Absolute lung cancer risk increases among individuals with >15 quit-years: Analyses to inform the update of the American Cancer Society lung cancer screening guidelines.

BACKGROUND: This report quantifies counteracting effects of quit-years and concomitant aging on lung cancer risk, especially on exceeding 15 quit-years, when the US Preventive Services Task Force (USPSTF) recommends curtailing lung-cancer screening. METHODS: Cox models were fitted to estimate absolute lung cancer risk among Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial (PLCO) and National Lung Screening Trial (NLST) participants who ever smoked. Absolute lung cancer risk and gainable years of life from screening for individuals aged 50 to 80 in the US-representative National Health Interview Survey (NHIS) 2015-2018 who ever smoked were projected. Relaxing USPSTF recommendations to 20/25/30 quit-years versus augmenting USPSTF criteria with individuals whose estimated gain in life expectancy from screening exceeded 16.2 days according to the Life Years From Screening-CT (LYFS-CT) prediction model was compared. RESULTS: Absolute lung cancer risk increased by 8.7%/year (95% CI, 7.7%-9.7%; p < .001) as individuals aged beyond 15 quit-years in the PLCO, with similar results in NHIS and NLST. For example, mean 5-year lung cancer risk for those aged 65 years with 15 quit-years = 1.47% (95% CI, 1.35%-1.59%) versus 1.76% (95% CI, 1.62%-1.90%) for those aged 70 years with 20 quit-years in the PLCO. Removing the quit-year criterion would make 4.9 million more people eligible and increase the proportion of preventable lung cancer deaths prevented (sensitivity) from 63.7% to 74.2%. Alternatively, augmentation using LYFS-CT would make 1.7 million more people eligible while increasing the lung cancer death sensitivity to 74.0%. CONCLUSIONS: Because of aging, absolute lung cancer risk increases beyond 15 quit-years, which does not support exemption from screening or curtailing screening once it has been initiated. Compared with relaxing the USPSTF quit-year criterion, augmentation using LYFS-CT could prevent most of the deaths at substantially superior efficiency, while also preventing deaths among individuals who currently smoke with low intensity or long duration.

Noninvasive Risk Prediction Models for Heart Failure Using Proportional Jaccard Indices and Comorbidity Patterns.

Background: In the post-coronavirus disease 2019 (COVID-19) era, remote diagnosis and precision preventive medicine have emerged as pivotal clinical medicine applications. This study aims to develop a digital health-monitoring tool that utilizes electronic medical records (EMRs) as the foundation for performing a non-random correlation analysis among different comorbidity patterns for heart failure (HF). Methods: Novel similarity indices, including proportional Jaccard index (PJI), multiplication of the odds ratio proportional Jaccard index (OPJI), and alpha proportional Jaccard index (APJI), provide a fundamental framework for constructing machine learning models to predict the risk conditions associated with HF. Results: Our models were constructed for different age groups and sexes and yielded accurate predictions of high-risk HF across demographics. The results indicated that the optimal prediction model achieved a notable accuracy of 82.1% and an area under the curve (AUC) of 0.878. Conclusions: Our noninvasive HF risk prediction system is based on historical EMRs and provides a practical approach. The proposed indices provided simple and straightforward comparative indicators of comorbidity pattern matching within individual EMRs. All source codes developed for our noninvasive prediction models can be retrieved from GitHub.

Statistical methods for Mendelian models with multiple genes and cancers.

Risk evaluation to identify individuals who are at greater risk of cancer as a result of heritable pathogenic variants is a valuable component of individualized clinical management. Using principles of Mendelian genetics, Bayesian probability theory, and variant-specific knowledge, Mendelian models derive the probability of carrying a pathogenic variant and developing cancer in the future, based on family history. Existing Mendelian models are widely employed, but are generally limited to specific genes and syndromes. However, the upsurge of multigene panel germline testing has spurred the discovery of many new gene-cancer associations that are not presently accounted for in these models. We have developed PanelPRO, a flexible, efficient Mendelian risk prediction framework that can incorporate an arbitrary number of genes and cancers, overcoming the computational challenges that arise because of the increased model complexity. We implement an 11-gene, 11-cancer model, the largest Mendelian model created thus far, based on this framework. Using simulations and a clinical cohort with germline panel testing data, we evaluate model performance, validate the reverse-compatibility of our approach with existing Mendelian models, and illustrate its usage. Our implementation is freely available for research use in the PanelPRO R package.

Predictors of genetic risk recall among the participants of a randomized controlled precision prevention trial against melanoma.

PURPOSE: Inherited variation in MC1R imparts low to moderate risk of melanoma. Research on genetic risk recall, factors predicting recall, and whether recall influences adoption of preventive behaviors is limited. METHODS: Participants (n = 447) enrolled in a melanoma precision prevention trial were provided with MC1R risk information (average or higher) and after 6 and 12 months, were asked to recall their genetic risk. Predictors of recall were identified using backward stepwise selection. Intervention effects were reassessed after stratifying by recall. RESULTS: Participants at higher risk were 2 to 3 times more likely to misremember or not recall than participants with average risk. Misremembering was almost exclusively observed among participants at higher risk. Among the participants with average risk, lower health numeracy and not completing the telephone follow-up were associated with not recalling or misremembering. Among the participants at higher risk, lower education was associated with not recalling and lower perceived comparative chance of developing melanoma was associated with misremembering. In general, participants at higher risk who correctly recalled had modestly stronger intervention effects on sun protection behaviors than those who misremembered or did not recall. CONCLUSION: Future studies should examine different strategies to increase genetic risk recall, which may result in improved behavioral outcomes, especially among participants with lower education and health numeracy.

Predicting Adolescent Intervention Non-responsiveness for Precision HIV Prevention Using Machine Learning.

Interventions to teach protective behaviors may be differentially effective within an adolescent population. Identifying the characteristics of youth who are less likely to respond to an intervention can guide program modifications to improve its effectiveness. Using comprehensive longitudinal data on adolescent risk behaviors, perceptions, sensation-seeking, peer and family influence, and neighborhood risk factors from 2564 grade 10-12 students in The Bahamas, this study employs machine learning approaches (support vector machines, logistic regression, decision tree, and random forest) to identify important predictors of non-responsiveness for precision prevention. We used 80% of the data to train the models and the rest for model testing. Among different machine learning algorithms, the random forest model using longitudinal data and the Boruta feature selection approach predicted intervention non-responsiveness best, achieving sensitivity of 85.4%, specificity of 78.4% and AUROC of 0.93 on the training data, and sensitivity of 84.3%, specificity of 67.1%, and AUROC of 0.85 on the test data. Key predictors include self-efficacy, perceived response cost, parent monitoring, vulnerability, response efficacy, HIV/AIDS knowledge, communication about condom use, and severity of HIV/STI. Machine learning can yield powerful predictive models to identify adolescents who are unlikely to respond to an intervention. Such models can guide the development of alternative strategies that may be more effective with intervention non-responders.

Towards precision home visiting: results at six months postpartum from a randomized pilot implementation trial to assess the feasibility of a precision approach to Family Spirit.

BACKGROUND: Shared implementation challenges at scale in early childhood home visiting have led researchers to explore precision home visiting as a promising service delivery mechanism to better address families' unique needs and build greater program efficiencies. This randomized controlled pilot study aimed to assess the acceptability of a precision approach to one home visiting model, Family Spirit® and explore potential differences between Precision Family Spirit (PFS) and Standard Family Spirit (Standard FS) on participant-home visitor relationship and maternal outcomes. METHODS: Participants (N = 60) were at least 14 years old, pregnant or within 2 months postpartum, and enrolled in Family Spirit. Four sites in Michigan were randomized 1:1 to deliver PFS (up to 17 core lessons plus up to 13 additional lessons as needed) or Standard FS (home visiting services as usual). Primary (program acceptability, participant satisfaction, home visitor-participant relationship quality, retention, adherence) and secondary (knowledge, quality of life, difficulty with parenting problems, substance use, depression, stress) outcomes at 6 months postpartum are presented. PFS participants also self-reported on quality of life, difficulty with parenting problems, stress, substance use, and concerns with sexual and reproductive health and self and child's nutrition status at each home visit. This informed which lessons they should receive. RESULTS: Mothers in both groups reported positive program acceptability, satisfaction, and home visitor-participant relationships at 6 months postpartum. However, open-ended feedback from Standard FS participants indicates that some lesson content may not be applicable to all participants. At 6 months, retention was 82.3% for PFS and 66.7% for Standard FS, and adherence was 30.1% for PFS and 20.6% for Standard FS. CONCLUSIONS: Preliminary findings indicate that precision home visiting may be acceptable and feasible. A definitive trial is needed to build on this pilot data, assess outcomes for mothers and children participating in a precision approach to home visiting as compared to standard home visiting, and ready this approach for scale. TRIAL REGISTRATION: ClinicalTrials.gov NCT03975530 (first posted on 05/06/2019).

Risk Factor Profiles Differ for Cancers of Different Regions of the Colorectum.

BACKGROUND & AIMS: The molecular features of colorectal tumors differ with their anatomic location. Colorectal tumors are usually classified as proximal or distal. We collected data from 3 cohorts to identify demographic, clinical, anthropometric, lifestyle, and dietary risk factors for colorectal cancer (CRC) at 7 anatomic subsites. We examined whether the associations differ among refined subsites and whether there are trends in associations from cecum to rectum. METHODS: We collected data from the Nurses' Health Study, Nurses' Health Study 2, and Health Professionals Follow-up Study (45,351 men and 178,016 women, followed for a median 23 years) on 24 risk factors in relation to risk of cancer in cecum, ascending colon, transverse colon, descending colon, sigmoid colon, rectosigmoid junction, and rectum. Hazard ratios were estimated using Cox proportional hazards regression. We tested for linear and nonlinear trends in associations with CRC among subsites and within proximal colon, distal colon, and rectum. RESULTS: We documented 3058 cases of CRC (474 in cecum, 633 in ascending colon, 250 in transverse colon, 221 in descending colon, 750 in sigmoid colon, 202 in rectosigmoid junction, and 528 in rectum). The positive associations with cancer risk decreased, from cecum to rectum, for age and family history of CRC. In contrast, the inverse associations with cancer risk increased, from cecum to rectum, for endoscopic screening and intake of whole grains, cereal fiber, and processed red meat. There was a significant nonlinear trend in the association between CRC and female sex, with hazard ratios ranging from 1.73 for ascending colon cancer to 0.54 for sigmoid colon cancer. For proximal colon cancers, the association with alcohol consumption and smoking before age 30 years increased from the cecum to transverse colon. For distal colon cancers, the positive association with waist circumference in men was greater for descending vs sigmoid colon cancer. CONCLUSIONS: In an analysis of 3058 cases of CRC, we found that risk factor profiles differed for cancers along the colorectum. Proximal vs distal classifications are not sufficient to encompass the regional variations in colorectal tumor features and risk factors.

Technological readiness and implementation of genomic-driven precision medicine for complex diseases.

The fields of human genetics and genomics have generated considerable knowledge about the mechanistic basis of many diseases. Genomic approaches to diagnosis, prognostication, prevention and treatment - genomic-driven precision medicine (GDPM) - may help optimize medical practice. Here, we provide a comprehensive review of GDPM of complex diseases across major medical specialties. We focus on technological readiness: how rapidly a test can be implemented into health care. Although these areas of medicine are diverse, key similarities exist across almost all areas. Many medical areas have, within their standards of care, at least one GDPM test for a genetic variant of strong effect that aids the identification/diagnosis of a more homogeneous subset within a larger disease group or identifies a subset with different therapeutic requirements. However, for almost all complex diseases, the majority of patients do not carry established single-gene mutations with large effects. Thus, research is underway that seeks to determine the polygenic basis of many complex diseases. Nevertheless, most complex diseases are caused by the interplay of genetic, behavioural and environmental risk factors, which will likely necessitate models for prediction and diagnosis that incorporate genetic and non-genetic data.

Precision medicine in diabetes: a Consensus Report from the American Diabetes Association (ADA) and the European Association for the Study of Diabetes (EASD).

The convergence of advances in medical science, human biology, data science and technology has enabled the generation of new insights into the phenotype known as 'diabetes'. Increased knowledge of this condition has emerged from populations around the world, illuminating the differences in how diabetes presents, its variable prevalence and how best practice in treatment varies between populations. In parallel, focus has been placed on the development of tools for the application of precision medicine to numerous conditions. This Consensus Report presents the American Diabetes Association (ADA) Precision Medicine in Diabetes Initiative in partnership with the European Association for the Study of Diabetes (EASD), including its mission, the current state of the field and prospects for the future. Expert opinions are presented on areas of precision diagnostics and precision therapeutics (including prevention and treatment) and key barriers to and opportunities for implementation of precision diabetes medicine, with better care and outcomes around the globe, are highlighted. Cases where precision diagnosis is already feasible and effective (i.e. monogenic forms of diabetes) are presented, while the major hurdles to the global implementation of precision diagnosis of complex forms of diabetes are discussed. The situation is similar for precision therapeutics, in which the appropriate therapy will often change over time owing to the manner in which diabetes evolves within individual patients. This Consensus Report describes a foundation for precision diabetes medicine, while highlighting what remains to be done to realise its potential. This, combined with a subsequent, detailed evidence-based review (due 2022), will provide a roadmap for precision medicine in diabetes that helps improve the quality of life for all those with diabetes.

Deep Digital Phenotyping and Digital Twins for Precision Health: Time to Dig Deeper.

This viewpoint describes the urgent need for more large-scale, deep digital phenotyping to advance toward precision health. It describes why and how to combine real-world digital data with clinical data and omics features to identify someone's digital twin, and how to finally enter the era of patient-centered care and modify the way we view disease management and prevention.

Molecular Targets in Precision Chemoprevention of Colorectal Cancer: An Update from Pre-Clinical to Clinical Trials.

Colorectal cancer (CRC) is one of the leading causes of cancer deaths worldwide. The initiation and progression of CRC is a multi-step process that proceeds via precursor lesions to carcinoma, with each stage characterized by its distinct molecular and tissue microenvironment changes. Precursor lesions of CRC, aberrant crypt foci, and adenoma exhibit drastic changes in genetic, transcriptomic, and proteomic profiles compared to normal tissue. The identification of these changes is essential and provides further validation as an initiator or promoter of CRC and, more so, as lesion-specific druggable molecular targets for the precision chemoprevention of CRC. Mutated/dysregulated signaling (adenomatous polyposis coli, ß-catenin, epidermal growth factor receptor, V-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog (KRAS), tumor protein53, Akt, etc.), inflammatory (cyclooxygenase-2, microsomal prostaglandin E synthase-1, inducible nitric oxide synthase, and other pro-inflammatory mediators), and metabolic/growth factor (fatty acid synthase, ß-Hydroxy ß-methylglutaryl-CoA reductase, and ornithine decarboxylase) related targets are some of the well-characterized molecular targets in the precision chemoprevention of CRC. In this review, we discuss precursor-lesion specific targets of CRC and the current status of pre-clinical studies regarding clinical interventions and combinations for better efficacy and safety toward future precision clinical chemoprevention. In addition, we provide a brief discussion on the usefulness of secondary precision chemopreventive targets for tertiary precision chemoprevention to improve the disease-free and overall survival of advanced stage CRC patients.

Informing Precision Home Visiting: Identifying Meaningful Subgroups of Families Who Benefit Most from Family Spirit.

The Maternal, Infant, and Early Childhood Home Visiting Program was reauthorized February 8, 2018, and invests $2 billion over 5 years to improve mothers' and children's outcomes across the life course. Along with this investment, the home-visiting field is striving for implementation innovations to deliver the greatest impact to the most families at the most efficient cost through a focus on precision home visiting. Consistent with the precision home-visiting approach to identify meaningful subgroups to guide content tailoring, the purpose of this paper is to answer (1) how and to what degree an evidence-based home-visiting model benefits mothers and children with substance use or depression and (2) what baseline characteristics indicate who can benefit most. We completed a secondary data analysis of the most recently completed randomized controlled trial (RCT) of Family Spirit (N = 322), a federally endorsed home-visiting intervention designed for young Native American mothers and their children. We examined how baseline differences in mothers' substance use, depression, and demographic characteristics (household mobility, education, parity, and premature birth) moderated mothers' and children's intervention-related outcomes. Children born to mothers with past substance use histories benefited more from the intervention than children born to abstinent mothers (p < 0.01). Unstable housing, parity, and low educational attainment emerged as moderators of intervention effectiveness. Results from this investigation will serve as a basis for designing and evaluating a precision approach to Family Spirit and may provide lessons for other models to explore tailoring variables for optimal impact and efficiency. Trial Registry: NCT00373750.

Principles of Precision Prevention Science for Improving Recruitment and Retention of Participants.

Precision medicine and precision public health focus on identifying and providing the right intervention to the right population at the right time. Expanding on the concept, precision prevention science could allow the field to examine prevention programs to identify ways to make them more efficient and effective at scale, including addressing issues related to engagement and retention of participants. Research to date on engagement and retention has often focused on demographics and risk factors. The current paper proposes using McCurdy and Daro (Family Relations, 50, 113-121, 2001) model that posits a complex mixture of individual, provider, program, and community-level factors synergistically affect enrollment, engagement, and retention. The paper concludes recommending the use of research-practice partnerships and innovative, rapid cycle methods to design and improve prevention programs related to participant engagement and retention at scale.

Biomarkers of chemotherapy-induced cardiotoxicity: toward precision prevention using extracellular vesicles.

Detrimental side effects of drugs like doxorubicin, which can cause cardiotoxicity, pose barriers for preventing cancer progression, or treating cancer early through molecular interception. Extracellular vesicles (EVs) are valued for their potential as biomarkers of human health, chemical and molecular carcinogenesis, and therapeutics to treat disease at the cellular level. EVs are released both during normal growth and in response to toxicity and cellular death, playing key roles in cellular communication. Consequently, EVs may hold promise as precision biomarkers and therapeutics to prevent or offset damaging off-target effects of chemotherapeutics. EVs have promise as biomarkers of impending cardiotoxicity induced by chemotherapies and as cardioprotective therapeutic agents. However, EVs can also mediate cardiotoxic cues, depending on the identity and past events of their parent cells. Understanding how EVs mediate signaling is critical toward implementing EVs as therapeutic agents to mitigate cardiotoxic effects of chemotherapies. For example, it remains unclear how mixtures of EV populations from cells exposed to toxins or undergoing different stages of cell death contribute to signaling across cardiac tissues. Here, we present our perspective on the outlook of EVs as future clinical tools to mitigate chemotherapy-induced cardiotoxicity, both as biomarkers of impending cardiotoxicity and as cardioprotective agents. Also, we discuss how heterogeneous mixtures of EVs and transient exposures to toxicants may add complexity to predicting outcomes of exogenously applied EVs. Elucidating how EV cargo and signaling properties change during dynamic cellular events may aid precision prevention of cardiotoxicity in anticancer treatments and development of safer chemotherapeutics.

Deep Diving Into the Cardiovascular Health Paradox: A Journey Towards Personalized Prevention.

Objectives: The Life's Simple 7 score (LS7) promotes cardiovascular health (CVH). Despite this, some with optimal LS7 develop cardiovascular disease (CVD), while others with poor CVH do not, termed the "CVH paradox." This paper explores pathways explaining this paradox. Methods: We examined methodological aspects: 1) misclassification bias in self-reported lifestyle factors (smoking, physical activity, diet); 2) cumulative exposure to risk factors over a lifetime, impacting the CVH paradox. Punctual risk factor assessments are suboptimal for predicting outcomes. We proposed personalized prevention using "novel" elements to refine CVH assessment: 1) subclinical vascular disease markers, 2) metabolic biomarkers in blood and urine, 3) emerging risk factors, 4) polygenic risk scores (PRS), 5) epigenetics, and 6) the exposome. Results: Addressing the CVH paradox requires a multifaceted approach, reducing misclassification bias, considering cumulative risk exposure, and incorporating novel personalized prevention elements. Conclusion: A holistic, individualized approach to CVH assessment and CVD prevention can better reduce cardiovascular outcomes and improve population health. Collaboration among researchers, healthcare providers, policymakers, and communities is essential for effective implementation and realization of these strategies.

Engagement of patients and the public in personalised prevention in Europe using genomic information: a scoping review.

Introduction: Personalised prevention using genomic information requires active involvement from patients and the public, who should be well-informed and empowered to make healthcare decisions that reflect their personal values. We aimed to map engagement practises, and assess the extent and types of engagement methods used in the field of personalised prevention of common chronic conditions using genomic information. Methods: A scoping review on selected literature (in Medline, Embase, Scopus, Web of Science, APA PsycINFO, and IBSS) from 2015 to 2023 was performed. Articles included described practises of patient and public engagement in personalised prevention and genomics conducted in Europe focusing on cancer, cardiovascular diseases and neurodegenerative disorders. Engagement was explored based on grouping practises across the domains of care, research, education, and governance. Results: A total of 23 articles describing 23 engagement practises were selected. Analysis revealed diverse engagement levels, the majority falling into the low to medium engagement category, and showing mainly unidirectional methods of engagement, especially consultation. Most engagement activities related to cancer, and none to neurodegenerative disorders. Most publications appeared in the care domain, followed by the research domain, a combination of research and care, and a combination of governance and education. Conclusion: These results suggest that most practises to engage patients and public in personalised prevention using genomic information appear to have lower levels of engagement. Elaborating on and implementing practises that engage and empower patients and the public at all levels of the engagement spectrum and for all chronic diseases is needed, fostering a more inclusive and participatory approach to personalised prevention.

Biomarkers for personalised prevention of chronic diseases: a common protocol for three rapid scoping reviews.

INTRODUCTION: Personalised prevention aims to delay or avoid disease occurrence, progression, and recurrence of disease through the adoption of targeted interventions that consider the individual biological, including genetic data, environmental and behavioural characteristics, as well as the socio-cultural context. This protocol summarises the main features of a rapid scoping review to show the research landscape on biomarkers or a combination of biomarkers that may help to better identify subgroups of individuals with different risks of developing specific diseases in which specific preventive strategies could have an impact on clinical outcomes. This review is part of the "Personalised Prevention Roadmap for the future HEalThcare" (PROPHET) project, which seeks to highlight the gaps in current personalised preventive approaches, in order to develop a Strategic Research and Innovation Agenda for the European Union. OBJECTIVE: To systematically map and review the evidence of biomarkers that are available or under development in cancer, cardiovascular and neurodegenerative diseases that are or can be used for personalised prevention in the general population, in clinical or public health settings. METHODS: Three rapid scoping reviews are being conducted in parallel (February-June 2023), based on a common framework with some adjustments to suit each specific condition (cancer, cardiovascular or neurodegenerative diseases). Medline and Embase will be searched to identify publications between 2020 and 2023. To shorten the time frames, 10% of the papers will undergo screening by two reviewers and only English-language papers will be considered. The following information will be extracted by two reviewers from all the publications selected for inclusion: source type, citation details, country, inclusion/exclusion criteria (population, concept, context, type of evidence source), study methods, and key findings relevant to the review question/s. The selection criteria and the extraction sheet will be pre-tested. Relevant biomarkers for risk prediction and stratification will be recorded. Results will be presented graphically using an evidence map. INCLUSION CRITERIA: Population: general adult populations or adults from specific pre-defined high-risk subgroups; concept: all studies focusing on molecular, cellular, physiological, or imaging biomarkers used for individualised primary or secondary prevention of the diseases of interest; context: clinical or public health settings. SYSTEMATIC REVIEW REGISTRATION: https://doi.org/10.17605/OSF.IO/7JRWD (OSF registration DOI).

Cancer Precision-Prevention trial of Metformin in adults with Li Fraumeni syndrome (MILI) undergoing yearly MRI surveillance: a randomised controlled trial protocol.

BACKGROUND: Li-Fraumeni syndrome (LFS) is a rare autosomal dominant disease caused by inherited or de novo germline pathogenic variants in TP53. Individuals with LFS have a 70-100% lifetime risk of developing cancer. The current standard of care involves annual surveillance with whole-body and brain MRI (WB-MRI) and clinical review; however, there are no chemoprevention agents licensed for individuals with LFS. Preclinical studies in LFS murine models show that the anti-diabetic drug metformin is chemopreventive and, in a pilot intervention trial, short-term use of metformin was well-tolerated in adults with LFS. However, metformin's mechanism of anticancer activity in this context is unclear. METHODS: Metformin in adults with Li-Fraumeni syndrome (MILI) is a Precision-Prevention phase II open-labelled unblinded randomised clinical trial in which 224 adults aged ≥ 16 years with LFS are randomised 1:1 to oral metformin (up to 2 mg daily) plus annual MRI surveillance or annual MRI surveillance alone for up to 5 years. The primary endpoint is to compare cumulative cancer-free survival up to 5 years (60 months) from randomisation between the intervention (metformin) and control (no metformin) arms. Secondary endpoints include a comparison of cumulative tumour-free survival at 5 years, overall survival at 5 years and clinical characteristics of emerging cancers between trial arms. Safety, toxicity and acceptability of metformin; impact of metformin on quality of life; and impact of baseline lifestyle risk factors on cancer incidence will be assessed. Exploratory end-points will evaluate the mechanism of action of metformin as a cancer preventative, identify biomarkers of response or carcinogenesis and assess WB-MRI performance as a diagnostic tool for detecting cancers in participants with LFS by assessing yield and diagnostic accuracy of WB-MRI. DISCUSSION: Alongside a parallel MILI study being conducted by collaborators at the National Cancer Institute (NCI), MILI is the first prevention trial to be conducted in this high-risk group. The MILI study provides a unique opportunity to evaluate the efficacy of metformin as a chemopreventive alongside exploring its mechanism of anticancer action and the biological process of mutated P53-driven tumourigenesis. TRIAL REGISTRATION: ISRCTN16699730. Registered on 28 November 2022. URL: https://www.isrctn.com/ EudraCT/CTIS number 2022-000165-41.

Multimodal Precision Prevention - A New Direction in Alzheimer's Disease.

At least 40% of all dementia has been linked to modifiable risk factors suggesting a clear potential for preventative approaches targeting these factors. Despite the recent promising findings from anti-amyloid monoclonal antibodies, a limited proportion of patients are expected to be eligible for these novel AD treatments. Given the heterogeneous nature of AD and the complex multi-level pathological processes leading to dementia (involving, e.g., shared risk factors, interaction of different pathology mechanisms, and their putative synergistic effects on cognition), targeting a single pathology may not be sufficient to halt or significantly impact disease progression. With exponentially increasing numbers of patients world-wide, in parallel to the unprecedented population ageing, new multimodal therapy approaches targeting several modifiable risk factors and disease mechanisms simultaneously are urgently required. Developing the next generation of combination therapies with lifestyle intervention and pharmacological treatments, implementing the right interventions for the right people at the right time, and defining accessible and sustainable strategies worldwide are crucial. Here, we summarize the state-of-the-art multimodal lifestyle-based approaches, especially findings and lessons learned from the FINGER trial, for prevention and risk reduction of cognitive impairment and dementia. We also discuss some emerging underlying biological mechanisms and the current development of precision prevention approaches. We present an example of a novel trial design combining healthy lifestyle changes with a repurposed putative disease-modifying drug and place this study in the context of the World-Wide FINGERS, the first interdisciplinary network of multimodal trials dedicated to the prevention and risk reduction of cognitive impairment and dementia.

Strategies reducing risk of surgical-site infection following pediatric spinal deformity surgery.

BACKGROUND: Identifying beneficial preventive strategies for surgical-site infection (SSI) in individual patients with different clinical and surgical characteristics is challenging. The purpose of this study was to investigate the association between preventive strategies and patient risk of SSI taking into consideration baseline risks and estimating the reduction of SSI probability in individual patients attributed to these strategies. METHODS: Pediatric patients who underwent primary, revision, or final fusion for their spinal deformity at 7 institutions between 2004 and 2018 were included. Preventive strategies included the use of topical vancomycin, bone graft, povidone-iodine (PI) irrigations, multilayered closure, impermeable dressing, enrollment in quality improvement (QI) programs, and adherence to antibiotic prophylaxis. The CDC definition of SSI as occurring within 90 days postoperatively was used. Multiple regression modeling was performed following multiple imputation and multicollinearity testing to investigate the effect of preventive strategies on SSI in individual patients adjusted for patient and surgical characteristics. RESULTS: Univariable regressions demonstrated that enrollment in QI programs and PI irrigation were significantly associated, and topical vancomycin, multilayered closure, and correct intraoperative dosing of antibiotics trended toward association with reduction of SSI. In the final prediction model using multiple regression, enrollment in QI programs remained significant and PI irrigation had an effect in decreasing risks of SSI by average of 49% and 18%, respectively, at the individual patient level. CONCLUSION: Considering baseline patient characteristics and predetermined surgical and hospital factors, enrollment in QI programs and PI irrigation reduce the risk of SSI in individual patients. Multidisciplinary efforts should be made to implement these practices to increase patient safety. LEVEL OF EVIDENCE: Prognostic level III study.