Emulating Target Trials With Real-World Data to Inform Health Technology Assessment: Findings and Lessons From an Application to Emergency Surgery

Objectives: International health technology assessment (HTA) agencies recommend that real-world data (RWD) are used in some circumstances to add to the evidence base about the effectiveness and cost-effectiveness of health interventions. The target trial framework applies the design principles of randomized-controlled trials to RWD and can help alleviate inevitable concerns about bias and design flaws with nonrandomized studies. This article aimed to tackle the lack of guidance and exemplar applications on how this methodology can be applied to RWD to inform HTA decision making./ Methods: We use Hospital Episode Statistics data from England on emergency hospital admissions from 2010 to 2019 to evaluate the cost-effectiveness of emergency surgery for 2 acute gastrointestinal conditions. We draw on the case study to describe the main challenges in applying the target trial framework alongside RWD and provide recommendations for how these can be addressed in practice./ Results: The 4 main challenges when applying the target trial framework to RWD are (1) defining the study population, (2) defining the treatment strategies, (3) establishing time zero (baseline), and (4) adjusting for unmeasured confounding. The recommendations for how to address these challenges, mainly around the incorporation of expert judgment and use of appropriate methods for handling unmeasured confounding, are illustrated within the case study./ Conclusions: The recommendations outlined in this study could help future studies seeking to inform HTA decision processes. These recommendations can complement checklists for economic evaluations and design tools for estimating treatment effectiveness in nonrandomized studies

Life-course partnership history and midlife health behaviours in a population-based birth cohort

The research leading to these results has received funding from the European Research Council under the European Union’s Seventh Framework Programme (FP7/2007-2013)/ ERC grant agreement n° 324055.Background:  Marital and partnership history is strongly associated with health in midlife and later life. However, the role of health behaviours as an explanatory mechanism remains unclear. The aim of this study was to investigate prospective associations between life-course partnership trajectories (taking into account timing, non-marital cohabitation, remarriage and marital transitions) and health behaviours measured in midlife. Methods:  We analysed data from the British National Child Development Study, a prospective cohort study that includes all people born in 1 week of March 1958 (N=10 226). This study included men and women with prospective data on partnership history from age 23 to 42–44 and health behaviours collected at ages 42–46 (2000–2004). Latent class analysis was used to derive longitudinal trajectories of partnership history. We used multivariable regression models to estimate the association between midlife health behaviours and partnership trajectory, adjusting for various early and young adult characteristics. Results:  After adjustment for a range of potential selection factors in childhood and early adulthood, we found that problem drinking, heavy drinking and smoking were more common in men and women who experienced divorce or who had never married or cohabited. Women who married later had a lower prevalence of smoking and were less likely to be overweight than those who married earlier. Overall marriage was associated with a higher body mass index. Individuals who never married or cohabited spent less time exercising. Conclusions:  Some aspects of partnership history such as remaining unpartnered and experiencing divorce are associated with more smoking and drinking in midlife, whereas marriage is associated with midlife weight gain. Despite these offsetting influences, differences in health behaviours probably account for much of the association between partnership trajectories and health found in previous studies.Publisher PDFPeer reviewe

The application of inelastic neutron scattering to investigate the interaction of methyl propanoate with silica

A modern industrial route for the manufacture of methyl methacrylate involves the reaction of methyl propanoate and formaldehyde over a silica-supported Cs catalyst. Although the process has been successfully commercialised, little is known about the surface interactions responsible for the forward chemistry. This work concentrates upon the interaction of methyl propanoate over a representative silica. A combination of infrared spectroscopy, inelastic neutron scattering, DFT calculations, X-ray diffraction and temperature-programmed desorption is used to deduce how the ester interacts with the silica surface

Regression models for linking patterns of growth to a later outcome:Infant growth and childhood overweight

Abstract Background Regression models are widely used to link serial measures of anthropometric size or changes in size to a later outcome. Different parameterisations of these models enable one to target different questions about the effect of growth, however, their interpretation can be challenging. Our objective was to formulate and classify several sets of parameterisations by their underlying growth pattern contrast, and to discuss their utility using an expository example. Methods We describe and classify five sets of model parameterisations in accordance with their underlying growth pattern contrast (conditional growth; being bigger v being smaller; becoming bigger and staying bigger; growing faster v being bigger; becoming and staying bigger versus being bigger). The contrasts are estimated by including different sets of repeated measures of size and changes in size in a regression model. We illustrate these models in the setting of linking infant growth (measured on 6 occasions: birth, 6 weeks, 3, 6, 12 and 24 months) in weight-for-height-for-age z-scores to later childhood overweight at 8y using complete cases from the Norwegian Childhood Growth study (n = 900). Results In our expository example, conditional growth during all periods, becoming bigger in any interval and staying bigger through infancy, and being bigger from birth were all associated with higher odds of later overweight. The highest odds of later overweight occurred for individuals who experienced high conditional growth or became bigger in the 3 to 6 month period and stayed bigger, and those who were bigger from birth to 24 months. Comparisons between periods and between growth patterns require large sample sizes and need to consider how to scale associations to make comparisons fair; with respect to the latter, we show one approach. Conclusion Studies interested in detrimental growth patterns may gain extra insight from reporting several sets of growth pattern contrasts, and hence an approach that incorporates several sets of model parameterisations. Co-efficients from these models require careful interpretation, taking account of the other variables that are conditioned on

Age of First Overweight and Obesity, COVID-19 and Long COVID in Two British Birth Cohorts

Longer exposure to obesity, and thus a longer period in an inflamed state, may increase susceptibility to infectious diseases and worsen severity. Previous cross-sectional work finds higher BMI is related to worse COVID-19 outcomes, but less is known about associations with BMI across adulthood. To examine this, we used body mass index (BMI) collected through adulthood in the 1958 National Child Development Study (NCDS) and the 1970 British Cohort Study (BCS70). Participants were grouped by the age they were first overweight (> 25 kg/m2) and obese (> 30 kg/m2). Logistic regression was used to assess associations with COVID-19 (self-reported and serology-confirmed), severity (hospital admission and contact with health services) and long-COVID reported at ages 62 (NCDS) and 50 (BCS70). An earlier age of obesity and overweight, compared to those who never became obese or overweight, was associated with increased odds of adverse COVID-19 outcomes, but results were mixed and often underpowered. Those with early exposure to obesity were over twice as likely in NCDS (odds ratio (OR) 2.15, 95% confidence interval (CI) 1.17-4.00) and three times as likely in BCS70 (OR 3.01, 95% CI 1.74-5.22) to have long COVID. In NCDS they were also over four times as likely to be admitted to hospital (OR 4.69, 95% CI 1.64-13.39). Most associations were somewhat explained by contemporaneous BMI or reported health, diabetes or hypertension; however, the association with hospital admission in NCDS remained. An earlier age of obesity onset is related to COVID-19 outcomes in later life, providing evidence of the long-term impact of raised BMI on infectious disease outcomes in midlife

Pathways between Socioeconomic Disadvantage and Childhood Growth in the Scottish Longitudinal Study, 1991–2001

Socioeconomically disadvantaged children are more likely to be of shorter stature and overweight, leading to greater risk of obesity in adulthood. Disentangling the mediatory pathways between socioeconomic disadvantage and childhood size may help in the development of appropriate policies aimed at reducing these health inequalities. We aimed to elucidate the putative mediatory role of birth weight using a representative sample of the Scottish population born 1991-2001 (n = 16,628). Estimated height and overweight/obesity at age 4.5 years were related to three measures of socioeconomic disadvantage (mother's education, Scottish Index of Multiple Deprivation, synthetic weekly income). Mediation was examined using two approaches: a 'traditional' mediation analysis and a counterfactual-based mediation analysis. Both analyses identified a negative effect of each measure of socioeconomic disadvantage on height, mediated to some extent by birth weight, and a positive 'direct effect' of mother's education and Scottish Index of Multiple Deprivation on overweight/obesity, which was partly counterbalanced by a negative 'indirect effect'. The extent of mediation estimated when adopting the traditional approach was greater than when adopting the counterfactual-based approach because of inappropriate handling of intermediate confounding in the former. Our findings suggest that higher birth weight in more disadvantaged groups is associated with reduced social inequalities in height but also with increased inequalities in overweight/obesity

Using linked administrative data to aid the handling of non-response and restore sample representativeness in cohort studies: the 1958 national child development study and hospital episode statistics data

BACKGROUND: There is growing interest in whether linked administrative data have the potential to aid analyses subject to missing data in cohort studies. METHODS: Using linked 1958 National Child Development Study (NCDS; British cohort born in 1958, n = 18,558) and Hospital Episode Statistics (HES) data, we applied a LASSO variable selection approach to identify HES variables which are predictive of non-response at the age 55 sweep of NCDS. We then included these variables as auxiliary variables in multiple imputation (MI) analyses to explore the extent to which they helped restore sample representativeness of the respondents together with the imputed non-respondents in terms of early life variables (father's social class at birth, cognitive ability at age 7) and relative to external population benchmarks (educational qualifications and marital status at age 55). RESULTS: We identified 10 HES variables that were predictive of non-response at age 55 in NCDS. For example, cohort members who had been treated for adult mental illness had more than 70% greater odds of bring non-respondents (odds ratio 1.73; 95% confidence interval 1.17, 2.51). Inclusion of these HES variables in MI analyses only helped to restore sample representativeness to a limited extent. Furthermore, there was essentially no additional gain in sample representativeness relative to analyses using only previously identified survey predictors of non-response (i.e. NCDS rather than HES variables). CONCLUSIONS: Inclusion of HES variables only aided missing data handling in NCDS to a limited extent. However, these findings may not generalise to other analyses, cohorts or linked administrative datasets. This work provides a demonstration of the use of linked administrative data for the handling of missing cohort data which we hope will act as template for others