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.

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.

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.

Personalized approaches to prevention based on genetic risk models have been anticipated, and many models for the prediction of individual breast cancer risk have been developed. However, few studies have evaluated personalized risk using both genetic and environmental factors. We developed a risk model using genetic and environmental risk factors using 1319 breast cancer cases and 2094 controls from three case-control studies in Japan. Risk groups were defined based on the number of risk alleles for 14 breast cancer susceptibility loci, namely low (0-10 alleles), moderate (11-16) and high (17+). Environmental risk factors were collected using a self-administered questionnaire and implemented with harmonization. Odds ratio (OR) and C-statistics, calculated using a logistic regression model, were used to evaluate breast cancer susceptibility and model performance. Respective breast cancer ORs in the moderate- and high-risk groups were 1.69 (95% confidence interval, 1.39-2.04) and 3.27 (2.46-4.34) compared with the low-risk group. The C-statistic for the environmental model of 0.616 (0.596-0.636) was significantly improved by combination with the genetic model, to 0.659 (0.640-0.678). This combined genetic and environmental risk model may be suitable for the stratification of individuals by breast cancer risk. New approaches to breast cancer prevention using the model are warranted.

The 2nd International DKFZ Conference on Cancer Prevention (CCP2020) organized by the German Cancer Research Center (DKFZ) was held as a virtual event on 17-18 September 2020. The event gathered experts on cancer prevention from around the world with the aim of generating a stimulating interchange of opinions between clinicians and basic researchers working in the field. The talks and posters of the conference fueled exciting discussions and debates about the state of the art of cancer prevention and provided a comprehensive outlook on the many aspects of the field. The program was divided into three main sessions, illustrating the most recent methodological approaches and interventions in primary, secondary and tertiary prevention, enriched by introductory lectures depicting the most relevant aspects of each session. The key concepts covered in this meeting were risk factors, early detection, improving life after cancer, cancer prevention in Europe and personalized prevention. The importance of the latter was expressly highlighted, many presentations emphasizing that in the era of personalized medicine, prevention also needs to be based on the unique genetic, epigenetic, social and behavioral characteristics of the individual to achieve maximal efficacy. In this article, we summarize the key messages emerging from each section, with particular attention on the most important challenges yet to be met in the field of cancer prevention.