UNASSIGNED: Cardiovascular diseases (CVDs) pose a significant global health challenge, necessitating innovative approaches for primary prevention. Personalized prevention, based on genetic risk scores (PRS) and digital technologies, holds promise in revolutionizing CVD preventive strategies. However, the clinical efficacy of these interventions requires further investigation. This study presents the protocol of the INNOPREV randomized controlled trial, aiming to evaluate the clinical efficacy of PRS and digital technologies in personalized cardiovascular disease prevention.
UNASSIGNED: The INNOPREV trial is a four-arm RCT conducted in Italy. A total of 1,020 participants, aged 40-69 with high 10-year CVD risk based on SCORE 2 charts, will be randomly assigned to traditional CVD risk assessment, genetic testing (CVD PRS), digital intervention (app and smart band), or a combination of genetic testing and digital intervention. The primary objective is to evaluate the efficacy of providing CVD PRS information, measured at baseline, either alone or in combination with the use of an app and a smart band, on two endpoints: changes in lifestyle patterns, and modification in CVD risk profiles. Participants will undergo a comprehensive assessment and cardiovascular evaluation at baseline, with follow-up visits at one, five, and 12 months. Lifestyle changes and CVD risk profiles will be assessed at different time points beyond the initial assessment, using the Life\'s Essential 8 and SCORE 2, respectively. Blood samples will be collected at baseline and at study completion to evaluate changes in lipid profiles. The analysis will employ adjusted mixed-effect models for repeated measures to assess significant differences in the data collected over time. Additionally, potential moderators and mediators will be examined to understand the underlying mechanisms of behavior change.
UNASSIGNED: As the largest trial in this context, the INNOPREV trial will contribute to the advancement of personalized cardiovascular disease prevention, with the potential to positively impact public health and reduce the burden of CVDs on healthcare systems. By systematically examining the clinical efficacy of PRS and digital interventions, this trial aims to provide valuable evidence to guide future preventive strategies and enhance population health outcomes.

UNASSIGNED: We introduce the Bitemporal Lens Model, a comprehensive methodology for chronic disease prevention using digital biomarkers.
UNASSIGNED: The Bitemporal Lens Model integrates the change-point model, focusing on critical disease-specific parameters, and the recurrent-pattern model, emphasizing lifestyle and behavioral patterns, for early risk identification.
UNASSIGNED: By incorporating both the change-point and recurrent-pattern models, the Bitemporal Lens Model offers a comprehensive approach to preventive healthcare, enabling a more nuanced understanding of individual health trajectories, demonstrated through its application in cardiovascular disease prevention.
UNASSIGNED: We explore the benefits of the Bitemporal Lens Model, highlighting its capacity for personalized risk assessment through the integration of two distinct lenses. We also acknowledge challenges associated with handling intricate data across dual temporal dimensions, maintaining data integrity, and addressing ethical concerns pertaining to privacy and data protection.
UNASSIGNED: The Bitemporal Lens Model presents a novel approach to enhancing preventive healthcare effectiveness.

UNASSIGNED: Breast cancer (BC) screening with mammography reduces mortality but considers currently only age as a risk factor. Personalized risk-based screening has been proposed as a more efficient alternative. For that, risk prediction tools are necessary. Genome-wide association studies have identified numerous genetic variants (single-nucleotide polymorphisms [SNPs]) associated with BC. The effects of SNPs are combined into a polygenic risk score (PRS) as a risk prediction tool.
UNASSIGNED: We aimed to develop a clinical-grade PRS test suitable for BC risk-stratified screening with clinical recommendations and implementation in clinical practice.
UNASSIGNED: In the first phase of our study, we gathered previously published PRS models for predicting BC risk from the literature and validated them using the Estonian Biobank and UK Biobank data sets. We selected the best performing model based on prevalent data and independently validated it in both incident data sets. We then conducted absolute risk simulations, developed risk-based recommendations, and implemented the PRS test in clinical practice. In the second phase, we carried out a retrospective analysis of the PRS test\'s performance results in clinical practice.
UNASSIGNED: The best performing PRS included 2803 SNPs. The C-index of the Cox regression model associating BC status with PRS was 0.656 (SE = 0.05) with a hazard ratio of 1.66. The PRS can stratify individuals with more than a 3-fold risk increase. A total of 2637 BC PRS tests have been performed for women between the ages 30 and 83. Results in clinical use overlap well with expected PRS performance with 5.7% of women with more than 2-fold and 1.4% with more than 3-fold higher risk than the population average.
UNASSIGNED: The PRS test separates different BC risk levels and is feasible to implement in clinical practice.

Oxidative stress and tissue damage (OSD) play a pivotal role as an early-stage process in chronic disease pathogenesis. However, there has been little research to better understand the temporal (χρόνος[chronos]) dimensions of OSD process associated with environmental (non-genetic, including behaviors/lifestyle) and/or occupational stressors, like night shift work. OSD processes have recently attracted attention in relation to time-resolved external stressor trajectories in personalized medicine (prevention) initiatives, as they seem to interact with circadian clock systems towards the improved delineation of the early stages of (chronic) disease process.
This work critically reviewed human studies targeting the temporal dynamics of OSD and circadian clock system\'s activity in response to environmental/occupational stressors; the case of night shift work was examined.
Being a key stressor influencing OSD processes and circadian rhythm, night shift work was evaluated as part of a scoping review of research in OSD, including inflammatory and metabolic processes to determine the extent of OSD research undertaken in human populations, methodologies, tools and biomarkers used and the extent that the temporal dimensions of exposure and biological effect(s) were accounted for. Online databases were searched for papers published from 2000 onwards, resulting in the selection of 53 original publications.
The majority of studies (n = 41) took place in occupational settings, while the rest were conducted in the general population or patient groups. Most occupational studies targeted outcomes of oxidative stress/damage (n = 19), followed by the combination of OSD with inflammatory response (n = 10), and studies focused on metabolic outcomes (n = 12). Only a minor fraction of the studies measured biomarkers related to circadian rhythm, such as, melatonin, its metabolite, or cortisol. Night shift work was associated with select biomarkers of OSD and inflammation, albeit with mixed results. Although much progress in delineating the biological mechanisms of OSD process has been made, an equally thorough investigation on the temporal trajectory of OSD processes as triggered by environmental/occupational stressors in human studies has yet to fully evolve.

BACKGROUND: While a population-wide strategy involving lifestyle changes and a high-risk strategy involving pharmacological interventions have been described, the recently proposed personalized medicine approach combining both strategies for the prevention of hypertension has increasingly gained attention. However, a cost-effectiveness analysis has been hardly addressed. This study was set out to build a Markov analytical decision model with a variety of prevention strategies in order to conduct an economic analysis for tailored preventative methods.
METHODS: The Markov decision model was used to perform an economic analysis of four preventative strategies: usual care, a population-based universal approach, a population-based high-risk approach, and a personalized strategy. In all decisions, the cohort in each prevention method was tracked throughout time to clarify the four-state model-based natural history of hypertension. Utilizing the Monte Carlo simulation, a probabilistic cost-effectiveness analysis was carried out. The incremental cost-effectiveness ratio was calculated to estimate the additional cost to save an additional life year.
RESULTS: The incremental cost-effectiveness ratios (ICER) for the personalized preventive strategy versus those for standard care were -USD 3317 per QALY gained, whereas they were, respectively, USD 120,781 and USD 53,223 per Quality-Adjusted Life Year (QALY) gained for the population-wide universal approach and the population-based high-risk approach. When the ceiling ratio of willingness to pay was USD 300,000, the probability of being cost-effective reached 74% for the universal approach and was almost certain for the personalized preventive strategy. The equivalent analysis for the personalized strategy against a general plan showed that the former was still cost-effective.
CONCLUSIONS: To support a health economic decision model for the financial evaluation of hypertension preventative measures, a personalized four-state natural history of hypertension model was created. The personalized preventive treatment appeared more cost-effective than population-based conventional care. These findings are extremely valuable for making hypertension-based health decisions based on precise preventive medication.

This paper summarizes many findings about depression among children and adolescents. Depression is prevalent, highly distressing, and exerts considerable burden worldwide. Rates surge from childhood through young adulthood and have increased over the last decade. Many risk factors have been identified, and evidence-based interventions exist targeting mostly individual-level changes via psychological or pharmacological means. At the same time, the field appears stuck and has not achieved considerable progress in advancing scientific understanding of depression\'s features or delivering interventions to meet the challenge of youth depression\'s high and growing prevalence. This paper adopts several positions to address these challenges and move the field forward. First, we emphasize reinvigoration of construct validation approaches that may better characterize youth depression\'s phenomenological features and inform more valid and reliable assessments that can enhance scientific understanding and improve interventions for youth depression. To this end, history and philosophical principles affecting depression\'s conceptualization and measurement are considered. Second, we suggest expanding the range and targets of treatments and prevention efforts beyond current practice guidelines for evidence-based interventions. This broader suite of interventions includes structural- and system-level change focused at community and societal levels (e.g., evidence-based economic anti-poverty interventions) and personalized interventions with sufficient evidence base. We propose that by focusing on the FORCE (Fundamentals, Openness, Relationships, Constructs, Evidence), youth depression research can provide new hope.

Effective risk prediction models are lacking for personalized endoscopic screening of gastric cancer (GC). We aimed to develop, validate, and evaluate a questionnaire-based GC risk assessment tool for risk prediction and stratification in the Chinese population.
In this three-stage multicenter study, we first selected eligible variables by Cox regression models and constructed a GC risk score (GCRS) based on regression coefficients in 416,343 subjects (aged 40-75 years) from the China Kadoorie Biobank (CKB, development cohort). In the same age range, we validated the GCRS effectiveness in 13,982 subjects from another independent Changzhou cohort (validation cohort) as well as in 5348 subjects from an endoscopy screening program in Yangzhou. Finally, we categorized participants into low (bottom 20%), intermediate (20-80%), and high risk (top 20%) groups by the GCRS distribution in the development cohort.
The GCRS using 11 questionnaire-based variables demonstrated a Harrell\'s C-index of 0.754 (95% CI, 0.745-0.762) and 0.736 (95% CI, 0.710-0.761) in the two cohorts, respectively. In the validation cohort, the 10-year risk was 0.34%, 1.05%, and 4.32% for individuals with a low (≤ 13.6), intermediate (13.7~30.6), and high (≥ 30.7) GCRS, respectively. In the endoscopic screening program, the detection rate of GC varied from 0.00% in low-GCRS individuals, 0.27% with intermediate GCRS, to 2.59% with high GCRS. A proportion of 81.6% of all GC cases was identified from the high-GCRS group, which represented 28.9% of all the screened participants.
The GCRS can be an effective risk assessment tool for tailored endoscopic screening of GC in China. Risk Evaluation for Stomach Cancer by Yourself (RESCUE), an online tool was developed to aid the use of GCRS.

Effective preventive strategies are urgently needed to address the rising burden of non-communicable diseases such as cardiovascular disease and cancer. To date, most prevention efforts to reduce disease incidence have primarily targeted populations using \"one size fits all\" public health recommendations and strategies. However, the risk for complex heterogeneous diseases is based on a multitude of clinical, genetic, and environmental factors, which translate into individual sets of component causes for every person. Recent advances in genetics and multi-omics enable the use of new technologies to stratify disease risks at an individual level fostering personalized prevention. In this article, we review the main components of personalized prevention, provide examples, and discuss both emerging opportunities and remaining challenges for its implementation. We encourage physicians, health policy makers, and public health professionals to consider and apply the key elements and examples of personalized prevention laid out in this article while overcoming challenges and potential barriers to their implementation.

The application of innovative technologies, and in particular of wearable devices, can potentially transform the field of antenatal care with the aim of improving maternal and new-born health through a personalized approach. The present study undertakes a scoping review to systematically map the literature about the use wearable sensors in the research of foetal and pregnancy outcomes. Online databases were used to identify papers published between 2000-2022, from which we selected 30 studies: 9 on foetal outcomes and 21 on maternal outcomes. Included studies focused primarily on the use of wearable devices for monitoring foetal vital signs (e.g., foetal heart rate and movements) and maternal activity during pregnancy (e.g., sleep patterns and physical activity levels). There were many studies that focused on development and/or validation of wearable devices, even if often they included a limited number of pregnant women without pregnancy complications. Although their findings support the potential adoption of wearable devices for both antenatal care and research, there is still insufficient evidence to design effective interventions. Therefore, high quality research is needed to determine which and how wearable devices could support antenatal care.

UNASSIGNED: The aim of this study was to evaluate the effect of the intervention by proactively sharing a patient\'s high polygenic risk score (PRS) for coronary artery disease (CAD). Outcomes included: (i) reduction in cardiovascular disease (CVD) risk factors over 12 months; (ii) difference in purchased prescriptions of lipid-lowering and anti-hypertensive drugs between intervention group and control group subjects; and (iii) opinion of the participating physicians and subjects on PRS usefulness.
UNASSIGNED: This randomized controlled trial was conducted among middle-aged subjects with a top 20% CAD PRS in a family medicine setting. Participants were selected from 26 953 Estonian Biobank cohort participants. Subjects were informed and counselled about their PRS score and CAD risk using the visual tool at baseline (Visit I), counselling session (Visit II), and on the final Visit III at 12 months. The primary endpoint was not significantly different. However, the intervention group participants had a significantly higher probability of initiating statin treatment compared with the controls. Their levels of LDL-cholesterol (LDL-C) were significantly decreased compared with baseline on Visit III and significantly lower than in the control group. The vast majority of participating family physicians believe that finding out about genetic risks will affect the subject\'s lifestyle and medication compliance.
UNASSIGNED: Most of our outcome measures were in favour of this intervention. Participants achieved larger changes in cholesterol and blood pressure values. The vast majority (98.4%) of family physicians are interested in continuing to use genetic risk assessment in practice.