial were analyzed and results suggested that impacts on personal appearance and relationships may be inadequately represented by EQ-5D. Nevertheless, the indications are that the bias in quality-adjusted life-year differences from deficient coverage by EQ-5D is likely to be modest. CONCLUSIONS: The methodology offers a systematic approach to determining whether there is clear evidence consistent with any claim that a generic outcome measure such as EQ-5D misses an important specific domain. The approach is readily implementable using data sets that are available in many randomized controlled trials.

Guidance on the use of complex systems models for economic evaluations of public health interventions.

To help health economic modelers respond to demands for greater use of complex systems models in public health. To propose identifiable features of such models and support researchers to plan public health modeling projects using these models. A working group of experts in complex systems modeling and economic evaluation was brought together to develop and jointly write guidance for the use of complex systems models for health economic analysis. The content of workshops was informed by a scoping review. A public health complex systems model for economic evaluation is defined as a quantitative, dynamic, non-linear model that incorporates feedback and interactions among model elements, in order to capture emergent outcomes and estimate health, economic and potentially other consequences to inform public policies. The guidance covers: when complex systems modeling is needed; principles for designing a complex systems model; and how to choose an appropriate modeling technique. This paper provides a definition to identify and characterize complex systems models for economic evaluations and proposes guidance on key aspects of the process for health economics analysis. This document will support the development of complex systems models, with impact on public health systems policy and decision making.

Enabling QALY estimation in mental health trials and care settings: mapping from the PHQ-9 and GAD-7 to the ReQoL-UI or EQ-5D-5L using mixture models.

PURPOSE: Patient-reported outcome measures (PROMs) are commonly collected in trials and some care settings, but preference-based PROMs required for economic evaluation are often missing. For these situations, mapping models are needed to predict preference-based (aka utility) scores. Our objective is to develop a series of mapping models to predict preference-based scores from two mental health PROMs: Patient Health Questionnaire-9 (PHQ-9; depression) and Generalised Anxiety Questionnaire-7 (GAD-7; anxiety). We focus on preference-based scores for the more physical-health-focussed EQ-5D (five-level England and US value set, and three-level UK cross-walk) and more mental-health-focussed Recovering Quality-of-Life Utility Index (ReQoL-UI). METHODS: We used trial data from the Improving Access to Psychological Therapies (IAPT) mental health services (now called NHS Talking Therapies), England, with a focus on people with depression and/or anxiety caseness. We estimated adjusted limited dependent variable or beta mixture models (ALDVMMs or Betamix, respectively) using GAD-7, PHQ-9, age, and sex as covariates. We followed ISPOR mapping guidance, including assessing model fit using statistical and graphical techniques. RESULTS: Over six data collection time-points between baseline and 12-months, 1340 observed values (N ≤ 353) were available for analysis. The best fitting ALDVMMs had 4-components with covariates of PHQ-9, GAD-7, sex, and age; age was not a probability variable for the final ReQoL-UI mapping model. Betamix had practical benefits over ALDVMMs only when mapping to the US value set. CONCLUSION: Our mapping functions can predict EQ-5D-5L or ReQoL-UI related utility scores for QALY estimation as a function of variables routinely collected within mental health services or trials, such as the PHQ-9 and/or GAD-7.

Relationship Between Standardized Measures of Chronic Kidney Disease-associated Pruritus Intensity and Health-related Quality of Life Measured with the EQ-5D Questionnaire: A Mapping Study.

Chronic kidney disease-associated pruritus is linked with decreased health-related quality of life assessed using disease-specific instruments. The extent to which worsening pruritus reduces generic quality of life assessed using the EQ-5D instrument is unknown. Prevalent kidney failure patients receiving in-centre haemodialysis from 5 centres completed the EQ-5D-5L quality of life measure, worst Itching Intensity Numerical Rating Scale and 5-D itch pruritus instruments. Latent class models were used to identify clusters of patients with similarly affected body parts, and mixture models were used to map the pruritus measures to the EQ-5D. Data on 487 respondents were obtained. Latent class analysis identified 3 groups of patients who had progressively worsening severity and an increasing number of body parts affected. Although the worst itching intensity numerical rating scale and 5-D itch instruments correlated with each other, only the latter had a strong relationship with EQ-5D. When controlling for age, sex, diabetes and years receiving dialysis, the meanpredicted EQ-5D utility (1: perfect health, 0: dead) decreased progressively from 0.69 to 0.41. These findings suggest that pruritus instruments that include domains capturing how the individual is physically, mentally and socially affected by their pruritus, in addition to severity, more closely approximate the EQ-5D generic quality of life measure.

The trajectory of a range of commonly captured symptoms with standard care in people with kidney failure receiving haemodialysis: consideration for clinical trial design.

BACKGROUND: Despite the recognized high symptom prevalence in haemodialysis population, how these symptoms change over time and its implications for clinical practice and research is poorly understood. METHODS: Prevalent haemodialysis patients in the SHAREHD trial reported 17 POS-S Renal symptoms (none, mild, moderate, severe and overwhelming) at baseline, 6, 12 and 18 months. To assess the prevalence change at population level in people reporting moderate or worse symptoms at baseline, the absolute change in prevalence was estimated using multi-level mixed effects probit regression adjusting for age, sex, time on haemodialysis and Charlson Comorbidity Score. To assess changes at individual level, the proportion of people changing their symptom score every 6 months was estimated. RESULTS: Five hundred fifty-two participants completed 1725 questionnaires at four timepoints. Across all 17 symptoms with moderate or worse symptom severity at baseline, the majority of the change in symptom prevalence at population level occurred in the 'severe' category. The absolute improvement in prevalence of the 'severe' category was ≤ 20% over 18 months in eleven of the seventeen symptoms despite a large degree of relatively balanced movement of individuals in and out of severe category every six months. Examples include depression, skin changes and drowsiness, which had larger proportion (75-80%) moving in and out of severe category each 6 months period but < 5% difference between movement in and out of severe category resulting in relatively static prevalence over time. Meanwhile, larger changes in prevalence of > 20% were observed in six symptoms, driven by a 9 to 18% difference between movement in and movement out of severe category. All symptoms had > 50% of people in severe group changing severity within 6 months. CONCLUSIONS: Changes in the severity of existing symptoms under standard care were frequent, often occurring within six months. Certain symptoms exhibited clinically meaningful shifts at both the population and individual levels. This highlighted the need to consider improvements in symptom severity when determining sample size and statistical power for trials. By accounting for potential symptom improvements with routine care, researchers can design trials capable of robustly detecting genuine treatment effects, distinguishing them from spontaneous changes associated with standard haemodialysis.

A model-based economic analysis of the CFHealthHub intervention to support adherence to inhaled medications for people with cystic fibrosis in the UK.

BACKGROUND: Adherence to preventative inhaled therapies in people with cystic fibrosis (CF) is low, resulting in potentially avoidable health losses and the need for costly rescue therapies. OBJECTIVES: To estimate the cost-effectiveness of the CFHealthHub (CFHH) intervention to support adherence to inhaled medications. METHODS: A state transition model was developed to assess the cost-effectiveness of the CFHH intervention versus usual care from the perspective of the UK National Health Service and Personal Social Services over a lifetime horizon. Costs and health outcomes were discounted at a rate of 3.5 percent per annum. Costs were valued at 2021/22 prices. The model structure includes health states defined by survival status, level of lung function, and transplant history. Treatment effects were modeled by changing the probabilities of transitioning between lung function states and reducing exacerbation rates. Model parameters were informed by the CFHH trial, CF Registry data, routine cost databases, literature, and expert opinion. Deterministic and probabilistic sensitivity analyses were undertaken to assess uncertainty. RESULTS: The CFHH intervention is expected to generate additional health gains and cost savings compared with usual care. Assuming that it is delivered for 10 years, the CFHH intervention is expected to generate 0.17 additional quality-adjusted life years and cost savings of GBP 1,600 (EUR 1,662) per patient. CONCLUSIONS: The CFHH intervention is expected to dominate usual care, irrespective of the duration over which the intervention is delivered. The modeled benefits and cost savings are smaller than initially expected and are sensitive to relative treatment effects on lung function.

Mapping between EQ-5D-3L and EQ-5D-5L: A survey experiment on the validity of multi-instrument data.

EQ-5D is a 5-item questionnaire instrument designed to measure health-related quality of life. It is extremely important, since it is used to measure health benefits in many studies providing evidence for reimbursement decisions by the National Institute for Health and Care Excellence in England and similar policy bodies in other countries. EQ-5D has been redesigned in a more detailed form (EQ-5D-5L), but much existing cost-effectiveness evidence is based on the older version (EQ-5D-3L). Statistical mapping from one version to another is widely used, exploiting data from multi-instrument surveys incorporating both variants. However, little is known about the robustness of data from such multi-instrument surveys. We design a randomized experiment to investigate whether inclusion of both versions at different stages in a single interview gives a reliable picture of the relationship between health measures from the two instruments and embed it in individual interviews from the UK Understanding Society household panel. We find that sequencing of the two versions of EQ-5D within an interview has a significant impact not only on the resulting data but also on the estimated mapping models. We illustrate the non-negligible effects in two real-world cost-effectiveness examples and discuss the implications for future multi-instrument survey design.

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.

Mapping From Visual Acuity to EQ-5D, EQ-5D With Vision Bolt-On, and VFQ-UI in Patients With Macular Edema in the LEAVO Trial.

OBJECTIVES: Mappings to convert clinical measures to preference-based measures of health such as the EQ-5D-3L are sometimes required in cost-utility analyses. We developed mappings to convert best-corrected visual acuity (BCVA) to the EQ-5D-3L, the EQ-5D-3L with a vision bolt-on (EQ-5D V), and the Visual Functioning Questionnaire-Utility Index (VFQ-UI) in patients with macular edema caused by central retinal vein occlusion. METHODS: We used data from Lucentis, Eylea, Avastin in vein occlusion (LEAVO), which is a phase-3 randomized controlled trial comparing ranibizumab, aflibercept, and bevacizumab in 463 patients with observations at 6 time points. We estimated adjusted limited dependent variable mixture models consisting of 1 to 4 distributions (components) using BCVA in each eye, age, and sex to predict utility within the components and BCVA as a determinant of component membership. We compared model fit using mean error, mean absolute error, root mean square error, Akaike information criteria, Bayesian information criteria, and visual inspection of mean predicted and observed utilities and cumulative distribution functions. RESULTS: Mean utility scores were 0.82 for the EQ-5D-3L, 0.79 for the EQ-5D V, and 0.88 for the VFQ-UI. The best-fitting models for the EQ-5D and EQ-5D V had 2 components (with means of approximately 0.44 and 0.85), and the best-fitting model for VFQ-UI had 3 components (with means of approximately 0.95, 0.74, and 0.90). CONCLUSIONS: Models with multiple components better predict utility than those with single components. This article provides a valuable addition to the literature, in which previous mappings in visual acuity have been limited to linear regressions, resulting in unfounded assumptions about the distribution of the dependent variable.

Mapping the FACT-B Instrument to EQ-5D-3L in Patients with Breast Cancer Using Adjusted Limited Dependent Variable Mixture Models versus Response Mapping.

BACKGROUND: Preference-based measures of health, such as the three-level EuroQol five-dimensional questionnaire (EQ-5D-3L), are required to calculate quality-adjusted life-years for use in cost-effectiveness analysis, but are often not recorded in clinical studies. In these cases, mapping can be used to estimate preference-based measures. OBJECTIVES: To model the relationship between the EQ-5D-3L and the Functional Assessment of Cancer Therapy-Breast Cancer (FACT-B) instrument, comparing indirect and direct mapping methods, and the use of FACT-B summary score versus FACT-B subscale scores. METHODS: We used data from three clinical studies for advanced breast cancer providing 11,958 observations with full information on FACT-B and the EQ-5D-3L. We compared direct mapping using adjusted limited dependent variable mixture models (ALDVMMs) with indirect mapping using seemingly unrelated ordered probit models. The EQ-5D-3L was estimated as a function of FACT-B and other patient-related covariates. RESULTS: The use of FACT-B subscale scores was better than using the total FACT-B score. A good fit to the observed data was observed across the entire range of disease severity in all models. ALDVMMs outperformed the indirect mapping. The breast cancer-specific scale had a strong influence in predicting the pain/discomfort and self-care dimensions of the EQ-5D-3L. CONCLUSIONS: This article adds to the growing literature that demonstrates the performance of the ALDVMM method for mapping. Regardless of which model is used, the subscales of FACT-B should be included as independent variables wherever possible. The breast cancer-specific subscale of FACT-B is important in predicting the EQ-5D-3L. This suggests that generic cancer measures should not be used for utility mapping in patients with breast cancer.

Development of Methods for the Mapping of Utilities Using Mixture Models: Mapping the AQLQ-S to the EQ-5D-5L and the HUI3 in Patients with Asthma.

BACKGROUND: Studies have shown that methods based on mixture models work well when mapping clinical to preference-based methods. OBJECTIVES: To develop these methods in different ways and to compare performance in a case study. METHODS: Data from 856 patients with asthma allowed mapping between the Asthma Quality of Life Questionnaire and both the five-level EuroQol five-dimensional questionnaire (EQ-5D-5L) and the health utilities index mark 3 (HUI3). Adjusted limited dependent variable mixture models and beta-based mixture models were estimated. Optional inclusion of the gap between full health and the next value as well as a mass point at the next feasible value were explored. RESULTS: In all cases, model specifications formally modeling the gap between full health and the next feasible value were an improvement on those that did not. Mapping to the HUI3 required more components in the mixture models than did mapping to the EQ-5D-5L because of its uneven distribution. The optimal beta-based mixture models mapping to the HUI3 included a probability mass at the utility value adjacent to full health. This is not the case when estimating the EQ-5D-5L, because of the low proportion of observations at this point. CONCLUSIONS: Beta-based mixture models marginally outperformed adjusted limited dependent variable mixture models with the same number of components in this data set. Nevertheless, they require a larger number of parameters and longer estimation time. Both mixture model types closely fit both EQ-5D-5L and HUI data. Standard mapping approaches typically lead to biased estimates of health gain. The mixture model approaches exhibit no such bias. Both can be used with confidence in applied cost-effectiveness studies. Future mapping studies in other disease areas should consider similar methods.

EQ-5D-5L versus EQ-5D-3L: The Impact on Cost Effectiveness in the United Kingdom.

OBJECTIVES: To model the relationship between the three-level (3L) and the five-level (5L) EuroQol five-dimensional questionnaire and examine how differences have an impact on cost effectiveness in case studies. METHODS: We used two data sets that included the 3L and 5L versions from the same respondents. The EuroQol Group data set (n = 3551) included patients with different diseases and a healthy cohort. The National Data Bank data set included patients with rheumatoid disease (n = 5205). We estimated a system of ordinal regressions in each data set using copula models to link responses of the 3L instrument to those of the 5L instrument and its UK tariff, and vice versa. Results were applied to nine cost-effectiveness studies. RESULTS: Best-fitting models differed between the EuroQol Group and the National Data Bank data sets in terms of the explanatory variables, copulas, and coefficients. In both cases, the coefficients of the covariates and latent factors between the 3L and the 5L instruments were significantly different, indicating that moving between instruments is not simply a uniform re-alignment of the response levels for most dimensions. In the case studies, moving from the 3L to the 5L caused a decrease of up to 87% in incremental quality-adjusted life-years gained from effective technologies in almost all cases. Incremental cost-effectiveness ratios increased, often substantially. Conversely, one technology with a significant mortality gain saw increased incremental quality-adjusted life-years. CONCLUSIONS: The 5L shifts mean utility scores up the utility scale toward full health and compresses them into a smaller range, compared with the 3L. Improvements in quality of life are valued less using the 5L than using the 3L. The 3L and the 5L can produce substantially different estimates of cost effectiveness. There is no simple proportional adjustment that can be made to reconcile these differences.

Family lifestyle dynamics and childhood obesity: evidence from the millennium cohort study.

BACKGROUND: The prevalence of childhood obesity has been increasing but the causes are not fully understood. Recent public health interventions and guidance aiming to reduce childhood obesity have focused on the whole family, as opposed to just the child but there remains a lack of empirical evidence examining this relationship. METHODS: Using data from the longitudinal Millennium Cohort Study (MCS), we investigate the dynamic relationship between underlying family lifestyle and childhood obesity during early childhood. The MCS interviewed parents shortly after the birth of their child and follow up interviews were carried out when the child was 3, 5 and 7 years. We use a dynamic latent factor model, an approach that allows us to identify family lifestyle, its evolution over time (in this case between birth and 7 years) and its influence on childhood obesity and other observable outcomes. RESULTS: We find that family lifestyle is persistent, 87.43% of families which were above the 95th percentile on the lifestyle distribution, remained above the 95th percentile when the child was 7 years old. Family lifestyle has a significant influence on all outcomes in the study, including diet, exercise and parental weight status; family lifestyle accounts for 11.3% of the variation in child weight by age 7 years. CONCLUSION: The analysis suggests that 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. Our results suggest that children from advantaged backgrounds are more likely to be exposed to healthier lifestyles and that this leads to inequalities in the prevalence of obesity. To reduce inequalities in childhood obesity, policy makers should target disadvantaged families and design interventions specifically for these families.

Mapping to Estimate Health-State Utility from Non-Preference-Based Outcome Measures: An ISPOR Good Practices for Outcomes Research Task Force Report.

Economic evaluation conducted in terms of cost per quality-adjusted life-year (QALY) provides information that decision makers find useful in many parts of the world. Ideally, clinical studies designed to assess the effectiveness of health technologies would include outcome measures that are directly linked to health utility to calculate QALYs. Often this does not happen, and even when it does, clinical studies may be insufficient for a cost-utility assessment. Mapping can solve this problem. It uses an additional data set to estimate the relationship between outcomes measured in clinical studies and health utility. This bridges the evidence gap between available evidence on the effect of a health technology in one metric and the requirement for decision makers to express it in a different one (QALYs). In 2014, ISPOR established a Good Practices for Outcome Research Task Force for mapping studies. This task force report provides recommendations to analysts undertaking mapping studies, those that use the results in cost-utility analysis, and those that need to critically review such studies. The recommendations cover all areas of mapping practice: the selection of data sets for the mapping estimation, model selection and performance assessment, reporting standards, and the use of results including the appropriate reflection of variability and uncertainty. This report is unique because it takes an international perspective, is comprehensive in its coverage of the aspects of mapping practice, and reflects the current state of the art.

Children's Development and Parental Input: Evidence From the UK Millennium Cohort Study.

In this study, we use the UK Millennium Cohort Study to estimate a dynamic factor model of child development. Our model follows the children from birth until 7 years of age and allows for both cognitive and noncognitive abilities in children. We find a significant self-productivity effect in both cognitive and noncognitive development, as well as some evidence of dynamic dependence across different abilities. The activities that parents carry out with children at home (parental investment) have a significant effect on children's development; we find substantial evidence of two distinct latent parental investment variables with differential effects across the two abilities.

The effects of breastfeeding on childhood BMI: a propensity score matching approach.

Background: Many studies have found a statistical association between breastfeeding and childhood adiposity. This paper investigates whether breastfeeding has an effect on subsequent childhood body mass index (BMI) using propensity scores to account for confounding. Methods: We use data from the Millennium Cohort Study, a nationally representative UK cohort survey, which contains detailed information on infant feeding and childhood BMI. Propensity score matching is used to investigate the mean BMI in children breastfed exclusively and partially for different durations of time. Results: We find statistically significant influences of breastfeeding on childhood BMI, particularly in older children, when breastfeeding is prolonged and exclusive. At 7 years, children who were exclusively breastfed for 16 weeks had a BMI 0.28 kg/m2 (95% confidence interval 0.07 to 0.49) lower than those who were never breastfed, a 2% reduction from the mean BMI of 16.6 kg/m2. Conclusions: For this young cohort, even small effects of breastfeeding on BMI could be important. In order to reduce BMI, breastfeeding should be encouraged as part of wider lifestyle intervention. This evidence could help to inform public health bodies when creating public health guidelines and recommendations.

Cost-effectiveness of treatment strategies using combination disease-modifying anti-rheumatic drugs and glucocorticoids in early rheumatoid arthritis.

OBJECTIVE: The aim of this study was to estimate the cost-effectiveness of combination DMARDs with short-term glucocorticoids in early active RA using data from the 2-year Combination of Anti-Rheumatic Drugs in Early RA (CARDERA) trial. METHODS: CARDERA enrolled 467 patients with active RA of <24-months duration. All patients received MTX; half received step-down prednisolone and half ciclosporin in a placebo-controlled factorial design. Differences in mean costs and quality-adjusted life-years (QALYs) over 24-months follow-up were estimated using patient-level data from a UK health service perspective and 2011-12 costs. RESULTS: Two-year costs for each treatment strategy showed primary care costs were negligible across all groups. Drug costs were lowest with MTX/ciclosporin and triple therapy. Hospital costs were lowest with MTX/prednisolone and triple therapy. Triple therapy was least costly and most effective; it dominated all other strategies. At positive values for a QALY in the typical UK range (£20 000-30 000) the probability that triple therapy was the most cost-effective strategy was 0.9. Results were robust to methods used to impute missing data. CONCLUSION: Intensive treatment of early RA with triple therapy (two DMARDs and short-term glucocorticoids) is both clinically effective and cost effective.