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Uncertainty Quantification in Cost-effectiveness Analysis for Stochastic-based Infectious Disease Models: Insights from Surveillance on Lymphatic Filariasis.
Cost-effectiveness analyses (CEA) typically involve comparing effectiveness and costs of one or more interventions compared to standard of care, to determine which intervention should be optimally implemented to maximise population health within the constraints of the healthcare budget. Traditionally, cost-effectiveness evaluations are expressed using incremental cost-effectiveness ratios (ICERs), which are compared with a fixed willingness-to-pay (WTP) threshold. Due to the existing uncertainty in costs for interventions and the overall burden of disease, particularly with regard to diseases in populations that are difficult to study, it becomes important to consider uncertainty quantification whilst estimating ICERs. To tackle the challenges of uncertainty quantification in CEA, we propose an alternative paradigm utilizing the Linear Wasserstein framework combined with Linear Discriminant Analysis (LDA) using a demonstrative example of lymphatic filariasis (LF). This approach uses geometric embeddings of the overall costs for treatment and surveillance, disability-adjusted lifeyears (DALYs) averted for morbidity by quantifying the burden of disease due to the years lived with disability, and probabilities of local elimination over a time-horizon of 20 years to evaluate the cost-effectiveness of lowering the stopping thresholds for post-surveillance determination of LF elimination as a public health problem. Our findings suggest that reducing the stopping threshold from <1% to <0.5% microfilaria (mf) prevalence for adults aged 20 years and above, under various treatment coverages and baseline prevalences, is cost-effective. When validated on 20% of test data, for 65% treatment coverage, a government expenditure of WTP ranging from $500 to $3,000 per 1% increase in local elimination probability justifies the switch to the lower threshold as cost-effective. Stochastic model simulations often lead to parameter and structural uncertainty in CEA. Uncertainty may impact the decisions taken, and this study underscores the necessity of better uncertainty quantification techniques within CEA for making informed decisions.
Neuroticism, omega-3 fatty acids, and risk of incident dementia.
BACKGROUND: High levels of neuroticism are associated with an increased risk of dementia, yet the underlying biological mechanisms remain poorly understood. Investigating the role of metabolites, the downstream products of metabolic processes, may offer valuable insights into this association. METHODS: In 215,624 dementia-free UK Biobank participants aged 40-69 years, we assessed neuroticism's associations with 249 nuclear magnetic resonance-measured metabolites using linear regression. Metabolites reaching Bonferroni-corrected significance were further tested for associations with incident all-cause dementia, Alzheimer's disease (AD) and vascular dementia (VaD) using Cox proportional-hazards regression, and with white matter hyperintensities volume using linear regression. Causality in significant observational relationships was evaluated through two-sample Mendelian randomization. RESULTS: Neuroticism was significantly associated with 119 out of 249 metabolites (Bonferroni-adjusted p
Multi-ancestry genome-wide association analyses incorporating SNP-by-psychosocial interactions identify novel loci for serum lipids.
Serum lipid levels, which are influenced by both genetic and environmental factors, are key determinants of cardiometabolic health and are influenced by both genetic and environmental factors. Improving our understanding of their underlying biological mechanisms can have important public health and therapeutic implications. Although psychosocial factors, including depression, anxiety, and perceived social support, are associated with serum lipid levels, it is unknown if they modify the effect of genetic loci that influence lipids. We conducted a genome-wide gene-by-psychosocial factor interaction (G×Psy) study in up to 133,157 individuals to evaluate if G×Psy influences serum lipid levels. We conducted a two-stage meta-analysis of G×Psy using both a one-degree of freedom (1df) interaction test and a joint 2df test of the main and interaction effects. In Stage 1, we performed G×Psy analyses on up to 77,413 individuals and promising associations (P
GWAS meta-analysis of CSF Alzheimer's disease biomarkers 18,948 individuals reveal novel loci and genes regulating lipid metabolism, brain volume and autophagy.
Cerebrospinal fluid (CSF) amyloid beta (Aβ42), total tau (t-tau), and phosphorylated tau (p-tau181) are well accepted markers of Alzheimer's disease. We performed a GWAS meta-analysis including 18,948 individuals of European and 416 non-European ancestry. We identified 12 genome-wide significant loci across all three biomarkers, eight of them novel. We replicated the association of CSF biomarkers with APOE , CR1 , GMNC/CCDC50 and C16orf95/MAP1LC3B . Novel loci included BIN1 for Aβ42 and GNA12, MS4A6A, SLCO1A2 with both t-tau and p-tau181, as well as additional loci on chr. 8, near ANGPT1 and chr. 9 near SMARCA2 . We also demonstrated that these variants were not only associated with CSF level of the three biomarkers but also showed significant association with AD risk, disease progression and/or brain amyloidosis. The associated genes are implicated in lipid metabolism independent APOE , as well as autophagy and brain volume regulation driven by t-tau and p-tau181 dysregulation.
Associations Between Trust in Healthcare Professionals and Perceptions of Modifiability of Dementia and Stroke Risks Through Maintaining or Changing Lifestyle Habits
Purpose: To investigate the trust levels in health information sources from a United States (U.S.) sample, and to examine the relationships between trust in healthcare professionals (HCPs) and perceptions of modifiability of dementia and stroke risks through maintaining or changing lifestyle habits. Design: Cross-sectional. Setting: A survey distributed via the vendor platform Prolific to a sample of the U.S. population. Participants: Data included on U.S. adults (n = 1478) in 2023. Measures: Outcome variables were perceiving that dementia and stroke risk can be modified through maintaining or changing lifestyle habits. Independent variables were trust levels in HCPs. Analysis: Descriptive analysis was performed to assess levels of trust in information sources. Subsequently, we performed multivariable regression analyses between trust in HCPs and perceptions of risk modifiability in dementia and stroke. A hierarchal cluster analysis was conducted to characterize trust patterns in this cohort. Results: Participants with high trust in HCPs compared to those with low trust in HCPs were more likely to perceive that maintaining (adjusted odds ratio [aOR] = 1.57, 95% confidence interval [CI]:1.15-2.12) and changing lifestyle habits (aOR = 1.72, 95% CI: 1.26-2.33) could reduce risk of dementia. Similar associations were found for perceptions of stroke risk reduction through maintaining (aOR = 1.49, 95% CI: 1.07-2.04) and changing (aOR = 2.68, 95% CI: 1.72-4.12) lifestyle habits. Cluster analyses identified three trust patterns amongst the participants: (i) a generally trusting cluster, (ii) a trusting of “official” health sources only cluster, and (iii) a generally not trusting cluster. Conclusion: This study found statistically significant associations between trusting HCPs and the perceptions that maintaining or changing lifestyle habits can modify risks of dementia and stroke, highlighting the importance of trust when developing preventive strategies.
Convergent and divergent brain-cognition relationships during development revealed by cross-sectional and longitudinal analyses in the ABCD Study.
How brain networks and cognition co-evolve during development remains poorly understood. Using longitudinal data collected at baseline and Year 2 from 2,949 individuals (ages 8.9-13.5) in the Adolescent Brain Cognitive Development (ABCD) Study, we show that baseline resting-state functional connectivity (FC) more strongly predicts future cognitive ability than concurrent cognitive ability. Models trained on baseline FC to predict baseline cognition generalize better to Year 2 data, suggesting that brain-cognition relationships strengthen over time. Intriguingly, baseline FC outperforms longitudinal FC change in predicting future cognitive ability. Differences in measurement reliability do not fully explain this discrepancy: although FC change is less reliable (intraclass correlation, ICC = 0.24) than baseline FC (ICC = 0.56), matching baseline FC's reliability by shortening scan time only partially narrows the predictive gap. Furthermore, neither baseline FC nor FC change meaningfully predicts longitudinal change in cognitive ability. We also identify converging and diverging predictive network features across cross-sectional and longitudinal models of brain-cognition relationships, revealing a multivariate twist on Simpson's paradox. Together, these findings suggest that during early adolescence, stable individual differences in brain functional network organization exert a stronger influence on future cognitive outcomes than short-term changes.
Transferability of European-derived Alzheimer's disease polygenic risk scores across multiancestry populations.
A polygenic score (PGS) for Alzheimer's disease (AD) was derived recently from data on genome-wide significant loci in European ancestry populations. We applied this PGS to populations in 17 European countries and observed a consistent association with the AD risk, age at onset and cerebrospinal fluid levels of AD biomarkers, independently of apolipoprotein E locus (APOE). This PGS was also associated with the AD risk in many other populations of diverse ancestries. A cross-ancestry polygenic risk score improved the association with the AD risk in most of the multiancestry populations tested when the APOE region was included. Finally, we found that the PGS/polygenic risk score captured AD-specific information because the association weakened as the diagnosis was broadened. In conclusion, a simple PGS captures the AD-specific genetic information that is common to populations of different ancestries, although studies of more diverse populations are still needed to better characterize the genetics of AD.
Right Ventricular Strain Improves Cardiac MRI-based Prognostication in Heart Failure with Preserved Ejection Fraction.
Background Right ventricular (RV) function is an independent predictor of clinical status and prognosis in multiple cardiovascular diseases; however, the prognostic value of RV strain in patients with heart failure with preserved ejection fraction (HFpEF) remains largely unknown. Purpose To determine the associations between RV strain variables derived from cardiac MRI feature tracking and adverse outcomes in patients with HFpEF. Materials and Methods This retrospective study included patients with HFpEF who underwent cardiac MRI from January 2010 to December 2018. The primary end point was all-cause mortality. The results were validated in a cohort of patients with HFpEF enrolled from January 2019 to June 2021. Cox regression analysis was performed to assess the associations between variables and clinical outcomes. Results The development cohort comprised 1019 patients (mean age, 56.9 years ± 12.3 [SD]; 710 men), and the validation cohort comprised 273 patients (mean age, 55.3 years ± 14.0; 191 men). During a median follow-up of 7.8 and 3.9 years, respectively, 103 patients in the development cohort and nine in the validation cohort died. Multivariable Cox regression analysis showed that RV global longitudinal and circumferential strain were independent predictors of all-cause mortality (adjusted hazard ratio per 1% increase, 1.07 [95% CI: 1.02, 1.12; P = .005] and 1.13 [95% CI: 1.05, 1.21; P < .001], respectively). The full model based on clinical, conventional imaging, and RV strain variables demonstrated the best discrimination performance in the development (C index = 0.794) and validation (C index = 0.782) cohorts. In a subgroup with T1 mapping data, RV global longitudinal and circumferential strain remained independent predictors after separate adjustment for native T1 value and extracellular volume fraction (all models, P < .05). Conclusion RV global longitudinal and circumferential strain derived from cardiac MRI were independent predictors of adverse outcomes in patients with HFpEF, providing greater prognostic value than traditional clinical and imaging-derived risk markers. © RSNA, 2025 Supplemental material is available for this article. See also the editorial by Murphy and Quinn in this issue.
Is it time to revisit the scoring of Slow Wave (N3) Sleep?
The use of a fixed electroencephalogram (EEG) amplitude threshold of 75 µV for labelling slow waves is a subject of ongoing discussion given EEG amplitude is known to vary with age and sex. This paper investigates the impact of this amplitude threshold on age- and sex-related trends in visually-annotated SWS. Automated methods for labelling SWS using data-driven thresholds and amplitude- or frequency-based inputs are developed. Age- and sex-related trends in SWS derived from visual annotation and automated labelling are then compared across a cohort of 2,913 participants from the Sleep Heart Health Study. In the selected cohort, males exhibit an age-related decrease in visually-annotated SWS, which is preserved when using automated labelling. In contrast, females exhibit a mild age-related increase in visually-annotated and amplitude-labelled SWS, but an age-related decrease in frequency-labelled SWS. Further, using frequency-labelled SWS results in a reduction in SWS in females to a level comparable to that of males. Overall, the consistency of age-related trends in SWS in males between visual annotation and automated labelling, as well as the lack of consistency in these trends in females, is striking. Given that the 75 µV amplitude threshold was established using data acquired primarily from young males, these results suggest that observed sex-based differences in visually-annotated SWS may be artefactual rather than physiological, and a result of the 75 µV amplitude criterion. This sex-related disparity highlights the need for the AASM guidelines for scoring SWS to be reviewed and updated to provide equivalent performance for males and females.
Continuous Indexing of Fibrosis (CIF): improving the assessment and classification of MPN patients.
The grading of fibrosis in myeloproliferative neoplasms (MPN) is an important component of disease classification, prognostication and monitoring. However, current fibrosis grading systems are only semi-quantitative and fail to fully capture sample heterogeneity. To improve the quantitation of reticulin fibrosis, we developed a machine learning approach using bone marrow trephine (BMT) samples (n = 107) from patients diagnosed with MPN or a reactive marrow. The resulting Continuous Indexing of Fibrosis (CIF) enhances the detection and monitoring of fibrosis within BMTs, and aids MPN subtyping. When combined with megakaryocyte feature analysis, CIF discriminates between the frequently challenging differential diagnosis of essential thrombocythemia (ET) and pre-fibrotic myelofibrosis with high predictive accuracy [area under the curve = 0.94]. CIF also shows promise in the identification of MPN patients at risk of disease progression; analysis of samples from 35 patients diagnosed with ET and enrolled in the Primary Thrombocythemia-1 trial identified features predictive of post-ET myelofibrosis (area under the curve = 0.77). In addition to these clinical applications, automated analysis of fibrosis has clear potential to further refine disease classification boundaries and inform future studies of the micro-environmental factors driving disease initiation and progression in MPN and other stem cell disorders.
Vascular and inflammatory biomarkers of cardiovascular events in non-steroidal anti-inflammatory drug users.
AimsThe Standard care vs. Celecoxib Outcome Trial (SCOT) found similar risk of cardiovascular events with traditional non-steroidal anti-inflammatory drugs (NSAIDs) and the cyclooxygenase-2-selective drug celecoxib. While pre-clinical work has suggested roles for vascular and renal dysfunction in NSAID cardiovascular toxicity, our understanding of these mechanisms remains incomplete. A post hoc analysis of the SCOT cohort was performed to identify clinical risk factors and circulating biomarkers of cardiovascular events in NSAID users.Methods and resultsWithin SCOT (7295 NSAID users with osteoarthritis or rheumatoid arthritis), clinical risk factors associated with cardiovascular events were identified using least absolute shrinkage and selection operator regression. A nested case-control study of serum biomarkers including targeted proteomics was performed in individuals who experienced a cardiovascular event within 1 year (n = 49), matched 2:1 with controls who did not (n = 97). Risk factors significantly associated with cardiovascular events included increasing age, male sex, smoking, total cholesterol:HDL ratio ≥5, and aspirin use. Statin use was cardioprotective [odds ratio (OR) 0.68; 95% confidence interval (CI) 0.46-0.98]. There was significantly higher immunoglobulin (Ig)G anti-malondialdehyde-modified LDL (MDA-LDL), asymmetric dimethylarginine (ADMA), and lower arginine/ADMA. Targeted proteomic analysis identified serum growth differentiation factor 15 (GDF-15) as a candidate biomarker [area under the curve of 0.715 (95% CI 0.63-0.81)].ConclusionGrowth differentiation factor 15 has been identified as a candidate biomarker and should be explored for its mechanistic contribution to NSAID cardiovascular toxicity, particularly given the remarkable providence that GDF-15 was originally described as NSAID-activated gene-1.