Dataset Information

External Validation of the Core Obesity Model to Assess the Cost-Effectiveness of Weight Management Interventions.

ABSTRACT:

Background

For economic models to be considered fit for purpose, it is vital that their outputs can be interpreted with confidence by clinicians, budget holders and other stakeholders. Consequently, thorough validation of models should be carried out to enhance confidence in their predictions. Here, we present results of external dependent and independent validations of the Core Obesity Model (COM), which was developed to assess the cost-effectiveness of weight management interventions.

Objective

The aim was to assess the external validity of the COM (version 6.1), in line with best practice guidance from the International Society for Pharmacoeconomics and Outcomes Research and the Society for Medical Decision Making.

Methods

For validation, suitable sources and outcomes were identified, and used to populate the COM with relevant inputs to allow prediction of study outcomes. Study characteristics were entered into the COM to replicate either the studies used to develop the model (dependent validation) or those not included in the model (independent validation). The concordance between predicted and observed outcomes was then assessed using established statistical methods and generation of mean error estimates.

Results

For most outcomes, the predictions of the COM showed good linear correlation with observed outcomes, as evidenced by the high coefficients of determination (R² values). The independent validation revealed a degree of underestimation in predictions of cardiovascular (CV) disease and mortality, and type 2 diabetes.

Conclusion

The predictions generated by the risk equations used in the COM showed good concordance both with the studies used to develop the model and with studies not included in the model. In particular, the concordance observed in the external dependent validation suggests that the COM accurately predicts obesity-related event rates observed in the studies used to develop the model. However, the impact of existing CV risk, as well as mortality, is a key area for future refinement of the COM. Our results should increase confidence in the estimates derived from the COM and reduce uncertainty associated with analyses using this model.

SUBMITTER: Lopes S

PROVIDER: S-EPMC7578171 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

External Validation of the Core Obesity Model to Assess the Cost-Effectiveness of Weight Management Interventions.

Lopes Sandra S Johansen Pierre P Lamotte Mark M McEwan Phil P Olivieri Anamaria-Vera AV Foos Volker V

PharmacoEconomics 20201001 10

<h4>Background</h4>For economic models to be considered fit for purpose, it is vital that their outputs can be interpreted with confidence by clinicians, budget holders and other stakeholders. Consequently, thorough validation of models should be carried out to enhance confidence in their predictions. Here, we present results of external dependent and independent validations of the Core Obesity Model (COM), which was developed to assess the cost-effectiveness of weight management interventions.< ...[more]

PMID: 32656686

Similar Datasets

Project description:BACKGROUND:The use of apps to tackle overweight and obesity by tracking physical and dietary patterns and providing recommendations and motivation strategies to achieve personalized goals has increased over recent years. However, evidence of the efficacy, effectiveness, and safety of these apps is severely lacking. OBJECTIVE:The aim of this study was to identify efficacy, safety, and effectiveness criteria used to assess weight control, overweight, and obesity management in mobile health (mHealth) interventions through a systematic review. METHODS:PubMed, PsycINFO, Scopus, UK Trial Database, ClinicalTrials.gov, and the Cochrane Library were surveyed up to May 2018. All types of clinical studies were considered. A total of 2 independent reviewers assessed quality using Scottish Intercollegiate Guidelines Network (SIGN) criteria. Ratings were used to provide an overall score for each study (low, moderate, or high). Data were synthesized in evidence tables. RESULTS:From 233 potentially relevant publications, only 28 studies were included. Of these, 13 (46%) were randomized control trials, 11 were single-arm studies (39%), 3 were nonrandomized controlled trials (11%), and 1 study was a cluster randomized trial (4%). The studies were classified as low (15), high (7), and moderate (6) quality according to SIGN criteria. All studies focused on efficacy, with only 1 trial mentioning safety and another 1 effectiveness. In 11 studies, the apps were used as stand-alone interventions, the others were multicomponent studies that included other tools for support such as sensors or websites. The main management tool included in the apps was feedback messaging (24), followed by goal-setting mechanisms (20) and self-monitoring (19). The majority of studies took weight or body mass index loss as the main outcome (22) followed by changes in physical activity (14) and diet (12). Regarding outputs, usability, adherence, and engagement (17) were the most reported, followed by satisfaction (7) and acceptability (4). CONCLUSIONS:There is a remarkable heterogeneity among these studies and the majority have methodological limitations that leave considerable room for improvement. Further research is required to identify all relevant criteria for assessing the efficacy of mHealth interventions in the management of overweight and obesity. TRIAL REGISTRATION:PROSPERO CRD42017056761; https://tinyurl.com/y2zhxtjx.

Project description:BackgroundThe 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. Current methods for estimating cost-effectiveness of interventions for obesity may be subject 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 findingsWe 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.ConclusionsMendelian 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.

Project description:BACKGROUND:Childhood obesity is associated with a multitude of co-morbidities, including hypertension, hyperlipidaemia, cardiovascular disease and type 2 diabetes. Childhood obesity can also affect a young person's social, emotional and mental health if they encounter negative prejudice and social marginalisation. Given the prevalence of overweight and obese children globally, it is imperative that effective interventions are developed. Children are receptive to information conveyed via digital means, therefore, the use of technology may play a crucial role in interventions to reduce childhood obesity. This systematic review aimed to review and critically appraise the literature published to date in relation to the effectiveness of technology-based interventions, employed as secondary prevention, in addressing childhood obesity. METHODS:An electronic search strategy was undertaken in Medline and Embase, covering publications up to and including 12th July 2018. Randomised controlled trials assessing the effectiveness of technology-based interventions on weight-related outcomes in children, aged 8 to 18, published only in the English language, were included. RESULTS:From an initial search total of 1012 studies, 11 met the inclusion criteria. They were assessed for methodological quality using the Cochrane Risk of Bias Tool for Randomised Controlled Trials and were analysed using a narrative approach. The findings of this review showed a limited potential of technology-based interventions, employed as secondary prevention, to address childhood obesity. Of the eleven studies reviewed, three (27%) showed a positive relationship between technology-based interventions and weight-related outcomes in overweight or obese children. CONCLUSIONS:This review suggests that technology-based interventions, primarily active video games, as well as internet or web-based interventions and mobile phone communications, may, with further research, have the potential to impact positively on weight-related outcomes. It is difficult to determine the degree of efficacy of these technology-based interventions, as only two databases were searched, selecting only English language articles. Moreover, the included studies demonstrated a lack of high-quality evidence. The lack and heterogeneity of studies with technology-based interventions is a further limitation.

Dataset Information

External Validation of the Core Obesity Model to Assess the Cost-Effectiveness of Weight Management Interventions.

Background

Objective

Methods

Results

Conclusion

Publications

External Validation of the Core Obesity Model to Assess the Cost-Effectiveness of Weight Management Interventions.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets