Childhood transitions between weight status categories: evidence from the UK Millennium Cohort Study

Background: Assessing the cost-effectiveness of interventions targeting childhood excess weight requires estimates of the hazards of transitioning between weight status categories. Current estimates are based on studies characterized by insufficient sample sizes, a lack of national representativeness, and untested assumptions. Objectives: We sought to (1) estimate transition probabilities and hazard ratios for transitioning between childhood weight status categories, (2) test the validity of the underlying assumption in the literature that transitions between childhood bodyweight categories are time-homogeneous, (3) account for complex sampling procedures when deriving nationally representative transition estimates, and (4) explore the impact of child, maternal, and sociodemographic characteristics. Methods: We applied a multistate transition modeling approach accounting for complex survey design to UK Millennium Cohort Study (MCS) data to predict transition probabilities and hazard ratios for weight status movements for children aged 3–17. Surveys were conducted at ages 3 (wave 2 in 2004), 5 (wave 3 in 2006), 7 (wave 4 in 2008), 11 (wave 5 in 2012), 14 (wave 6 in 2015), and 17 (wave 7 in 2018) years. We derived datasets that included repeated body mass index measurements across waves after excluding multiple births and children with missing or implausible bodyweight records. To account for the stratified cluster sample design of the MCS, we incorporated survey weights and jackknife replicates of survey weights. Using a validation dataset from the MCS, we tested the validity of our models. Finally, we estimated the relationships between state transitions and child, maternal, and sociodemographic factors. Results: The datasets for our primary analysis consisted of 10,399 children for waves 2–3, 10,729 for waves 3–4, 9685 for waves 4–5, 8593 for waves 5–6, and 7085 for waves 6–7. All datasets consisted of roughly equal splits of boys and girls. Under the assumption of time-heterogeneous transition rates (our base-case model), younger children (ages 3–5 and 5–7 years) had significantly higher annual transition probabilities of moving from healthy weight to overweight (0.033, 95% confidence interval [CI] 0.026–0.041, and 0.027, 95% CI 0.021–0.033, respectively) compared to older children (0.015, 95% CI 0.012–0.018, at ages 7–11; 0.018, 95% CI 0.013–0.023, at ages 11–14; and 0.018, 95% CI 0.013–0.025 at ages 14–17 years). However, the resolution of unhealthy weight was more strongly age-dependent than transitions from healthy weight to non-healthy weight states. Transition hazards differed by child, maternal, and sociodemographic factors. Conclusions: Our models generated estimates of bodyweight status transitions in a representative UK childhood population. Compared to our scenario models (i.e., time-homogeneous transition rates), our base-case model fits the observed data best, indicating a non-time-homogeneous pattern in transitions between bodyweight categories during childhood. Transition hazards varied significantly by age and across subpopulations, suggesting that conducting subgroup-specific cost-effectiveness analyses of childhood weight management interventions will optimize decision-making

A methodological framework for assessing agreement between cost-effectiveness outcomes estimated using alternative sources of data on treatment costs and effects for trial-based economic evaluations

A new methodological framework for assessing agreement between cost-effectiveness endpoints generated using alternative sources of data on treatment costs and effects for trial-based economic evaluations is proposed. The framework can be used to validate cost-effectiveness endpoints generated from routine data sources when comparable data is available directly from trial case report forms or from another source. We illustrate application of the framework using data from a recent trial-based economic evaluation of the probiotic Bifidobacterium breve strain BBG administered to babies less than 31 weeks of gestation. Cost-effectiveness endpoints are compared using two sources of information; trial case report forms and data extracted from the National Neonatal Research Database (NNRD), a clinical database created through collaborative efforts of UK neonatal services. Focusing on mean incremental net benefits at £30,000 per episode of sepsis averted, the study revealed no evidence of discrepancy between the data sources (two-sided p values >0.4), low probability estimates of miscoverage (ranging from 0.039 to 0.060) and concordance correlation coefficients greater than 0.86. We conclude that the NNRD could potentially serve as a reliable source of data for future trial-based economic evaluations of neonatal interventions. We also discuss the potential implications of increasing opportunity to utilize routinely available data for the conduct of trial-based economic evaluations

Multivariate generalised linear mixed-effects models for analysis of clinical trial-based cost-effectiveness data

Economic evaluations conducted alongside randomized controlled trials are a popular vehicle for generating high-quality evidence on the incremental cost-effectiveness of competing health care interventions. Typically, in these studies, resource use (and by extension, economic costs) and clinical (or preference-based health) outcomes data are collected prospectively for trial participants to estimate the joint distribution of incremental costs and incremental benefits associated with the intervention. In this article, we extend the generalized linear mixed-model framework to enable simultaneous modeling of multiple outcomes of mixed data types, such as those typically encountered in trial-based economic evaluations, taking into account correlation of outcomes due to repeated measurements on the same individual and other clustering effects. We provide new wrapper functions to estimate the models in Stata and R by maximum and restricted maximum quasi-likelihood and compare the performance of the new routines with alternative implementations across a range of statistical programming packages. Empirical applications using observed and simulated data from clinical trials suggest that the new methods produce broadly similar results as compared with Stata’s merlin and gsem commands and a Bayesian implementation in WinBUGS. We highlight that, although these empirical applications primarily focus on trial-based economic evaluations, the new methods presented can be generalized to other health economic investigations characterized by multivariate hierarchical data structures

Economic outcomes associated with deep surgical site infection in patients with an open fracture of the lower limb

Aims The aim of this study was to estimate economic outcomes associated with deep surgical site infection (SSI) in patients with an open fracture of the lower limb. Patients and Methods A total of 460 patients were recruited from 24 specialist trauma hospitals in the United Kingdom Major Trauma Network. Preference-based health-related quality-of-life outcomes, assessed using the EuroQol EQ-5D-3L and the 6-Item Short-Form Health Survey questionnaire (SF-6D), and economic costs (£, 2014/2015 prices) were measured using participant-completed questionnaires over the 12 months following injury. Descriptive statistics and multivariate regression analysis were used to explore the relationship between deep SSI and health utility scores, quality-adjusted life-years (QALYs), and health and personal social service (PSS) costs. Results Deep SSI was associated with lower EQ-5D-3L derived QALYs (adjusted mean difference -0.102, 95% confidence interval (CI) -0.202 to 0.001, p = 0.047) and increased health and social care costs (adjusted mean difference £1950; 95% CI £1383 to £5285, p = 0.250) versus patients without deep SSI over the 12 months following injury. Conclusion Deep SSI may lead to significantly impaired health-related quality of life and increased economic costs. Our economic estimates can be used to inform clinical and budgetary service planning and can act as reference data for future economic evaluations of preventive or treatment interventions

Network meta-analysis of multiple outcome measures accounting for borrowing of information across outcomes

Background: Network meta-analysis (NMA) enables simultaneous comparison of multiple treatments while preserving randomisation. When summarising evidence to inform an economic evaluation, it is important that the analysis accurately reflects the dependency structure within the data, as correlations between outcomes may have implication for estimating the net benefit associated with treatment. A multivariate NMA offers a framework for evaluating multiple treatments across multiple outcome measures while accounting for the correlation structure between outcomes. Methods: The standard NMA model is extended to multiple outcome settings in two stages. In the first stage, information is borrowed across outcomes as well across studies through modelling the within-study and between-study correlation structure. In the second stage, we make use of the additional assumption that intervention effects are exchangeable between outcomes to predict effect estimates for all outcomes, including effect estimates on outcomes where evidence is either sparse or the treatment had not been considered by any one of the studies included in the analysis. We apply the methods to binary outcome data from a systematic review evaluating the effectiveness of nine home safety interventions on uptake of three poisoning prevention practices (safe storage of medicines, safe storage of other household products, and possession of poison centre control telephone number) in households with children. Analyses are conducted in WinBUGS using Markov Chain Monte Carlo (MCMC) simulations. Results: Univariate and the first stage multivariate models produced broadly similar point estimates of intervention effects but the uncertainty around the multivariate estimates varied depending on the prior distribution specified for the between-study covariance structure. The second stage multivariate analyses produced more precise effect estimates while enabling intervention effects to be predicted for all outcomes, including intervention effects on outcomes not directly considered by the studies included in the analysis. Conclusions: Accounting for the dependency between outcomes in a multivariate meta-analysis may or may not improve the precision of effect estimates from a network meta-analysis compared to analysing each outcome separately

Cycle threshold values are inversely associated with poorer outcomes in hospitalised patients with Covid-19:a prospective, observational cohort study conducted at a UK tertiary hospital

ABSTRACT: This single-centre observational study demonstrated that lower cycle threshold (Ct) values (indicating higher viral loads) on admission to hospital were associated with poorer outcomes in unvaccinated, hospitalized patients with coronavirus disease 2019 (COVID-19). Demographic and outcome data were collected prospectively for all adult patients who tested positive for severe acute respiratory syndrome coronavirus-2 on admission to the University Hospitals North Midlands NHS Trust between 1 February and 1 July 2020. Nasopharyngeal swab samples were obtained, and a valid Ct value was determined for all patients using the Viasure reverse transcription polymerase chain reaction assay, validated by Public Health England, on admission to hospital. Multi-variable logistic regression results based on data from 618 individuals demonstrated a significant inverse relationship between the odds of death and Ct values (adjusted odds ratio 0.95, 95% confidence interval 0.92–0.98, P=0.001). The association remained highly significant after adjusting for known clinical risk factors for COVID-1

Rapid antigen detection and molecular tests for group A streptococcal infections for acute sore throat : systematic reviews and economic evaluation

Background Sore throat is a common condition caused by an infection of the airway. Most cases are of a viral nature; however, a number of these infections may be caused by the group A Streptococcus bacterium. Most viral and bacterial sore throat infections resolve spontaneously within a few weeks. Point-of-care testing in primary care has been recognised as an emerging technology for aiding targeted antibiotic prescribing for sore throat in cases that do not spontaneously resolve. Objective Systematically review the evidence for 21 point-of-care tests for detecting group A Streptococcus bacteria and develop a de novo economic model to compare the cost-effectiveness of point-of-care tests alongside clinical scoring tools with the cost-effectiveness of clinical scoring tools alone for patients managed in primary care and hospital settings. Data sources Multiple electronic databases were searched from inception to March 2019. The following databases were searched in November and December 2018 and searches were updated in March 2019: MEDLINE [via OvidSP (Health First, Rockledge, FL, USA)], MEDLINE In-Process & Other Non-Indexed Citations (via OvidSP), MEDLINE Epub Ahead of Print (via OvidSP), MEDLINE Daily Update (via OvidSP), EMBASE (via OvidSP), Cochrane Database of Systematic Reviews [via Wiley Online Library (John Wiley & Sons, Inc., Hoboken, NJ, USA)], Cochrane Central Register of Controlled Trials (CENTRAL) (via Wiley Online Library), Database of Abstracts of Reviews of Effects (DARE) (via Centre for Reviews and Dissemination), Health Technology Assessment database (via the Centre for Reviews and Dissemination), Science Citation Index and Conference Proceedings [via the Web of Science™ (Clarivate Analytics, Philadelphia, PA, USA)] and the PROSPERO International Prospective Register of Systematic Reviews (via the Centre for Reviews and Dissemination). Review methods Eligible studies included those of people aged ≥ 5 years presenting with sore throat symptoms, studies comparing point-of-care testing with antibiotic-prescribing decisions, studies of test accuracy and studies of cost-effectiveness. Quality assessment of eligible studies was undertaken. Meta-analysis of sensitivity and specificity was carried out for tests with sufficient data. A decision tree model estimated costs and quality-adjusted life-years from an NHS and Personal Social Services perspective. Results The searches identified 38 studies of clinical effectiveness and three studies of cost-effectiveness. Twenty-six full-text articles and abstracts reported on the test accuracy of point-of-care tests and/or clinical scores with biological culture as a reference standard. In the population of interest (patients with Centor/McIsaac scores of ≥ 3 points or FeverPAIN scores of ≥ 4 points), point estimates were 0.829 to 0.946 for sensitivity and 0.849 to 0.991 for specificity. There was considerable heterogeneity, even for studies using the same point-of-care test, suggesting that is unlikely that any single study will have accurately captured a test’s true performance. There is some randomised controlled trial evidence to suggest that the use of rapid antigen detection tests may help to reduce antibiotic-prescribing rates. Sensitivity and specificity estimates for each test in each age group and care setting combination were obtained using meta-analyses where appropriate. Any apparent differences in test accuracy may not be attributable to the tests, and may have been caused by known differences in the studies, latent characteristics or chance. Fourteen of the 21 tests reviewed were included in the economic modelling, and these tests were not cost-effective within the current National Institute for Health and Care Excellence’s cost-effectiveness thresholds. Uncertainties in the cost-effectiveness estimates included model parameter inputs and assumptions that increase the cost of testing, and the penalty for antibiotic overprescriptions. Limitations No information was identified for the elderly population or pharmacy setting. It was not possible to identify which test is the most accurate owing to the paucity of evidence. Conclusions The systematic review and the cost-effectiveness models identified uncertainties around the adoption of point-of-care tests in primary and secondary care settings. Although sensitivity and specificity estimates are promising, we have little information to establish the most accurate point-of-care test. Further research is needed to understand the test accuracy of point-of-care tests in the proposed NHS pathway and in comparable settings and patient groups

Mapping between headache specific and generic preference-based health-related quality of life measures

Background: The Headache Impact Test (HIT-6) and the Chronic Headache Questionnaire (CH-QLQ) measure headache-related quality of life but are not preference-based and therefore cannot be used to generate health utilities for cost-effectiveness analyses. There are currently no established algorithms for mapping between the HIT-6 or CH-QLQ and preference-based health-related quality-of-life measures for chronic headache population. Methods: We developed algorithms for generating EQ-5D-5L and SF-6D utilities from the HIT-6 and the CHQLQ using both direct and response mapping approaches. A multi-stage model selection process was used to assess the predictive accuracy of the models. The estimated mapping algorithms were derived to generate UK tariffs and was validated using the Chronic Headache Education and Self-management Study (CHESS) trial dataset. Results: Several models were developed that reasonably accurately predict health utilities in this context. The best performing model for predicting EQ-5D-5L utility scores from the HIT-6 scores was a Censored Least Absolute Deviations (CLAD) (1) model that only included the HIT-6 score as the covariate (mean squared error (MSE) 0.0550). The selected model for CH-QLQ to EQ-5D-5L was the CLAD (3) model that included CH-QLQ summary scores, age, and gender, squared terms and interaction terms as covariates (MSE 0.0583). The best performing model for predicting SF-6D utility scores from the HIT-6 scores was the CLAD (2) model that included the HIT-6 score and age and gender as covariates (MSE 0.0102). The selected model for CH-QLQ to SF-6D was the OLS (2) model that included CH-QLQ summary scores, age, and gender as covariates (MSE 0.0086). Conclusion: The developed algorithms enable the estimation of EQ-5D-5L and SF-6D utilities from two headache-specific questionnaires where preference-based health-related quality of life data are missing. However, further work is needed to help define the best approach to measuring health utilities in headache studies

Protocol for a multi-centre, parallel-arm, 12-month, randomised controlled trial of arthroscopic surgery versus conservative care for femoroacetabular impingement syndrome (FASHIoN)

INTRODUCTION: Femoroacetabular impingement (FAI) syndrome is a recognised cause of young adult hip pain. There has been a large increase in the number of patients undergoing arthroscopic surgery for FAI; however, a recent Cochrane review highlighted that there are no randomised controlled trials (RCTs) evaluating treatment effectiveness. We aim to compare the clinical and cost-effectiveness of arthroscopic surgery versus best conservative care for patients with FAI syndrome. METHODS: We will conduct a multicentre, pragmatic, assessor-blinded, two parallel arm, RCT comparing arthroscopic surgery to physiotherapy-led best conservative care. 24 hospitals treating NHS patients will recruit 344 patients over a 26-month recruitment period. Symptomatic adults with radiographic signs of FAI morphology who are considered suitable for arthroscopic surgery by their surgeon will be eligible. Patients will be excluded if they have radiographic evidence of osteoarthritis, previous significant hip pathology or previous shape changing surgery. Participants will be allocated in a ratio of 1:1 to receive arthroscopic surgery or conservative care. Recruitment will be monitored and supported by qualitative intervention to optimise informed consent and recruitment. The primary outcome will be pain and function assessed by the international hip outcome tool 33 (iHOT-33) measured 1-year following randomisation. Secondary outcomes include general health (short form 12), quality of life (EQ5D-5L) and patient satisfaction. The primary analysis will compare change in pain and function (iHOT-33) at 12 months between the treatment groups, on an intention-to-treat basis, presented as the mean difference between the trial groups with 95% CIs. The study is funded by the Health Technology Assessment Programme (13/103/02). ETHICS AND DISSEMINATION: Ethical approval is granted by the Edgbaston Research Ethics committee (14/WM/0124). The results will be disseminated through open access peer-reviewed publications, including Health Technology Assessment, and presented at relevant conferences. TRIAL REGISTRATION NUMBER: ISRCTN64081839; Pre-results