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Contribution of the Cluster randomised triAl of PSA testing for Prostate cancer (CAP) to the ongoing debate on the value of prostate cancer screening

Mendelian randomization analysis of the causal impact of body mass index and waist-hip ratio on rates of hospital admission

We analyze how measures of adiposity – body mass index (BMI) and waist hip ratio (WHR) – causally influence rates of hospital admission. Conventional analyses of this relationship are susceptible to omitted variable bias from variables that jointly influence both hospital admission and adipose status. We implement a novel quasi-Poisson instrumental variable model in a Mendelian randomization framework, identifying causal effects from random perturbations to germline genetic variation. We estimate the individual and joint effects of BMI, WHR, and WHR adjusted for BMI. We also implement multivariable instrumental variable methods in which the causal effect of one exposure is estimated conditionally on the causal effect of another exposure. Data on 310,471 participants and over 550,000 inpatient admissions in the UK Biobank were used to perform one-sample and two-sample Mendelian randomization analyses. The results supported a causal role of adiposity on hospital admissions, with consistency across all estimates and sensitivity analyses. Point estimates were generally larger than estimates from comparable observational specifications. We observed an attenuation of the BMI effect when adjusting for WHR in the multivariable Mendelian randomization analyses, suggesting that an adverse fat distribution, rather than a higher BMI itself, may drive the relationship between adiposity and risk of hospital admission.

Assessing the Causal Impact of Adiposity Variation on Rates of Hospital Admission: Application of Mendelian Randomization

Cost-effectiveness of rapid laboratory-based mass-spectrometry diagnosis of bloodstream infection: Evidence from the RAPIDO randomised controlled trial

Objectives and intervention Bloodstream infection, the presence of viable micro-organisms in the blood, is a prevalent clinical event associated with substantial mortality. Patient outcomes may be improved when the causative micro-organism is identified quickly. We assessed the cost-effectiveness of rapid microbial identification by matrix-assisted laser desorption/ionisation time-of-flight (MALDI-TOF) mass spectrometry. Design Economic evaluation alongside a randomised multicentre trial (RAPIDO: RAPId Diagnosis on Outcome) assessing the impact of rapid identification by MALDI-TOF spectrometry. Setting Adult inpatients with bloodstream infections at seven National Health Service hospital trusts in England and Wales. Primary outcome Net monetary benefit, estimated as incremental costs compared with incremental 28-day survival, of rapid identification by MALDI-TOF spectrometry compared with conventional identification. Methods Patients were randomised (1:1) to receive diagnosis by conventional methods of microbial identification (conventional arm) only or by MALDI-TOF spectrometry in addition to conventional identification (RAPIDO arm). Results Data from 5550 patients were included in primary analysis. Mean imputed costs in 2018/2019 prices per patient were lower by £126 in the RAPIDO arm (95% CI-£784 to £532) but the proportion of patients alive at day 28 was lower (81.4% vs 82.3%). The probability of cost-effectiveness of MALDI-TOF was <0.5 at cost-effectiveness thresholds between £20 000 and £50 000. Conclusions Adjunctive MALDI-TOF diagnosis was unlikely to be cost-effective when measured as cost per death avoided at 28 days. However, the differences between arms in cost and effect were modest, associated with uncertainty and may not accurately reflect 'real-world' routine use of MALDI-TOF technology in this patient group. Trial registration numbers ISRCTN97107018/UKCRN 11978.

Long-term cost-effectiveness of interventions for obesity: A mendelianAU randomisation: PerPLOSstyle study ; eponymic

The prevalence of obesity has increased in the United Kingdom, and reliably measuring the impact on quality of life and the total healthcare cost from obesity is key to informing the cost-effectiveness of interventions that target obesity, and determining healthcare funding. shouldbelowercase Current methods :Hencefor ; allinstancesofcapitalizedMendelianhavebeenchangedtolowercasemendelianthroughoutthetext estimating cost-effectiveness of interventions for obesity may be sub- : ject to confounding and reverse causation. The aim of this study is to apply a new approach using mendelian randomisation for estimating the cost-effectiveness of interventions that target body mass index (BMI), which may be less affected by confounding and reverse causation than previous approaches. Methods and findings We estimated health-related quality-adjusted life years (QALYs) and both primary and secondary healthcare costs for 310,913 men and women of white British ancestry aged between 39 and 72 years in UK Biobank between recruitment (2006 to 2010) and 31 March 2017. We then estimated the causal effect of differences in BMI on QALYs and total healthcare costs using mendelian randomisation. For this, we used instrumental variable regression with a polygenic risk score (PRS) for BMI, derived using a genome-wide association study (GWAS) of BMI, with age, sex, recruitment centre, and 40 genetic principal components as covariables to estimate the effect of a unit increase in BMI on QALYs and total healthcare costs. Finally, we used simulations to estimate the likely effect on BMI of policy relevant interventions for BMI, then used the mendelian randomisation estimates to estimate the cost-effectiveness of these interventions. A unit increase in BMI decreased QALYs by 0.65% of a QALY (95% confidence interval [CI]: 0.49% to 0.81%) per year and increased annual total healthcare costs by £42.23 (95% CI: £32.95 to £51.51) per person. When considering only health conditions usually considered in previous cost-effectiveness modelling studies (cancer, cardiovascular disease, cerebrovascular disease, and type 2 diabetes), we estimated that a unit increase in BMI decreased QALYs by only 0.16% of a QALY (95% CI: 0.10% to 0.22%) per year. We estimated that both laparoscopic bariatric surgery among individuals with BMI greater than 35 kg/m2, and restricting volume promotions for high fat, salt, and sugar products, would increase QALYs and decrease total healthcare costs, with net monetary benefits (at £20,000 per QALY) of £13,936 (95% CI: £8,112 to £20,658) per person over 20 years, and £546 million (95% CI: £435 million to £671 million) in total per year, respectively. The main limitations of this approach are that mendelian randomisation relies on assumptions that cannot be proven, including the absence of directional pleiotropy, and that genotypes are independent of confounders. Conclusions Mendelian randomisation can be used to estimate the impact of interventions on quality of life and healthcare costs. We observed that the effect of increasing BMI on health-related quality of life is much larger when accounting for 240 chronic health conditions, compared with only a limited selection. This means that previous cost-effectiveness studies have likely underestimated the effect of BMI on quality of life and, therefore, the potential cost-effectiveness of interventions to reduce BMI.

Robust causal inference for long-term policy decisions: cost effectiveness of interventions for obesity using Mendelian randomization

Objectives: To estimate the cost-effectiveness of interventions to reduce body mass index (BMI) using Mendelian randomization. Design We estimated the causal effect of differences in BMI on quality-adjusted life years (QALYs) and total healthcare costs using Mendelian randomization and applied our results to policy-relevant questions. Setting UK Biobank. Participants 310,913 men and women of white British ancestry aged between 39 and 72 years, followed-up for an average of 8.1 years (6.1 years for secondary care healthcare costs). Main outcome measures Predicted average QALYs and total healthcare costs per year, and cost-effectiveness of interventions. Results A unit increase in BMI decreased QALYs by 0.65% of a QALY (95% confidence interval [CI]: 0.49% to 0.81%) per year and increased annual total healthcare costs by 42.23 (95% CI: 32.95 to 51.51) per person. When considering only health conditions usually considered in previous studies (cancer, cardiovascular disease, cerebrovascular disease and type 2 diabetes), we estimated that a unit increase in BMI decreased QALYs by only 0.16% of a QALY (95% CI: 0.10% to 0.22%) per year. Compared to no intervention and over 20 years, a person in England or Wales aged 40-69 years with a BMI over 35 kg/m2 receiving laparoscopic bariatric surgery would have, on average, an increase of 0.92 QALYs (95% CI: 0.66 to 1.17) and a decrease in total healthcare costs of 5,096 (95% CI: 3,459 to 6,852), with a net monetary benefit (at 20,000 per QALY) of 13,936 (95% CI: 8,112 to 20,658). Restricting volume promotions for high fat, salt and sugar products would, across the 21.7 million adults aged 40 to 69 years in England and Wales, increase QALYs by 20,551 per year (95% CI: 15,335 to 25,301), decrease total healthcare costs by 137 million per year (95% CI: 106 million to 170 million), with a net monetary benefit (at 20,000 per QALY) of 546 million per year (95% CI: 435 million to 671 million). Between 1993 and 2017 in England and Wales, the increase in BMI of people aged 40 to 69 years led to a decrease of 1.13% of a QALY per person per year (95% CI: 0.90% to 1.38%) and an increase in annual healthcare costs of 69 per person (95% CI: 53 to 84). Compared to if all people with a BMI above 25 kg/m2 aged 40 to 69 years in England and Wales in 2017 had a BMI of 25 kg/m2, QALYs are decreased by 580,494 in total per year (95% CI: 457,907 to 717,691) and annual healthcare costs are increased by 3.58 billion (95% CI: 2.75 billion to 4.34 billion). Conclusions Mendelian randomization can be used to estimate the impact of interventions on quality of life and healthcare costs. The effect of increasing BMI on health-related quality of life is much larger when accounting for 240 chronic health conditions, compared with only a limited selection.

Estimating the causal effect of genetic liability to prevalent disease on hospital costs using Mendelian Randomization

ABSTRACT BACKGROUND Accurate measurement of the effects of disease status on healthcare cost is important in the pragmatic evaluation of interventions but is complicated by endogeneity biases due to omitted variables and reverse causality. Mendelian Randomization, the use of random perturbations in germline genetic variation as instrumental variables, can avoid these limitations. We report a novel Mendelian Randomization analysis of the causal effect of liability to disease on healthcare costs. METHODS We used Mendelian Randomization to model the causal impact on inpatient hospital costs of liability to six highly prevalent diseases: asthma, eczema, migraine, coronary heart disease, type 2 diabetes, and major depressive disorder. We identified genetic variants from replicated genome-wide associations studies and estimated their association with inpatient hospital costs using data from UK Biobank, a large prospective cohort study of individuals linked to records of hospital care. We assessed potential violations of the instrumental variable assumptions, particularly the exclusion restriction (i.e. variants affecting costs through alternative paths). We also conducted new genome wide association studies of hospital costs within the UK Biobank cohort as a further “split sample”sensitivity analysis. RESULTS We analyzed data on 307,032 individuals. Genetic variants explained only a small portion of the variance in each disease phenotype. Liability to coronary heart disease had substantial impacts (mean per person per year increase in costs from allele score Mendelian Randomization models: £712 (95% confidence interval: £238 to £1,186)) on inpatient hospital costs in causal analysis, but other results were imprecise. There was concordance of findings across varieties of sensitivity analyses, including stratification by sex, and those obtained from the split sample analysis. CONCLUSION A novel Mendelian Randomization analysis of the causal effect of liability to disease on healthcare cost demonstrates that this type of analysis is feasible and informative in this context. There was concordance across data sources and across methods bearing different assumptions. Selection into the relatively healthy UK Biobank cohort and the modest proportion of variance in disease status accounted for by the allele scores reduced the precision of our estimates. We therefore could not exclude the possibility of substantial costs due to these diseases. JEL Classification Numbers H51, I10, I11, I18,

Mendelian Randomization analysis of the causal impact of body mass index and waist-hip ratio on rates of hospital admission

We analyze how measures of adiposity – body mass index (BMI) and waist-hip ratio (WHR) – causally influence rates of hospital admission. Conventional analyses of this relationship are susceptible to omitted variable bias from variables that jointly influence both hospital admission and adipose status. We implement a novel quasi-Poisson instrumental variable modelsin a Mendelian Randomization framework, identifying causal effects from random perturbations to germline genetic variation. We estimate the individual and joint effects of BMI, WHR, and WHR adjusted for BMI. We also implement multivariable instrumental variable methods in which the causal effect of one exposure is estimated conditionally on the causal effect of another exposure. Data on 310,471 participants and over 550,000 inpatient admissions in the UK Biobank were used to perform one-sample and two-sample Mendelian Randomization analyses. The results supported a causal role of adiposity on hospital admissions, with consistency across all estimates and sensitivity analyses. Point estimates were generally larger than estimates from comparable observational specifications. We observe an attenuation of the BMI effect when adjusting for WHR in the multivariable Mendelian Randomization analyses, suggesting that an adverse fat distribution, rather than a higher BMI itself, may drive the relationship between adiposity and risk of hospital admission.

Observational Cost-Effectiveness Analysis Using Routine Data: Admission and Discharge Care Bundles for Patients with Chronic Obstructive Pulmonary Disease

Background: Chronic obstructive pulmonary disease (COPD) is a prevalent respiratory disease, and accounts for a substantial proportion of unplanned hospital admissions. Care bundles for COPD are a set of standardised, evidence-based interventions that may improve outcomes in hospitalised COPD patients. We estimated the cost effectiveness of care bundles for acute exacerbations of COPD using routinely collected observational data. Methods: Data were collected from implementation (n = 7) and comparator (n = 7) acute hospitals located in England and Wales. We conducted a difference-in-difference cost-effectiveness analysis using a secondary care (i.e. hospital) perspective to examine the effect on National Health Service (NHS) costs and 90-day mortality of implementing care bundles compared with usual care for patients admitted to hospital with an acute exacerbation of COPD. Adjusted models included as covariates patient age, sex, deprivation, ethnicity and seasonal effects and mixed effects for site. Results: Outcomes and baseline characteristics of up to 12,532 patients were analysed using both complete case and multiply imputed models. Implementation of bundles varied. COPD care bundles were associated with slightly lower secondary care costs, but there was no evidence that they improved outcomes once adjustments were made for site and baseline covariates. Care bundles were unlikely to be cost effective for the NHS with an estimated net monetary benefit per 90-day death avoided from an adjusted multiply imputed model of −£1231 (95% confidence interval − £2428 to − £35) at a high cost-effectiveness threshold of £50,000 per 90-day death avoided. Conclusion and Recommendations: Care bundles for COPD did not appear to be cost effective, although this finding may have been influenced by unmeasured variations in bundle implementation and other potential confounding factors.

The causal effects of health conditions and risk factors on social and socioeconomic outcomes: Mendelian randomization in UK Biobank

Background: We aimed to estimate the causal effect of health conditions and risk factors on social and socioeconomic outcomes in UK Biobank. Evidence on socioeconomic impacts is important to understand because it can help governments, policy makers and decision makers allocate resources efficiently and effectively. Methods: We used Mendelian randomization to estimate the causal effects of eight health conditions (asthma, breast cancer, coronary heart disease, depression, eczema, migraine, osteoarthritis, type 2 diabetes) and five health risk factors [alcohol intake, body mass index (BMI), cholesterol, systolic blood pressure, smoking] on 19 social and socioeconomic outcomes in 336 997 men and women of White British ancestry in UK Biobank, aged between 39 and 72 years. Outcomes included annual household income, employment, deprivation [measured by the Townsend deprivation index (TDI)], degree-level education, happiness, loneliness and 13 other social and socioeconomic outcomes. Results: Results suggested that BMI, smoking and alcohol intake affect many socioeconomic outcomes. For example, smoking was estimated to reduce household income [mean difference = -£22 838, 95% confidence interval (CI): -£31 354 to -£14 321] and the chance of owning accommodation [absolute percentage change (APC) = -20.8%, 95% CI: -28.2% to -13.4%], of being satisfied with health (APC = -35.4%, 95% CI: -51.2% to -19.5%) and of obtaining a university degree (APC = -65.9%, 95% CI: -81.4% to -50.4%), while also increasing deprivation (mean difference in TDI = 1.73, 95% CI: 1.02 to 2.44, approximately 216% of a decile of TDI). There was evidence that asthma decreased household income, the chance of obtaining a university degree and the chance of cohabiting, and migraine reduced the chance of having a weekly leisure or social activity, especially in men. For other associations, estimates were null. Conclusions: Higher BMI, alcohol intake and smoking were all estimated to adversely affect multiple social and socioeconomic outcomes. Effects were not detected between health conditions and socioeconomic outcomes using Mendelian randomization, with the exceptions of depression, asthma and migraines. This may reflect true null associations, selection bias given the relative health and age of participants in UK Biobank, and/or lack of power to detect effects.

Cost-Effectiveness of Sertraline in Primary Care According to Initial Severity and Duration of Depressive Symptoms: Findings from the PANDA RCT

Background: Antidepressants are commonly prescribed for depression, but it is unclear whether treatment efficacy depends on severity and duration of symptoms and how prescribing might be targeted cost-effectively. Objectives: We investigated the cost-effectiveness of the antidepressant sertraline compared with placebo in subgroups defined by severity and duration of depressive symptoms. Methods: We undertook a cost-effectiveness analysis from the perspective of the NHS and Personal and Social Services (PSS) in the UK alongside the PANDA (What are the indications for Prescribing ANtiDepressants that will leAd to a clinical benefit?) randomised controlled trial (RCT), which compared sertraline with placebo over a 12-week period. Quality of life data were collected at baseline and at 2, 6, and 12 weeks post-randomisation using EQ-5D-5L, from which we calculated quality-adjusted life years (QALYs). Costs (in 2017/18£) were collected using patient records and from resource use questionnaires administered at each follow-up interval. Differences in mean costs and mean QALYs and net monetary benefits were estimated. Our primary analysis used net monetary benefit regressions to identify any interaction between the cost-effectiveness of sertraline and subgroups defined by baseline symptom severity (0–11; 12–19; 20+ on the Clinical Interview Schedule—Revised) and, separately, duration of symptoms (greater or less than 2 years duration). A secondary analysis estimated the cost-effectiveness of sertraline versus placebo, irrespective of duration or severity. Results: There was no evidence of an association between the baseline severity of depressive symptoms and the cost-effectiveness of sertraline. Compared to patients with low symptom severity, the expected net benefits in patients with moderate symptoms were £24 (95% CI − £280 to £328; p value 0.876) and the expected net benefits in patients with high symptom severity were £37 (95% CI − £221 to £296; p value 0.776). Patients who had a longer history of depressive symptoms at baseline had lower expected net benefits from sertraline than those with a shorter history; however, the difference was uncertain (− £27 [95% CI − £258 to £204]; p value 0.817). In the secondary analysis, patients treated with sertraline had higher expected net benefits (£122 [95% CI £18 to £226]; p value 0.101) than those in the placebo group. Sertraline had a high probability (> 95%) of being cost-effective if the health system was willing to pay at least £20,000 per QALY gained. Conclusions: We found insufficient evidence of a prespecified threshold based on severity or symptom duration that GPs could use to target prescribing to a subgroup of patients where sertraline is most cost-effective. Sertraline is probably a cost-effective treatment for depressive symptoms in UK primary care. Trial Registration: Controlled Trials ISRCTN Registry, ISRCTN84544741.

Assessing the construct validity and responsiveness of Preference-Based Measures (PBMs) in cataract surgery patients

Purpose: The validity and responsiveness of the EQ-5D-3L in visual conditions has been questioned, inspiring development of a vision ‘bolt-on’ domain (EQ-5D-3L + VIS). Developments in preference-based measures (PBM) also includes the EQ-5D-5L and the ICECAP-O capability wellbeing measure. This study aimed to examine the construct validity and responsiveness of the EQ-5D-3L, EQ-5D-5L, EQ-5D-3L + VIS and ICECAP-O in cataract surgery patients for the first time, to inform choice of PBM for economic evaluation in this population. Methods: The analyses used data from the UK Predict-CAT cataract surgery cohort study. PBMs and the Cat-PROM5 [a validated measure of cataract quality of life (QOL)] were completed before surgery and 4–8 weeks after. Construct validity was assessed using correlations and known-group differences evaluated using regression. Responsiveness was evaluated using effect sizes and analysis of variance to compare change scores between groups, defined by patient-reported and clinical outcomes. Results: The sample comprised 1315 patients at baseline. No PBMs were associated with visual acuity and only the ICECAP-O (Spearman’s rs = − 0.35), EQ-5D-3L + VIS (rs = − 0.42) and EQ-5D-5L (Value Set for England rs = − 0.31) correlated at least moderately with the Cat-PROM5. Effect sizes of change were consistently largest for the EQ-5D-3L + VIS (range 0.34–0.41), followed by the ICECAP-O (range 0.20–0.34). Results indicated no improvement in responsiveness using the EQ-5D-5L (range 0.13–0.16) compared to the EQ-5D-3L (range 0.17–0.20). Conclusions: Whilst no PBMs comprehensively demonstrated evidence of construct validity and responsiveness in cataract surgery patients, the ICECAP-O was the most responsive generic PBM to improvements in QOL. Surprisingly the EQ-5D-5L was not more responsive than the EQ-5D-3L in this setting.

Mendelian Randomization analysis of the causal effect of adiposity on hospital costs

Estimates of the marginal effect of measures of adiposity such as body mass index (BMI) on healthcare costs are important for the formulation and evaluation of policies targeting adverse weight profiles. Most estimates of this association are affected by endogeneity bias. We use a novel identification strategy exploiting Mendelian Randomization – random germline genetic variation modelled using instrumental variables – to identify the causal effect of BMI on inpatient hospital costs. Using data on over 300,000 individuals, the effect size per person per marginal unit of BMI per year varied according to specification, including £21.22 (95% confidence interval (CI): £14.35-£28.07) for conventional inverse variance weighted models to £18.85 (95% CI: £9.05-£28.65) for penalized weighted median models. Effect sizes from Mendelian Randomization models were larger in most cases than non-instrumental variable multivariable adjusted estimates (£13.47, 95% CI: £12.51-£14.43). There was little evidence of non-linearity. Within-family estimates, intended to address dynastic biases, were imprecise.

Mapping to Quality of Life and Capability Measures in Cataract Surgery Patients: From Cat-PROM5 to EQ-5D-3L, EQ-5D-5L, and ICECAP-O Using Mixture Modelling

Objectives. Cataract is a prevalent and potentially blinding eye condition. Cataract surgery, the only proven treatment for this condition, is a very frequently undertaken procedure. The objective of this analysis was to develop a mapping algorithm that could be used to predict quality of life and capability scores from the Cat-PROM5, a newly developed, validated patient-reported outcome measure for patients undergoing cataract surgery. Methods. We estimated linear models and adjusted limited dependent variable mixture models. Data were taken from the Predict-CAT cohort of up to 1181 patients undergoing cataract surgery at two sites in England. The Cat-PROM5 was mapped to two quality of life measures (EQ-5D-3L and EQ-5D-5L) and one capability measure (ICECAP-O). All patients reported ICECAP-O and one or other of the EQ-5D measures both before and after cataract surgery. Model performance was assessed using likelihood statistics, graphical inspections of model fit, and error measurements. Results. Adjusted limited dependent variable mixture models dominated linear models on all performance criteria. Mixture models offered very good fit. Three component models that allowed component membership to be a function of covariates (age, sex, and diabetic status depending on specification and outcome measure) and which conditioned on covariates offered the best performance in almost all cases. An exception was the EQ-5D-5L post-surgery for which a two-component model was selected. Conclusions. Mapping from Cat-PROM5 to quality of life and capability measures using adjusted limited dependent variable mixture models is feasible, and the estimates can be used to support cost-effectiveness analysis in relation to cataract care. Mixture models performed strongly for both quality of life outcomes and capability outcomes.

The causal effect of adiposity on hospital costs: Mendelian Randomization analysis of over 300,000 individuals from the UK Biobank

Estimates of the marginal effect of measures of adiposity such as body mass index (BMI) on healthcare costs are important for the formulation and evaluation of policies targeting adverse weight profiles. Many existing estimates of this association are affected by endogeneity bias caused by simultaneity, measurement error and omitted variables. The contribution of this study is to avoid this bias by using a novel identification strategy – random germline genetic variation in an instrumental variable analysis – to identify the presence and magnitude of the causal effect of BMI on inpatient hospital costs. We also use data on genetic variants to undertake much richer testing of the sensitivity of results to potential violations of the instrumental variable assumptions than is possible with existing approaches. Using data on over 300,000 individuals, we found effect sizes for the marginal unit of BMI more than 50% larger than multivariable effect sizes. These effects attenuated under sensitivity analyses, but remained larger than multivariable estimates for all but one estimator. There was little evidence for non-linear effects of BMI on hospital costs. Within-family estimates, intended to address dynastic biases, were null but suffered from low power. This paper is the first to use genetic variants in a Mendelian Randomization framework to estimate the causal effect of BMI (or any other disease/trait) on healthcare costs. This type of analysis can be used to inform the cost-effectiveness of interventions and policies targeting the prevention and treatment of overweight and obesity, and for setting research priorities.

The Causal Effects of Health Conditions and Risk Factors on Social and Socioeconomic Outcomes: Mendelian Randomization in UK Biobank

Objectives To estimate the causal effect of health conditions and risk factors on social and socioeconomic outcomes in UK Biobank. Evidence on socioeconomic impacts is important to understand because it can help governments, policy-makers and decision-makers allocate resources efficiently and effectively. Design We used Mendelian randomization to estimate the causal effects of eight health conditions (asthma, breast cancer, coronary heart disease, depression, eczema, migraine, osteoarthritis, type 2 diabetes) and five health risk factors (alcohol intake, body mass index [BMI], cholesterol, systolic blood pressure, smoking) on 19 social and socioeconomic outcomes. Setting UK Biobank. Participants 337,009 men and women of white British ancestry, aged between 39 and 72 years. Main outcome measures Annual household income, employment, deprivation (measured by the Townsend deprivation index [TDI]), degree level education, happiness, loneliness, and 13 other social and socioeconomic outcomes. Results Results: suggested that BMI, smoking and alcohol intake affect many socioeconomic outcomes. For example, smoking was estimated to reduce household income (mean difference = −£24,394, 95% confidence interval (CI): −£33,403 to −£15,384), the chance of owning accommodation (absolute percentage change [APC] = −21.5%, 95% CI: −29.3% to −13.6%), being satisfied with health (APC = −32.4%, 95% CI: −48.9% to −15.8%), and of obtaining a university degree (APC = −73.8%, 95% CI: −90.7% to −56.9%), while also increasing deprivation (mean difference in TDI = 1.89, 95% CI: 1.13 to 2.64, approximately 236% of a decile of TDI). There was evidence that asthma increased deprivation and decreased both household income and the chance of obtaining a university degree, and migraine reduced the chance of having a weekly leisure or social activity, especially in men. For other associations, estimates were null. Conclusions Higher BMI, alcohol intake and smoking were all estimated to adversely affect multiple social and socioeconomic outcomes. Effects were not detected between health conditions and socioeconomic outcomes using Mendelian randomization, with the exceptions of depression, asthma and migraines. This may reflect true null associations, selection bias given the relative health and age of participants in UK Biobank, and/or lack of power to detect effects. What is known? Studies have shown associations between poor health and adverse social (e.g. wellbeing, social contact) and socioeconomic (e.g. educational attainment, income, employment) outcomes, but there is also strong evidence that social and socioeconomic factors influence health. These bidirectional relationships make it difficult to establish whether health conditions and health risk factors have causal effects on social and socioeconomic outcomes. Mendelian randomization is a technique that uses genetic variants robustly related to an exposure of interest (here, health conditions and risk factors for poor health) as a proxy for the exposure. Since genetic variants are randomly allocated at conception, they tend to be unrelated to the factors that typically confound observational studies, and are less likely to suffer from reverse causality, making causal inference from Mendelian randomization analyses more plausible. What this study adds This study suggests causal effects of higher BMI, smoking and alcohol use on a range of social and socioeconomic outcomes, implying that population-level improvements in these risk factors may, in addition to the well-known health benefits, have social and socioeconomic benefits for individuals and society. There was evidence that asthma increased deprivation, decreased household income and the chance of having a university degree, migraine reduced the chance of having a weekly leisure or social activity, especially in men, and depression increased loneliness and decreased happiness. There was little evidence for causal effects of cholesterol, systolic blood pressure or breast cancer on social and socioeconomic outcomes.

Care bundles to reduce re-admissions for patients with chronic obstructive pulmonary disease: a mixed-methods study

BackgroundChronic obstructive pulmonary disease (COPD) is the commonest respiratory disease in the UK, accounting for 10% of emergency hospital admissions annually. Nearly one-third of patients are re-admitted within 28 days of discharge.ObjectivesThe study aimed to evaluate the effectiveness of introducing standardised packages of care (i.e. care bundles) as a means of improving hospital care and reducing re-admissions for COPD.DesignA mixed-methods evaluation with a controlled before-and-after design.ParticipantsAdults admitted to hospital with an acute exacerbation of COPD in England and Wales.InterventionCOPD care bundles.Main outcome measuresThe primary outcome was re-admission to hospital within 28 days of discharge. The study investigated secondary outcomes including length of stay, total number of bed-days, in-hospital mortality, 90-day mortality, context, process and costs of care, and staff, patient and carer experience.Data sourcesRoutine NHS data, including numbers of COPD admissions and re-admissions, in-hospital mortality and length of stay data, were provided by 31 sites for 12 months before and after the intervention roll-out. Detailed pseudo-anonymised data on care during admission were collected from a subset of 14 sites, in addition to information about delivery of individual components of care collected from random samples of medical records at each location. Six case study sites provided data from interviews, observation and documentary review to explore implementation, engagement and perceived impact on delivery of care.ResultsThere is no evidence that care bundles reduced 28-day re-admission rates for COPD. All-cause re-admission rates, in-hospital mortality, length of stay, total number of bed-days, and re-admission and mortality rates in the 90 days following discharge were similar at implementation and comparator sites, as were resource utilisation, NHS secondary care costs and cost-effectiveness of care. However, the rate of emergency department (ED) attendances decreased more in implementation sites than in comparator sites {implementation: incidence rate ratio (IRR) 0.63 [95% confidence interval (CI) 0.56 to 0.70]; comparator: IRR 1.14 (95% CI 1.04 to 1.26) interaction p LimitationsThe observational nature of the study design means that secular trends and residual confounding cannot be discounted as potential sources of any observed between-site differences. The availability of data from some sites was suboptimal.ConclusionsCare bundles are valued by health-care professionals, but were challenging to implement and there was a blurring of the distinction between the implementation and comparator groups, which may have contributed to the lack of effect on re-admissions and mortality. Care bundles do appear to be associated with a reduced number of subsequent ED attendances, but care bundles are unlikely to be cost-effective for COPD.Future workA longitudinal study using implementation science methodology could provide more in-depth insights into the implementation of care bundles.Trial registrationCurrent Controlled Trials ISRCTN13022442.FundingThis project was funded by the National Institute for Health Research Health Services and Delivery Research programme and will be published in full in Health Services and Delivery Research; Vol. 7, No. 21. See the NIHR Journals Library website for further project information.

Antidepressant treatment with sertraline for adults with depressive symptoms in primary care: The PANDA research programme including RCT

Background: Despite a growing number of prescriptions for antidepressants (over 70 million in 2018), there is uncertainty about when people with depression might benefit from antidepressant medication and concern that antidepressants are prescribed unnecessarily. Objectives: The main objective of the PANDA (What are the indications for Prescribing ANtiDepressAnts that will lead to a clinical benefit?) research programme was to provide more guidance about when antidepressants are likely to benefit people with depression. We aimed to estimate the minimal clinically important difference for commonly used self-administered scales for depression and anxiety, and to understand more about how patients respond to such assessments. We carried out an observational study of patients with depressive symptoms and a placebo-controlled randomised controlled trial of sertraline versus placebo to estimate the treatment effect in UK primary care. The hypothesis was that the severity and duration of symptoms were related to treatment response. Design: The programme consisted of three phases. The first phase relied on the secondary analysis of existing data extracted from published trials. The second phase was the PANDA cohort study of patients with depressive symptoms who presented to primary care and were followed up 2, 4 and 6 weeks after a baseline assessment. Both quantitative and qualitative methods were used in the analysis. The third phase was a multicentre randomised placebo-controlled double-blind trial of sertraline versus placebo in patients presenting to primary care with depressive symptoms. Setting: UK primary care in Bristol, London, Liverpool and York. Participants: Patients aged 18–74 years who were experiencing depressive symptoms in primary care. Eligibility for the PANDA randomised controlled trial included that there was uncertainty about the benefits about treatment with an antidepressant. Interventions: In the PANDA randomised controlled trial, patients were individually randomised to 100 mg daily of sertraline or an identical placebo. The PANDA cohort study was an observational study. Main outcome measures: Depressive symptoms measured using the Patient Health Questionnaire were the primary outcome for the randomised controlled trial. Other outcomes included anxiety symptoms using the Generalised Anxiety Disorder-7; depressive symptoms using the Beck Depression Inventory, version 2; health-related quality of life; self-reported improvement; and cost-effectiveness. Results: The secondary analysis of existing randomised controlled trials [GENetic and clinical Predictors Of treatment response in Depression (GenPod), TREAting Depression with physical activity (TREAD) and Clinical effectiveness and cost-effectiveness of cognitive Behavioural Therapy as an adjunct to pharmacotherapy for treatment-resistant depression in primary care (CoBalT)] found evidence that the minimal clinically important difference increased as the initial severity of depressive symptoms rose. Our estimates of minimal clinically important difference were a 17% and 18% reduction in Beck Depression Inventory scores for GenPod and TREAD, respectively. In CoBalT, a 32% reduction corresponded to the minimal clinically important difference but the participants in this study had depression that had not responded to antidepressants. In the PANDA study cohort, and from our analyses in existing data, we found that the minimal clinically important difference varies considerably with the initial severity of depressive and anxiety symptoms. Expressing the minimal clinically important difference as a percentage reduction reduces this variation at higher scores, but at low scores the percentage reduction increased substantially. The results from the qualitative studies pointed out many limitations of the Patient Health Questionnaire-9 items in assessing change and recovery from depression. In the PANDA randomised controlled trial, there was no evidence that sertraline resulted in a reduction in depressive symptoms within 6 weeks of randomisation, but there was some evidence of a reduction by 12 weeks. However, sertraline led to a reduction in anxiety symptoms, an improvement of mental health-related quality of life and an increased likelihood of reporting improvement. The mean Patient Health Questionnaire-9 items score at 6 weeks was 7.98 (standard deviation 5.63) in the sertraline group and 8.76 (standard deviation 5.86) in the placebo group (5% relative reduction, 95% confidence interval –7% to 15%; p = 0.41). Of the secondary outcomes, there was strong evidence that sertraline reduced anxiety symptoms (Generalised Anxiety Disorder-7 score reduced by 17% (95% confidence interval 9% to 25%; p = 0.00005). Sertraline had a high probability (> 90%) of being cost-effective at 12 weeks. The PANDA randomised controlled trial found no evidence that treatment response or cost-effectiveness was related to severity or duration of depressive symptoms. The minimal clinically important difference estimates suggested that sertraline’s effect on anxiety, but not on depression, was likely to be clinically important. Limitations: The results from the randomised controlled trial and the estimates of minimal clinically important difference were not sufficiently precise to provide specific clinical guidance for individuals. We had low power in testing whether or not initial severity and duration of depressive symptoms are related to treatment response. Conclusions: The results of the trial support the use of sertraline and probably other selective serotonin reuptake inhibitors because of their action in reducing anxiety symptoms and the likelihood of longer-term benefit on depressive symptoms. Sertraline could be prescribed for anxiety symptoms that commonly occur with depression and many patients will experience a clinical benefit. The Patient Health Questionnaire-9 items and similar self-administered scales should not be used on their own to assess clinical outcome, but should be supplemented with further clinical assessment. Future work: We need to examine the longer-term effects of antidepressant treatment. We need more precise estimates of the treatment effects and minimal clinically important difference at different severities to provide more specific guidance for individuals. However, the methods we have developed provide an approach towards providing such detailed guidance. Trial registration: Current Controlled Trials ISRCTN84544741 and EudraCT number 2013-003440-22.

The Association Between Adiposity and Inpatient Hospital Costs in the UK Biobank Cohort

Background: High adiposity is associated with higher risks for a variety of adverse health outcomes, including higher rates of age-adjusted mortality and increased morbidity. This has important implications for the management of healthcare systems, since the endocrinal, cardiometabolic and other changes associated with increased adiposity may be associated with substantial healthcare costs. Methods: We studied the association between various measures of adiposity and inpatient hospital costs through record linkage between UK Biobank and records of inpatient care in England and Wales. UK Biobank is a large prospective cohort study that aimed to recruit men and women aged between 40 and 69 from 2006 to 2010. We applied generalised linear models to cost per person year to estimate the marginal effect of adiposity, and average adjusted predicted costs of adiposity. Results: Valid cost and body mass index (BMI) data from 457,689 participants were available for inferential analysis. Some 54.4% of individuals included in the analysis sample had positive inpatient healthcare costs over the period of follow-up. Median hospital costs per person-year of follow-up were £89, compared to mean costs of £481. Mean BMI overall was 27.4 kg/m2 (standard deviation 4.8). The marginal effect of a unit increase in BMI was £13.61 (99% confidence interval £12.60–£14.63) per person-year of follow up. The marginal effect of a standard deviation increase in BMI was £69.20 (99% confidence interval £64.98–£73.42). The marginal effect of becoming obese was £136.35 (99% confidence interval £124.62–£148.08). Average adjusted predicted inpatient hospital costs increased almost linearly when modelled using continuous measure of adiposity. Sensitivity analysis of different scenarios did not substantially change these conclusions, although there was some evidence of attenuation of the effects of adiposity when controlling for waist-hip ratios, and when individuals who self-reported any pre-existing conditions were excluded from analysis. Conclusions: Higher adiposity is associated with higher inpatient hospital costs. Further scrutiny using causal inferential methods is warranted to establish if further public health investments are required to manage the large healthcare costs observationally associated with overweight and obesity.

Evaluation of 'care bundles' for patients with chronic obstructive pulmonary disease (COPD): A multisite study in the UK

Background Chronic obstructive pulmonary disease (COPD) accounts for 10% of emergency hospital admissions in the UK annually. Nearly 33% of patients are readmitted within 28 days of discharge. We evaluated the effectiveness of implementing standardised packages of care called 'care bundles' on COPD readmission, emergency department (ED) attendance, mortality, costs and process of care. Methods This is a mixed-methods, controlled before-and-after study with nested case studies. 31 acute hospitals in England and Wales which introduced COPD care bundles (implementation sites) or provided usual care (comparator sites) were recruited and provided monthly aggregate data. 14 sites provided additional individual patient data. Participants were adults admitted with an acute exacerbation of COPD. Results There was no evidence that care bundles reduced 28-day COPD readmission rates: OR=1.02 (95% CI 0.83 to 1.26). However, the rate of ED attendance was reduced in implementation sites over and above that in comparator sites (implementation: IRR=0.63 (95% CI 0.56 to 0.71); comparator: IRR=1.12 (95% CI 1.02 to 1.24); group-time interaction p<0.001). At implementation sites, delivery of all bundle elements was higher but was only achieved in 2.2% (admissions bundle) and 7.6% (discharge bundle) of cases. There was no evidence of cost-effectiveness. Staff viewed bundles positively, believing they help standardise practice and facilitate communication between clinicians. However, they lacked skills in change management, leading to inconsistent implementation. Discussion COPD care bundles were not effectively implemented in this study. They were associated with a reduced number of subsequent ED attendances, but not with change in readmissions, mortality or reduced costs. This is unsurprising given the low level of bundle uptake in implementation sites, and it remains to be determined if COPD care bundles affect patient care and outcomes when they are effectively implemented. Trial registration number ISRCTN13022442.