Long-term cost-effectiveness of interventions for obesity: A mendelian randomisation study

Valuing behavioral interventions for obesity reduction: A scoping review of economic models

Policymakers require health economic modeling to guide their decision-making over the choice of interventions for obesity. This scoping review was undertaken to report on the health economic models in use for estimating the value of behavioral interventions (individual or population level) for obesity reduction. Electronic databases (MEDLINE, Embase, PsycINFO, EconLit, and Web of Science) were searched for publications meeting inclusion criteria from January 2015 to May 2023. Seventy-three studies were included, using 44 health economic models between them. When considered against the expert recommendations for modeling of this type, only four models (9%) met all five key elements. The element most commonly unfulfilled was the use of a microsimulation modeling approach (41%, n = 18), followed by model validation (46%, n = 20). A majority of models met each of the other elements: use of a lifetime horizon (59%, n = 26), inclusion of key health events (66%, n = 29), and a risk equation approach to event simulation (71%, n = 31). In addition, under half of the studies considered health inequalities in their reporting. Continued proliferation of models with inadequate time horizons, breadth of obesity-related health conditions, and perspectives on costs and outcomes risks underestimation of the benefits of longer term interventions and impacts on health inequalities.

Visceral obesity augments prescription use: An analysis of the cross-sectional study of NHANES 2011-2018

BACKGROUND

Visceral obesity (VATob) increases the risk for many diseases. Central obesity has been associated with an augmented prescription use; however, there is a paucity of research focused on VATob. Here, the aim was to evaluate the association between VATob and prescription use.

METHODS

Data was collected from the NHANES dataset (2011-2018). Visceral adipose tissue was measured using dual x-ray absorptiometry, and VATob was defined as ≥100 cm2. Prescription use was collected from the RXQ_RX files and classified according to Vademecum. Association between VATob and prescription use was determined with logistic regression and reported as odds ratios (ORs) with 95% confidence intervals (95%CIs).

RESULTS

10,952 participants (weighted: 121,090,702) were included, in which 41.8% were VATob and 52.0% of them had ≥1 prescription. Overall, VATob demonstrated an augmented rate of prescription use when compared to non-VATob (52.0% versus 36.7%, p<0.001), specifically with metabolic (4.5-fold increase), cardiovascular (3.9-fold increase), gastrointestinal (2.5-fold increase), and hematopoietic agents (2.3-fold increase). This was associated with increased the risk for overall prescription use (ORoverall = 1.9, 95%CI: 1.7-2.1, p<0.001). Similar results were observed with metabolic and cardiovascular agents. However, when stratified by BMI, normal weight participants (ORmetabolic = 10.4; 95%CI: 6.5-16.6 & ORcardiovascular = 7.0; 95%CI: 4.4-11.1, p<0.001) had a greater risk than the overweight (ORmetabolic = 4.1; 95%CI: 3.0-5.6 & ORcardiovascular = 3.4; 95%CI: 2.5-4.7, p<0.001) or obese participants (ORmetabolic = 3.5; 95%CI: 2.3-5.3 & ORcardiovascular = 3.5; 95%CI: 2.5-4.9, p<0.001).

CONCLUSION

VATob is associated with augmented prescription use, particularly with cardiovascular and metabolic agents. This association was higher for normal weight participants.

Taking a health economic perspective in monitoring health inequalities: A focus on excess weight

BACKGROUND

Traditional approaches to monitoring health inequalities predominantly rely on headcount methods. However, these methods fail to reflect the non-linear health economic implications of changes in disease severity. Alternative, distribution-sensitive metrics are available which could more adequately inform financial planning and policy decision making.

METHODS

We describe the design of the Foster-Greer-Thorbecke (FGT) index, and discuss its relative merits as a summary monitoring metric of health inequalities in the population, compared to the Erreygers concentration index. We illustrate the FGT index by conducting a comparative longitudinal analysis of adult excess inequalities in England using Health Survey for England data from 2009 to 2019.

FINDINGS

Excess weight inequalities have steadily increased in the English adult population, especially over the last five years. Going beyond headcount, the FGT index analyses revealed that, unlike the rest of the population, the average overweight adult from the most socio-economically deprived group is either obese (30.3 BMI for females) or at the brink of obesity (29.1 BMI for males). These results underscore a deepening divide in obesity severity between communities, with the most socioeconomically deprived groups being increasingly and disproportionally affected.

CONCLUSIONS

The FGT index can address some shortcomings of traditional approaches to inequality measurement and local governments should consider adopting it as an alternative population health metric. Future research should apply and develop more refined distribution-sensitive measures of health inequality.

Potential health and economic impact of achieving Kenya's overweight and obesity reduction target: a modelling study

Introduction

Kenya has adopted the WHO target of halting the rise of overweight, including obesity, by 2025. This paper assesses the potential impact of achieving the set target on health, healthcare cost and productivity.

Methods

We used a proportional multistate life table model (Kenya Obesity Model) to simulate the 2019 population of Kenya over their lifetime. We compared a scenario in which body mass index (BMI) distributions stabilise in 2025 against one whose BMI distributions stabilise in 2044, and quantified changes in disease-specific health outcomes, healthcare costs and productivity. We searched the literature to identify the best estimates of the total and disease-specific healthcare costs in Kenya. We used the Human Capital Approach to estimate productivity gains.

Results

If BMI distributions stabilised in 2025, an estimated 6.8 million health-adjusted life years (HALYs) (95% uncertainty interval (UI) 5.8-7.9 million) would be saved over the lifetime of the 2019 Kenyan population (135 HALYs per 1000 persons). A total of US$755 million in body mass-related healthcare costs could be saved by 2044 (US$15 per capita). For context, this equates to 16% of Kenya's annual healthcare expenditure. Over the lifetime, ~US$3 billion healthcare costs could be saved (US$62 per capita). By 2044, the total productivity gain resulting from a reduction in high BMI-related mortality and morbidity (combined) was ~US$5.8 billion (~US$237 per capita).

Conclusion

Achieving Kenya's overweight and obesity reduction target could improve health outcomes and also yield substantial healthcare cost savings and productivity gains.

Mendelian Randomization and Transcriptomic Analysis Reveal the Protective Role of NKT Cells in Sepsis

Background

Sepsis is a life-threatening clinical syndrome caused by dysregulated host response to infection. The mechanism underlying sepsis-induced immune dysfunction remains poorly understood. Natural killer T (NKT) cells are cytotoxic lymphocytes that bridge the innate and adaptive immune systems, the role of NKT cells in sepsis is not entirely understood, and NKT cell cluster differences in sepsis remain unexplored.

Methods

Mendelian randomization (MR) analyses were first conducted to investigate the causal relationship between side scatter area (SSC-A) on NKT cells and 28-day mortality of septic patients. A prospective and observational study was conducted to validate the relationship between the percentage of NKT cells and 28-day mortality of sepsis. Then, the single-cell RNA sequencing (scRNA-seq) data of peripheral blood mononuclear cells (PBMCs) from healthy controls and septic patients were profiled.

Results

MR analyses first revealed the protective roles of NKT cells in the 28-day mortality of sepsis. Then, 115 septic patients were enrolled. NKT percentage was significantly higher in survivors (n = 84) compared to non-survivors (n = 31) (%, 5.00 ± 3.46 vs 2.18 ± 1.93, P < 0.0001). Patients with lower levels of NKT cells exhibited a significantly increased risk of 28-day mortality. According to scRNA-seq analysis, NKT cell clusters exhibited multiple distinctive characteristics, including a distinguishing cluster defined as FOS+NKT cells, which showed a significant decrease in sepsis. Pseudo-time analysis showed that FOS+NKT cells were characterized by upregulated expression of crucial functional genes such as GZMA and CCL4. CellChat revealed that interactions between FOS+NKT cells and adaptive immune cells including B cells and T cells were decreased in sepsis compared to healthy controls.

Conclusion

Our findings indicate that NKT cells may protect against sepsis, and their percentage can predict 28-day mortality. Additionally, we discovered a unique FOS+NKT subtype crucial in sepsis immune response, offering novel insights into its immunopathogenesis.

Role of obesity in lower mortality risk in sepsis: a meta-analysis of observational studies

This meta-analysis aims to explore the correlation between obesity and mortality in patients with sepsis. Data were gathered from various sources, including PubMed, the Cochrane Library, and Embase (no language restrictions). Clinical studies, both retrospective and prospective ones, were selected to analyze mortality due to sepsis in patients with or without obesity. The Newcastle-Ottawa Scale was used to assess the quality of the studies included. In data synthesis, odds ratio (OR) and 95% confidence interval (CI) were meta-analyzed using the DerSimonian-Laird random-effects model, followed by sensitivity and heterogeneity analyses. Two cohort studies were included to investigate survival in inpatients with obesity and sepsis, with pooled analysis indicating a lowered mortality rate (OR=0.88; 95% CI: 0.81-0.95; I2=0.00%; P=0.000). This meta-analysis lends support to the obesity paradox, suggesting a reduced mortality from sepsis in obese patients. However, further prospective trials and research on mechanisms are needed to test this hypothesis.

Causal Estimation of Long-term Intervention Cost-effectiveness Using Genetic Instrumental Variables: An Application to Cancer

BACKGROUND

This article demonstrates a means of assessing long-term intervention cost-effectiveness in the absence of data from randomized controlled trials and without recourse to Markov simulation or similar types of cohort simulation.

METHODS

Using a Mendelian randomization study design, we developed causal estimates of the genetically predicted effect of bladder, breast, colorectal, lung, multiple myeloma, ovarian, prostate, and thyroid cancers on health care costs and quality-adjusted life-years (QALYs) using outcome data drawn from the UK Biobank cohort. We then used these estimates in a simulation model to estimate the cost-effectiveness of a hypothetical population-wide preventative intervention based on a repurposed class of antidiabetic drugs known as sodium-glucose cotransporter-2 (SGLT2) inhibitors very recently shown to reduce the odds of incident prostate cancer.

RESULTS

Genetic liability to prostate cancer and breast cancer had material causal impacts on either or both health care costs and QALYs. Mendelian randomization results for the less common cancers were associated with considerable uncertainty. SGLT2 inhibition was unlikely to be a cost-effective preventative intervention for prostate cancer, although this conclusion depended on the price at which these drugs would be offered for a novel anticancer indication.

IMPLICATIONS

Our new causal estimates of cancer exposures on health economic outcomes may be used as inputs into decision-analytic models of cancer interventions such as screening programs or simulations of longer-term outcomes associated with therapies investigated in randomized controlled trials with short follow-ups. Our method allowed us to rapidly and efficiently estimate the cost-effectiveness of a hypothetical population-scale anticancer intervention to inform and complement other means of assessing long-term intervention value.

HIGHLIGHTS

The article demonstrates a novel method of assessing long-term intervention cost-effectiveness without relying on randomized controlled trials or cohort simulations.Mendelian randomization was used to estimate the causal effects of certain cancers on health care costs and quality-adjusted life-years (QALYs) using data from the UK Biobank cohort.Given causal data on the association of different cancer exposures on costs and QALYs, it was possible to simulate the cost-effectiveness of an anticancer intervention.Genetic liability to prostate cancer and breast cancer significantly affected health care costs and QALYs, but the hypothetical intervention using SGLT2 inhibitors for prostate cancer may not be cost-effective, depending on the drug's price for the new anticancer indication. The methods we propose and implement can be used to efficiently estimate intervention cost-effectiveness and to inform decision making in all manner of preventative and therapeutic contexts.

Counting the lifetime cost of obesity: Analysis based on national England data

AIM

Obesity has a significant impact on all-cause mortality rate and overall health care resource use (HCRU). These outcomes are also strongly linked to age, sex and local deprivation of the population. We aimed to establish the lifetime costs of obesity by demographic group/geographic area using published mortality rates and HCRU use for integrated care boards (ICB) in England in the context of costs of therapeutic intervention.

METHODS

Population and expected mortality rates by age, sex and deprivation were obtained from national data. Obesity class prevalence was taken from the health of the nation study. The published impact of obesity by age, group, sex and deprivation on mortality and HCRU were applied to estimate life years lost and lifetime HCRU [by sex, age band and body mass index (BMI) class for each ICB]. The year 2019 was chosen as the study basis data to avoid influences of COVID-19 pandemic on obesity rates with application of 2022/23 HCRU values. Outcomes including prevalence, deaths, life years lost, HCRU and lifetime HCRU were compared by age and sex groups across four BMI classes normal/underweight (BMI <25 kg/m2 ), overweight (25-29.9 kg/m2 ), obese class I and II (30-39.9 kg/m2 ), and obese class III (≥40), with benchmarking being set against all population being BMI <25 kg/m2 overall and by each of the 42 ICBs. We also associated future life with deaths to provide an estimate of 'future life years lost' occurring each year.

RESULTS

Total population aged >16 years was 45.4 million (51% female).

PREVALENCE

13.7 million (28% of the total adult population) had a BMI ≥30 mg/m2 and BMI ≥40 kg/m2 were 1.50 million (12%) of these 1.0 million (68%) were female and of these 0.6 million 40% were women aged 16-49 years. In addition, 35% of those with a BMI ≥40 kg/m2 were in the top deprivation quintile (i.e. overall 20%). Mortality was based on expected deaths of 518K/year, and modelling suggested that if a BMI <25 kg/m2 was achieved in all individuals, the death rate would fall by 63K to 455K/year for the English population (12% reduction). For those with a BMI ≥40 kg/m2 the predicted reduction was 12K deaths (54% lower); while in those aged 16-49 years with a BMI ≥40 kg/m2 72% of deaths were linked to obesity. For future life years lost, we estimated 2.5 years were lost in people with BMI 30-39.9 kg/m2 6.7 years when BMI ≥40 kg/m2 . However, for those aged 16-49 years with a BMI ≥40 kg/m2 , 8.3 years were lost. HCRU, for weight reduction, the annual HCRU decrease from BMI ≥40 kg/m2 to BMI 30-39.9 kg/m2 was £342 per person and from BMI 30-39.9 to 25-29.9 kg/m2 the reduction was £316/person. However, lifetime costs were similar because of reduced life expectancy for obese individuals. In quality adjusted life years (QALY), overall, 791 689 future life years were lost (13.1% of all) in people with BMI ≥25 kg/m2 and were related to excess weight. When the NICE £30 000 per QALY value was applied to the estimated total 791 689 future life years lost then the potential QALY value reduction lost was equivalent to £24 billion/year or £522/person in the obese population. For morbidly obese men and women the potential QALY value lost was £2864/person/year. Regarding geography, across the 42 ICBs, we observed significant variation in the prevalence of BMI ≥40 (1.8%-4.3%), excess mortality (11.6%-15.4%) and HCRU linked to higher BMI (7.2%-8.8%). The areas with the greatest impact on HCRU were in the north-west, north-east and Midlands of England, while the south shows less impact.

CONCLUSION

The expected increases in annual HCRU because of obesity, when considered over a lifetime, are being mitigated by the increased mortality of obese individuals. Our data suggest that simple short-term HCRU reduction brought about through BMI reduction will be insufficient to fund additional specialist weight reduction interventions. The HRCUs associated with BMI are not in most cases related to short-term health conditions. They are a cumulative result over a number of years, so for age 16-49 years reducing BMI from ≥40 to 30-39.9 kg/m2 might show an annual decrease in HCRU/person by £325/year for women and £80/year for men but this might not have immediately occurred within that year. For those aged >70 years reducing BMI from ≥40 to 30-39.9 kg/m2 might show an annual decrease in HCRU/person by £777/year for women and £796/year for men but also may not be manifest within that year. However, for the morbidly obese men and women, the potential QALY value lost was £2864 per person per year with the potential for these funds to be applied to intensive weight management programmes, including pharmacotherapy.

Cost-effectiveness analysis of individual-level obesity treatment in paediatrics: A scoping review

OBJECTIVES

This scoping review informs a health economics perspective on the treatment of paediatric obesity. The results detail recently published research findings on the cost-effectiveness of paediatric obesity treatments and identify key characteristics of cost-effective interventions.

METHODS

A structured search was applied to six databases with no data restriction through March 2023: Medline, Embase, Cochrane CENTRAL, CINAHL, and PsycINFO. Studies that included a cost analysis of an individual level, weight management intervention (behavioural, pharmacotherapy, and surgical) in youth, with obesity, ages 2 to 21 years were eligible for inclusion.

RESULTS

Of the 4371 records identified in the initial search, 353 underwent full-text review, 39 studies met the pre-specified inclusion criteria. The majority were published after 2010 (n = 36/39, 92%) and applied to high-income countries (n = 39/39, 100%). Thirty-five of the studies assessed the cost-effectiveness of lifestyle interventions (90%), and four studies assessed surgical outcomes (10%). No pharmacotherapy studies met eligibility criteria. Although the outcome measures differed across the studies, all four surgical interventions were reported to be cost-effective. Thirty of the 35 (85%) lifestyle modification studies were reported to be cost-effective compared to the study comparator examined.

CONCLUSIONS

There is a small amount of evidence that individual-level paediatric obesity treatment interventions are cost-effective and, in some cases cost-saving, with most of this work conducted on behavioural interventions. The economic evaluation of paediatric obesity interventions poses various methodologic challenges, which should be addressed in future research to fully use the potential of economic evaluation as an aid to decision-making.

Lipid-Lowering Strategies for Primary Prevention of Coronary Heart Disease in the UK: A Cost-Effectiveness Analysis

AIM

We aimed to assess the cost effectiveness of four different lipid-lowering strategies for primary prevention of coronary heart disease initiated at ages 30, 40, 50, and 60 years from the UK National Health Service perspective.

METHODS

We developed a microsimulation model comparing the initiation of a lipid-lowering strategy to current standard of care (control). We included 458,692 participants of the UK Biobank study. The four lipid-lowering strategies were: (1) low/moderate-intensity statins; (2) high-intensity statins; (3) low/moderate-intensity statins and ezetimibe; and (4) inclisiran. The main outcome was the incremental cost-effectiveness ratio for each lipid-lowering strategy compared to the control, with 3.5% annual discounting using 2021 GBP (£); incremental cost-effectiveness ratios were compared to the UK willingness-to-pay threshold of £20,000-£30,000 per quality-adjusted life-year.

RESULTS

The most effective intervention, low/moderate-intensity statins and ezetimibe, was projected to lead to a gain in quality-adjusted life-years of 0.067 per person initiated at 30 and 0.026 at age 60 years. Initiating therapy at 40 years of age was the most cost effective for all lipid-lowering strategies, with incremental cost-effectiveness ratios of £2553 (95% uncertainty interval: 1270, 3969), £4511 (3138, 6401), £11,107 (8655, 14,508), and £1,406,296 (1,121,775, 1,796,281) per quality-adjusted life-year gained for strategies 1-4, respectively. Incremental cost-effectiveness ratios were lower for male individuals (vs female individuals) and for people with higher (vs lower) low-density lipoprotein-cholesterol. For example, low/moderate-intensity statin use initiated from age 40 years had an incremental cost-effectiveness ratio of £5891 (3822, 9348), £2174 (772, 4216), and was dominant (i.e. cost saving; -2,760, 350) in female individuals with a low-density lipoprotein-cholesterol of ≥ 3.0, ≥ 4.0 and ≥ 5.0 mmol/L, respectively. Inclisiran was not cost effective in any sub-group at its current price.

CONCLUSIONS

Low-density lipoprotein-cholesterol lowering from early ages is a more cost-effective strategy than late intervention and cost effectiveness increased with the increasing lifetime risk of coronary heart disease.

Integrated Analyses of Single-Cell Transcriptome and Mendelian Randomization Reveal the Protective Role of Resistin in Sepsis Survival in Intensive Care Unit

The high morbidity and mortality rates associated with sepsis highlight the challenges of finding specific remedies for this condition in the intensive care unit (ICU). This study aimed to explore the differentially expressed genes (DEGs) specific to cell types in sepsis and investigate the role of resistin in the survival of sepsis patients through Mendelian randomization (MR) analyses. We used single-cell and bulk transcriptome data to identify cell type-specific DEGs between sepsis and healthy controls. MR analyses were then conducted to investigate the causal relationships between resistin (one of the identified DEGs) levels and the survival of sepsis patients. Additionally, we utilized meQTL (methylation quantitative trait loci) to identify cytosine-phosphate-guanine (CpG) sites that may directly affect sepsis. We identified 560 cell type-specific DEGs between sepsis and healthy controls. Notably, we observed the upregulation of resistin levels in macrophages during sepsis. In bulk transcriptome, RETN is also upregulated in sepsis samples compared with healthy controls. MR analyses revealed a negative association existed between the expression of resistin, at both gene and protein levels, and the mortality or severity of sepsis patients in ICU. Moreover, there were no associations observed between resistin levels and death or organ failure due to other causes. We also identified three methylation CpG sites, located in RETN or its promoter region-cg06633066, cg22322184, and cg02346997-that directly affected both resistin protein levels and sepsis death in the ICU. Our findings suggest that resistin may provide feasible protection for sepsis patients, particularly those with severe cases, without serious side effects. Therefore, resistin could be a potential drug candidate for sepsis treatment. Additionally, we identified two CpG sites, cg06633066 and cg22322184, that were associated with RETN protein levels and sepsis death, providing novel insights into the underlying mechanisms of sepsis.

Systematic comparison of Mendelian randomisation studies and randomised controlled trials using electronic databases

OBJECTIVE

To scope the potential for (semi)-automated triangulation of Mendelian randomisation (MR) and randomised controlled trials (RCTs) evidence since the two methods have distinct assumptions that make comparisons between their results invaluable.

METHODS

We mined ClinicalTrials.Gov, PubMed and EpigraphDB databases and carried out a series of 26 manual literature comparisons among 54 MR and 77 RCT publications.

RESULTS

We found that only 13% of completed RCTs identified in ClinicalTrials.Gov submitted their results to the database. Similarly low coverage was revealed for Semantic Medline (SemMedDB) semantic triples derived from MR and RCT publications -36% and 12%, respectively. Among intervention types that can be mimicked by MR, only trials of pharmaceutical interventions could be automatically matched to MR results due to insufficient annotation with Medical Subject Headings ontology. A manual survey of the literature highlighted the potential for triangulation across a number of exposure/outcome pairs if these challenges can be addressed.

CONCLUSIONS

We conclude that careful triangulation of MR with RCT evidence should involve consideration of similarity of phenotypes across study designs, intervention intensity and duration, study population demography and health status, comparator group, intervention goal and quality of evidence.

Quantifying the causal impact of biological risk factors on healthcare costs

Understanding the causal impact that clinical risk factors have on healthcare-related costs is critical to evaluate healthcare interventions. Here, we used a genetically-informed design, Mendelian Randomization (MR), to infer the causal impact of 15 risk factors on annual total healthcare costs. We calculated healthcare costs for 373,160 participants from the FinnGen Study and replicated our results in 323,774 individuals from the United Kingdom and Netherlands. Robust causal effects were observed for waist circumference (WC), adult body mass index, and systolic blood pressure, in which a standard deviation increase corresponded to 22.78% [95% CI: 18.75-26.95], 13.64% [10.26-17.12], and 13.08% [8.84-17.48] increased healthcare costs, respectively. A lack of causal effects was observed for certain clinically relevant biomarkers, such as albumin, C-reactive protein, and vitamin D. Our results indicated that increased WC is a major contributor to annual total healthcare costs and more attention may be given to WC screening, surveillance, and mitigation.

Loss of Health State Utilities Attributable to Obesity

OBJECTIVES

This study aimed to quantify the association between the loss of health state utilities (LHSU) and obesity, considering different obesity categories. This is relevant to interventions economic evaluations and for public policy decision planning.

METHODS

Using data from the Chilean National Health Survey, this study uses linear regression models and counterfactual scenarios to calculate the prevalent burden, population averages, and total sum of LHSU attributable to obesity for the Chilean national level on people older than 15 years, year 2017. Adjustments for socioeconomic status and associated noncommunicable diseases (NCDs) are considered. Calculating the LHSU using these methods enables the approximation of loss of prevalent quality-adjusted life-years (QALYs).

RESULTS

The raw obesity LHSU burden was 9.1% (95% uncertainty interval [UI] 5.1-13). When adjustment is considered, the LHSU attributable to obesity reaches 4.6% (95% UI 0.6-8.5) being responsible for 121 045 prevalent QALYs. Socioeconomic status adjusted analysis of higher body mass index (BMI, in kg/m²) categories of obesity shows a dose-response effect for LHSU, being the BMI ≥ 40 category with the highest population average of attributable LHSU (10.1; 95% UI 5.5-14.5, scale 0 [full health] to 100 [dead]). Burden for BMI ≥ 35 categories showed the biggest change after NCD adjustment.

CONCLUSIONS

Obesity carries a significant burden of QALY loss. Policy decision-making addressing obesity should focus specially on the BMI ≥ 40 group. NCD comorbidity should be considered for policies addressing the BMI ≥ 35 group.

Cost-Effectiveness of Smoking Cessation Interventions in Patients With Ischemic Stroke and Transient Ischemic Attack

BACKGROUND

Smoking cessation rates after stroke and transient ischemic attack are suboptimal, and smoking cessation interventions are underutilized. We performed a cost-effectiveness analysis of smoking cessation interventions in this population.

METHODS

We constructed a decision tree and used Markov models that aimed to assess the cost-effectiveness of varenicline, any pharmacotherapy with intensive counseling, and monetary incentives, compared with brief counseling alone in the secondary stroke prevention setting. Payer and societal costs of interventions and outcomes were modeled. The outcomes were recurrent stroke, myocardial infarction, and death using a lifetime horizon. Estimates and variance for the base case (35% cessation), costs and effectiveness of interventions, and outcome rates were imputed from the stroke literature. We calculated incremental cost-effectiveness ratios and incremental net monetary benefits. An intervention was considered cost-effective if the incremental cost-effectiveness ratio was less than the willingness-to-pay threshold of $100 000 per quality-adjusted life-year (QALY) or when the incremental net monetary benefit was positive. Probabilistic Monte Carlo simulations modeled the impact of parameter uncertainty.

RESULTS

From the payer perspective, varenicline and pharmacotherapy with intensive counseling were associated with more QALYs (0.67 and 1.00, respectively) at less total lifetime costs compared with brief counseling alone. Monetary incentives were associated with 0.71 more QALYs at an additional cost of $120 compared with brief counseling alone, yielding an incremental cost-effectiveness ratio of $168/QALY. From the societal perspective, all 3 interventions provided more QALYs at less total costs compared with brief counseling alone. In 10 000 Monte Carlo simulations, all 3 smoking cessation interventions were cost-effective in >89% of runs.

CONCLUSIONS

For secondary stroke prevention, it is cost-effective and potentially cost-saving to deliver smoking cessation therapy beyond brief counseling alone.

Staple Food Preference and Obesity Phenotypes: The Regional Ethnic Cohort Study in Northwest China

Staple food preference vary in populations, but evidence of its associations with obesity phenotypes are limited. Using baseline data (n = 105,840) of the Regional Ethnic Cohort Study in Northwest China, staple food preference was defined according to the intake frequency of rice and wheat. Overall and specifically abdominal fat accumulation were determined by excessive body fat percentage and waist circumference. Logistic regression and equal frequency substitution methods were used to evaluate the associations. We observed rice preference (consuming rice more frequently than wheat; 7.84% for men and 8.28% for women) was associated with a lower risk of excessive body fat (OR, 0.743; 95%CI, 0.669-0.826) and central obesity (OR, 0.886; 95%CI, 0.807-0.971) in men; and with lower risk of central obesity (OR, 0.898; 95%CI, 0.836-0.964) in women, compared with their wheat preference counterparties. Furthermore, similar but stronger inverse associations were observed in participants with normal body mass index. Wheat-to-rice (5 times/week) reallocations were associated with a 36.5% lower risk of normal-weight obesity in men and a 20.5% lower risk of normal-weight central obesity in women. Our data suggest that, compared with wheat, rice preference could be associated with lower odds ratios of certain obesity phenotypes in the Northwest Chinese population.

Integrating the Biology of Cardiovascular Disease into the Epidemiology of Economic Decision Modelling via Mendelian Randomisation

Health economic analyses are essential for health services research, providing decision-makers and payers with evidence about the value of interventions relative to their opportunity cost. However, many health economic approaches are still limited, especially regarding the primary prevention of cardiovascular disease (CVD). In this article, we discuss some limitations to current health economic models and then outline an approach to address these via the incorporation of genomics into the design of health economic models for CVD. We propose that when a randomised clinical trial is not possible or practical, health economic models for primary prevention of CVD can be based on Mendelian randomisation analyses, a technique to assess causality in observational data. We discuss the advantages of this approach, such as integrating well-known disease biology into health economic models and how this may overcome current statistical approaches to assessing the benefits of interventions. We argue that this approach may provide the economic argument for integrating genomics into clinical practice and the efficient targeting of newer therapeutics, transforming our approach to the primary prevention of CVD, thereby moving from reactive to preventive healthcare. We end by discussing some limitations and potential pitfalls of this approach.

Causal relationship between insomnia and tuberculosis: A bi-directional Mendelian randomization analysis

Previous observational studies appear to have established a bi-directional association between sleep disorders and tuberculosis. However, their conclusions are prone to be biased by confounding effects and reverse causation due to the nature of observational studies. Mendelian randomization (MR) approach provides unconfounded estimates of causal effects and overcomes the limitations of observational studies. We performed a bi-directional MR analysis to clarify whether there existed a causal effect of insomnia on tuberculosis, or tuberculosis on insomnia. In forward-direction MR, we chose genome-wide significant (P < .5 × 10-8) and independent (r2 < 0.001) single-nucleotide polymorphisms (SNPs) as instrumental variants (IVs), then extracted effect estimates of these IVs in tuberculosis genome-wide association study (GWAS) dataset to explore causal effect of genetically proxied insomnia on tuberculosis using inverse variance-weighted (IVW), MR-Egger, and weighted median methods. Additionally, we examined robustness and pleiotropy of effect estimates by heterogeneity and sensitivity analysis. Similarly, we investigated causal effect of genetically proxied tuberculosis on insomnia in reverse-direction MR. We revealed no causal relationship between genetically proxied insomnia and tuberculosis using 15 SNPs in forward-direction MR (IVW OR 5.305 [0.100-281.341], P = .410) and reverse-direction MR analysis (ORs and P values were not applicable due to no eligible SNPs in GWAS), with insignificant heterogeneity (Q = 22.6, I2 < 0.001, P = .066) and pleiotropy (intercept = 0.032, SE = 0.057, P = .592) in effect estimates. Our bi-directional MR analysis affirms no causal effect of insomnia on tuberculosis, or tuberculosis on insomnia.

Female obesity and infertility: outcomes and regulatory guidance

Obesity has been associated with reduced fertility, although the dynamics and mechanisms which link excess weight to reduced fertility are not yet fully clarified. Obese women, especially those with central obesity, are less likely to conceive per cycle. Obese women suffer from perturbations of the hypothalamus-pituitary-ovary axis, disturbances of the menstrual cycle and are up to three times more likely to suffer from oligo/anovulation. A delicate hormonal balance regulates follicular development and the maturation of oocytes and it has been observed that obesity can alter the hormonal environment: adipocytes, in fact, are responsible for the production of a hormone called leptin (present in high quantities in obese women) which has been associated with reduced fecundity. In addition to compromising ovulation, obesity negatively affects the development and implantation of the endometrium. The expression of polycystic ovary syndrome (PCOS) is regulated, in part, by weight, so obese women with PCOS often have a more severe phenotype and higher subfertility rates. Furthermore, obesity impairs women's response to medically assisted procreation (MAP) treatments. The authors have set out to delineate a broad-ranging overview of obesity's impact on female fertility, by drawing upon sources spanning the 1994-2022 period. Assisted reproductive technology (ART) procedures are also discussed as they relate to obese patients. In addition the dynamics by which maternal obesity reportedly affects fetal, neonatal and child development have also been briefly enunciated.