Surrogate disease markers as substitutes for chronic disease outcomes in studies of diet and chronic disease relations

Change analysis for intermediate disease markers in nutritional epidemiology: a causal inference perspective

BACKGROUND

Several approaches are commonly used to estimate the effect of diet on changes of various intermediate disease markers in prospective studies, including "change-score analysis", "concurrent change-change analysis" and "lagged change-change analysis". Although empirical evidence suggests that concurrent change-change analysis is most robust, consistent, and biologically plausible, in-depth dissection and comparison of these approaches from a causal inference perspective is lacking. We intend to explicitly elucidate and compare the underlying causal model, causal estimand and interpretation of these approaches, intuitively illustrate it with directed acyclic graph (DAG), and further clarify strengths and limitations of the recommended concurrent change-change analysis through simulations.

METHODS

Causal model and DAG are deployed to clarify the causal estimand and interpretation of each approach theoretically. Monte Carlo simulation is used to explore the performance of distinct approaches under different extents of time-invariant heterogeneity and the performance of concurrent change-change analysis when its causal identification assumptions are violated.

RESULTS

Concurrent change-change analysis targets the contemporaneous effect of exposure on outcome (measured at the same survey wave), which is more relevant and plausible in studying the associations of diet and intermediate biomarkers in prospective studies, while change-score analysis and lagged change-change analysis target the effect of exposure on outcome after one-period timespan (typically several years). Concurrent change-change analysis always yields unbiased estimates even with severe unobserved time-invariant confounding, while the other two approaches are always biased even without time-invariant heterogeneity. However, concurrent change-change analysis produces almost linearly increasing estimation bias with violation of its causal identification assumptions becoming more serious.

CONCLUSIONS

Concurrent change-change analysis might be the most superior method in studying the diet and intermediate biomarkers in prospective studies, which targets the most plausible estimand and circumvents the bias from unobserved individual heterogeneity. Importantly, careful examination of the vital identification assumptions behind it should be underscored before applying this promising method.

Nutrition Interventions for Lowering Cardiovascular Risk After Hypertensive Disorders of Pregnancy: A Systematic Review

Background

Hypertension is one of the most common medical problems during pregnancy. Hypertensive disorders of pregnancy (HDP) increase the risk of premature cardiovascular disease (CVD) 2- to 4-fold within 10 years after delivery. Early health behaviour modifications may prevent or manage several cardiovascular risk factors. Importantly, compared with women without HDP, fewer women with HDP achieve national dietary guidelines to prevent CVD. This highlights an opportunity for programs tailored for women post-HDP to support their nutritional behaviours as a key component of postpartum CVD preventive care. This systematic review investigated the impacts of nutrition modifications on lowering measures of CVD risk after HDP.

Methods

Four electronic databases (MEDLINE, EMBASE, CINAHL, Cochrane Library) were searched in October 2022 with a search strategy focused on nutrition programs/interventions and women post-HDP. Additional inclusion criteria were original research and reported outcome of CVD risk or cardiovascular risk factors.

Results

Six studies were included: 4 experimental trials and 2 prospective cohort studies. Of the nutrition interventions, 4 were embedded within comprehensive health behaviour intervention programs. Outcome measures varied, but all studies reported blood pressure. A narrative synthesis found that the range of changes in blood pressure varied from no change to clinically meaningful change.

Conclusions

This review found statistically nonsignificant yet clinically important improvements in measures of cardiovascular risk across a range of nutritional interventions in women after HDP. Further high-quality evidence is needed to inform the design and implementation of nutritional preventive cardiovascular care targeting this high CVD-risk population.

Precision Nutrition: The Hype Is Exceeding the Science and Evidentiary Standards Needed to Inform Public Health Recommendations for Prevention of Chronic Disease

As dietary guidance for populations shifts from preventing deficiency disorders to chronic disease risk reduction, the biology supporting such guidance becomes more complex due to the multifactorial risk profile of disease and inherent population heterogeneity in the diet-disease relationship. Diet is a primary driver of chronic disease risk, and population-based guidance should account for individual responses. Cascading effects on evidentiary standards for population-based guidance are not straightforward. Precision remains a consideration for dietary guidance to prevent deficiency through the identification of population subgroups with unique nutritional needs. Reducing chronic disease through diet requires greater precision in (a) establishing essential nutrient needs throughout the life cycle in both health and disease; (b) considering effects of nutrients and other food substances on metabolic, immunological, inflammatory, and other physiological responses supporting healthy aging; and (c) considering healthy eating behaviors. Herein we provide a template for guiding population-based eating recommendations for reducing chronic diseases in heterogenous populations.

Comparative efficacy and safety among high-intensity statins. Systematic Review and Meta-Analysis

Aim: To summarize the evidence in terms of efficacy and safety of head-to-head studies of high-intensity statins regardless of the underlying population. Materials & methods: A systematic review and meta-analysis was conducted to summarize the effect sizes in randomized controlled trials and cohort studies that compared high-intensity statins. Results: Based on 44 articles, similar effectiveness was observed across the statins in reducing LDL levels from baseline. All statins were observed to have similar adverse drug reactions (ADRs), although higher dosages were associated with more ADRs. Based on a pooled quantitative analysis of atorvastatin 80 mg versus rosuvastatin 40 mg, rosuvastatin was statistically more effective in reducing LDL. Conclusion: This review further confirms that high-intensity statins reduce LDL by ≥50%, favoring rosuvastatin over atorvastatin. Additional data are needed to confirm the clinical significance on cardiovascular outcomes using real-world studies.

Protocol for the development of SPIRIT and CONSORT extensions for randomised controlled trials with surrogate primary endpoints: SPIRIT-SURROGATE and CONSORT-SURROGATE

INTRODUCTION

Randomised controlled trials (RCTs) may use surrogate endpoints as substitutes and predictors of patient-relevant/participant-relevant final outcomes (eg, survival, health-related quality of life). Translation of effects measured on a surrogate endpoint into health benefits for patients/participants is dependent on the validity of the surrogate; hence, more accurate and transparent reporting on surrogate endpoints is needed to limit misleading interpretation of trial findings. However, there is currently no explicit guidance for the reporting of such trials. Therefore, we aim to develop extensions to the SPIRIT (Standard Protocol Items: Recommendations for Interventional Trials) and CONSORT (Consolidated Standards of Reporting Trials) reporting guidelines to improve the design and completeness of reporting of RCTs and their protocols using a surrogate endpoint as a primary outcome.

METHODS AND ANALYSIS

The project will have four phases: phase 1 (literature reviews) to identify candidate reporting items to be rated in a Delphi study; phase 2 (Delphi study) to rate the importance of items identified in phase 1 and receive suggestions for additional items; phase 3 (consensus meeting) to agree on final set of items for inclusion in the extensions and phase 4 (knowledge translation) to engage stakeholders and disseminate the project outputs through various strategies including peer-reviewed publications. Patient and public involvement will be embedded into all project phases.

ETHICS AND DISSEMINATION

The study has received ethical approval from the University of Glasgow College of Medical, Veterinary and Life Sciences Ethics Committee (project no: 200210051). The findings will be published in open-access peer-reviewed publications and presented in conferences, meetings and relevant forums.

Biomarkers of non-communicable chronic disease: an update on contemporary methods

Chronic diseases constitute a major global burden with significant impact on health systems, economies, and quality of life. Chronic diseases include a broad range of diseases that can be communicable or non-communicable. Chronic diseases are often associated with modifications of normal physiological levels of various analytes that are routinely measured in serum and other body fluids, as well as pathological findings, such as chronic inflammation, oxidative stress, and mitochondrial dysfunction. Identification of at-risk populations, early diagnosis, and prediction of prognosis play a major role in preventing or reducing the burden of chronic diseases. Biomarkers are tools that are used by health professionals to aid in the identification and management of chronic diseases. Biomarkers can be diagnostic, predictive, or prognostic. Several individual or grouped biomarkers have been used successfully in the diagnosis and prediction of certain chronic diseases, however, it is generally accepted that a more sophisticated approach to link and interpret various biomarkers involved in chronic disease is necessary to improve our current procedures. In order to ensure a comprehensive and unbiased coverage of the literature, first a primary frame of the manuscript (title, headings and subheadings) was drafted by the authors working on this paper. Second, based on the components drafted in the preliminary skeleton a comprehensive search of the literature was performed using the PubMed and Google Scholar search engines. Multiple keywords related to the topic were used. Out of screened papers, only 190 papers, which are the most relevant, and recent articles were selected to cover the topic in relation to etiological mechanisms of different chronic diseases, the most recently used biomarkers of chronic diseases and finally the advances in the applications of multivariate biomarkers of chronic diseases as statistical and clinically applied tool for the early diagnosis of chronic diseases was discussed. Recently, multivariate biomarkers analysis approach has been employed with promising prospect. A brief discussion of the multivariate approach for the early diagnosis of the most common chronic diseases was highlighted in this review. The use of diagnostic algorithms might show the way for novel criteria and enhanced diagnostic effectiveness inpatients with one or numerous non-communicable chronic diseases. The search for new relevant biomarkers for the better diagnosis of patients with non-communicable chronic diseases according to the risk of progression, sickness, and fatality is ongoing. It is important to determine whether the newly identified biomarkers are purely associations or real biomarkers of underlying pathophysiological processes. Use of multivariate analysis could be of great importance in this regard.

Bempedoic Acid: The New Kid on the Block for the Treatment of Dyslipidemia and LDL Cholesterol: A Narrative Review

Diabetes is a major risk factor for atherosclerotic cardiovascular disease (ASCVD) in which dyslipidaemia plays a crucial role. Statins are first line therapy for primary and secondary prevention of ASCVD; however, adverse events include reversible musculoskeletal and liver side effects in addition to a diabetogenic association. In this short review, we provide a succinct narrative of the future role and current trial data of a novel first-in-class molecule, bempedoic acid. The authors provide their expert insight with a focus on Phase III randomised controlled trials (RCT) of bempedoic acid. Bempedoic acid was approved by the US Food and Drug Administration (FDA) and the European Medicines Agency (EMA) in February and March 2020, respectively, and is a novel molecule which inhibits cholesterol biosynthesis in the same mechanistic pathway as statins. It is a first-in-class small molecule, delivered as a prodrug and administered as an oral, once-daily dose that decreases low-density lipoprotein cholesterol (LDL-C) levels. Phase II and III RCTs have demonstrated efficacy with adequate safety data as mono- or combination therapy with statins and ezetimibe. Bempedoic acid is hepatically converted to the active drug with a lack of activation in skeletal muscle. Due to this novel mechanism, musculoskeletal-related adverse events exhibit a lower prevalence providing an alternative pharmacotherapy in statin-intolerant patients. Bempedoic acid may be used as an adjunct to diet and maximally tolerated statin therapy or in statin-intolerant patients for the treatment of dyslipidaemia. The recent National Institute of Health and Care Excellence (NICE) (UK) technology appraisal guidance [TA694] published in April 2021 recommended bempedoic acid with ezetimibe as a treatment option for primary hypercholesterolaemia or mixed dyslipidaemia if statins are not tolerated or contraindicated and if there is inadequate control of LDL-C with ezetimibe alone. Additionally, outcomes trials evaluating 'hard' endpoints in statin-intolerant patients or those with ASCVD are currently underway.

Nutrition to Optimise Human Health-How to Obtain Physiological Substantiation?

Demonstrating in an unambiguous manner that a diet, let alone a single product, 'optimizes' health, presents an enormous challenge. The least complicated is when the starting situation is clearly suboptimal, like with nutritional deficiencies, malnutrition, unfavourable lifestyle, or due to disease or ageing. Here, desired improvements and intervention strategies may to some extent be clear. However, even then situations require approaches that take into account interactions between nutrients and other factors, complex dose-effect relationships etc. More challenging is to substantiate that a diet or a specific product optimizes health in the general population, which comes down to achieve perceived, 'non-medical' or future health benefits in predominantly healthy persons. Presumed underlying mechanisms involve effects of non-nutritional components with subtle and slowly occurring physiological effects that may be difficult to translate into measurable outcomes. Most promising strategies combine classical physiological concepts with those of 'multi-omics' and systems biology. Resilience-the ability to maintain or regain homeostasis in response to stressors-is often used as proxy for a particular health domain. Next to this, quantifying health requires personalized strategies, measurements preferably carried out remotely, real-time and in a normal living environment, and experimental designs other than randomized controlled trials (RCTs), for example N-of-1 trials.