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Influenza is an important public health issue given its significant burden of disease. In Italy, the unsatisfactory coverage rate in people ≥65 years underlines the need to improve the current vaccination pathway. This study aims to define an integrated pathway across primary and secondary care, facilitated by a digital clinical decision support system (CDSS), to enhance vaccination coverage in people ≥65 years by actively recruiting patients in hospitals and administering vaccination. Moreover, the study seeks to gauge the potential epidemiological and economic impact of this approach. The methodology consisted of two main phases: definition of the integrated pathway and CDSS and estimation of the potential epidemiological and economic impact resulting from the implementation of the pathway in the whole Lazio region. Assuming an increase of influenza vaccination coverage from the current rate of 60% to 65% in ≥65 years old population in the Lazio region thanks to the pathway implementation, an increase of 8% in avoided influenza cases, avoided influenza- or pneumonia-related hospitalizations and avoided influenza-related outpatient visits was estimated with a relative increase in savings for hospitalizations and outpatient visits of up to 11.85%. Setting the vaccination coverage at 70%, the impact is doubled. Alongside offering a predictive estimate of the pathway’s potential impact, both epidemiological and economic, this project, with its robust methodology, may serve as a scalable and transferable model for enhancing vaccination coverage at national and international level.

Background: Aspirin intake might be inversely associated with head and neck cancer (HNC). Thus, we investigated this relationship within the International Head and Neck Cancer Epidemiology (INHANCE) consortium.Methods: Four case-control studies within the INHANCE consortium were included (2024 cases, 4196 controls). Study-specific odds ratios (ORs) and 95% confidence intervals (CIs) were estimated using logistic regression and subsequently pooled with DerSimonian-Laird random-effects model. Nonlinearity of the relationship between duration of intake and HNC was modeled with fractional polynomials.Results: Aspirin was inversely associated with HNC overall (OR = 0.48; 95% CI: 0.26, 0.91). Results for laryngeal cancer were similar (OR = 0.54; 95% CI: 0.30, 0.96). Analysis on duration of intake confirmed findings for HNC overall, showing also inverse associations for oropharyngeal and laryngeal cancer.Conclusions: This study suggests that aspirin intake may reduce the risk of HNC, driven mainly by decreases in risk for laryngeal and oropharyngeal cancer.

Background: The current management of lung cancer patients has reached a high level of complexity. Indeed, besides the traditional clinical variables (e.g., age, sex, TNM stage), new omics data have recently been introduced in clinical practice, thereby making more complex the decision-making process. With the advent of Artificial intelligence (AI) techniques, various omics datasets may be used to create more accurate predictive models paving the way for a better care in lung cancer patients. Methods: The LANTERN study is a multi-center observational clinical trial involving a multidisciplinary consortium of five institutions from different European countries. The aim of this trial is to develop accurate several predictive models for lung cancer patients, through the creation of Digital Human Avatars (DHA), defined as digital representations of patients using various omics-based variables and integrating well-established clinical factors with genomic data, quantitative imaging data etc. A total of 600 lung cancer patients will be prospectively enrolled by the recruiting centers and multi-omics data will be collected. Data will then be modelled and parameterized in an experimental context of cutting-edge big data analysis. All data variables will be recorded according to a shared common ontology based on variable-specific domains in order to enhance their direct actionability. An exploratory analysis will then initiate the biomarker identification process. The second phase of the project will focus on creating multiple multivariate models trained though advanced machine learning (ML) and AI techniques for the specific areas of interest. Finally, the developed models will be validated in order to test their robustness, transferability and generalizability, leading to the development of the DHA. All the potential clinical and scientific stakeholders will be involved in the DHA development process. The main goals aim of LANTERN project are: i) To develop predictive mode

Objective We analyzed the pooled case-control data from the International Head and Neck Cancer Epidemiology (INHANCE) consortium to compare cigarette smoking and alcohol consumption risk factors for head and neck cancer between less developed and more developed countries. Subjects and Methods The location of each study was categorized as either a less developed or more developed country. We compared the risk of overall head and neck cancer and cancer of specific anatomic subsites associated with cigarette smoking and alcohol consumption. Additionally, age and sex distribution between categories was compared. Results The odds ratios for head and neck cancer sites associated with smoking duration differed between less developed and more developed countries. Smoking greater than 20 years conferred a higher risk for oral cavity and laryngeal cancer in more developed countries, whereas the risk was greater for oropharynx and hypopharynx cancer in less developed countries. Alcohol consumed for more than 20 years conferred a higher risk for oropharynx, hypopharynx, and larynx cancer in less developed countries. The proportion of cases that were young (<45 years) or female differed by country type for some HNC subsites. Conclusion These findings suggest the degree of industrialization and economic development affects the relationship between smoking and alcohol with head and neck cancer.

Background: Gastric cancer (GC) is clinically heterogenous according to location (cardia/non-cardia) and histopathology (diffuse/intestinal). We aimed to characterize the genetic risk architecture of GC according to its subtypes. Another aim was to examine whether cardia GC and oesophageal adenocarcinoma (OAC) and its precursor lesion Barrett's oesophagus (BO), which are all located at the gastro-oesophageal junction (GOJ), share polygenic risk architecture. Methods: We did a meta-analysis of ten European genome-wide association studies (GWAS) of GC and its subtypes. All patients had a histopathologically confirmed diagnosis of gastric adenocarcinoma. For the identification of risk genes among GWAS loci we did a transcriptome-wide association study (TWAS) and expression quantitative trait locus (eQTL) study from gastric corpus and antrum mucosa. To test whether cardia GC and OAC/BO share genetic aetiology we also used a European GWAS sample with OAC/BO. Findings: Our GWAS consisting of 5816 patients and 10,999 controls highlights the genetic heterogeneity of GC according to its subtypes. We newly identified two and replicated five GC risk loci, all of them with subtype-specific association. The gastric transcriptome data consisting of 361 corpus and 342 antrum mucosa samples revealed that an upregulated expression of MUC1, ANKRD50, PTGER4, and PSCA are plausible GC-pathomechanisms at four GWAS loci. At another risk locus, we found that the blood-group 0 exerts protective effects for non-cardia and diffuse GC, while blood-group A increases risk for both GC subtypes. Furthermore, our GWAS on cardia GC and OAC/BO (10,279 patients, 16,527 controls) showed that both cancer entities share genetic aetiology at the polygenic level and identified two new risk loci on the single-marker level. Interpretation: Our findings show that the pathophysiology of GC is genetically heterogenous according to location and histopathology. Moreover, our findings point to common molecular me

Introduction: Personalized Medicine (PM) is one of the main priorities of the research agenda of the European Commission and the focus of the European Coordination and Support Action titled "Integrating China into the International Consortium for Personalized Medicine" (IC2PerMed). Similar to the European focus, PM is a current priority of the Chinese Government, through dedicated policies and its five-year investment plans. In the context of IC2PerMed, we implemented a survey to understand the state of the art of the implementation of PM related policies in EU and China, and to identify opportunities for future Sino-European collaborations. Methods: The survey was elaborated by the IC2PerMed consortium and validated by a focus group of experts. The final version, in English and Chinese, was administered online to a pool of accurately selected experts. Participation was anonymous and voluntary. The survey consists of 19 questions in 3 sections: (1) personal information; (2) policy in PM; (3) facilitating and hindering factors for Sino-European collaboration in PM. Results: Forty-seven experts completed the survey, 27 from Europe and 20 from China. Only four participants were aware of the implementation of PM-related policies in their working country. Expert reported that PM areas with greatest policy impact so far were: Big Data and digital solutions; citizen and patient literacy; and translational research. The main obstacles found were the lack of shared investment strategies and the limited application of scientific developments in clinical practice. Aligning European and Chinese efforts, finding common ground across cultural, social, and language barriers, were considered as actions needed to enhance efforts in applying PM strategies internationally. Conclusion: To achieve efficiency and sustainability of health systems, it remains crucial to transform PM into an opportunity for all citizens and patients with the commitment of all the stakeholders involved. The

Background European countries are still searching to eliminate or contain the Covid-19 pandemic. A variety of approaches have achieved different levels of success in limiting the spread of the disease early and preventing avoidable deaths. Governmental policy responses may explain these differences and this study aims to describe evidence about the effectiveness of containment measures throughout the course of the pandemic in five European countries (France, Germany, Italy, Spain and the UK). Methods The research approach adopted consisted of three steps: 1) Build a Containment Index (C.I.) that considers nine parameters to make an assessment on the strength of measures; 2) Develop dynamic epidemiological models for forecasting purposes; 3) Predict case numbers by assuming containment measures remain constant for a period of 30 days. Results Our analysis revealed that in the five European countries we compared, the use of different approaches definitively affected the effectiveness of containment measures for the Covid-19 pandemic. Conclusion The evidence found in our research can be useful to inform policy makers' decisions when deciding to introduce or relax containment measures and their timing, both during the current pandemic or in addressing possible future health crises.

Background: The spread of Personalized Medicine (PM) over the last decade defined a revolution in healthcare systems. PM is among the priorities of the European Commission's research agenda, which funded the IC2PerMed international project aiming to integrate China into the International Consortium of PM (ICPerMed). In the context of this project, we mapped the existing policies related to PM in the European Union (EU) and at the EU Member States (EU-MS) level. Methods: PubMed, Google Scholar, Google, Microsoft and national and international institutions' official repositories were searched in order to identify documents on PM-related policies, programmes and action plans at the EU and EU-MS level, published up to December 2020. Results: We identified 28 policies in the EU aimed at improving public health promoting and fostering PM implementation, through some actions including the standardization of good medical practice, use of big data and digital innovation, data sharing and cross-border interoperability, healthcare sustainability, disease prevention and patients'/citizens' engagement. We identified 23 policies at EU-MS level which, notwithstanding national differences, have a common focus, such as patient-tailored treatment and targeted prevention, education of healthcare workers, research and innovation, big data harmonization and healthcare system sustainability. Conclusions: The definition of an integrated regulatory framework is essential to turn PM into an opportunity for citizens and patients with the involvement of all the stakeholders. This work can provide a valuable tool for decision-makers to define common approaches, priorities for research, development and increase international collaboration, which could overcome the fragmented European scenario and align the future direction on PM.

Objective: To examine SARS-CoV-2 vaccine confidence, attitudes and intentions in Australian adults as part of the iCARE Study. Design and setting: Cross-sectional online survey conducted when free COVID-19 vaccinations first became available in Australia in February 2021. Participants: Total of 1166 Australians from general population aged 18-90 years (mean 52, SD of 19). Main outcome measures: Primary outcome: responses to question 'If a vaccine for COVID-19 were available today, what is the likelihood that you would get vaccinated?'.Secondary outcome: analyses of putative drivers of uptake, including vaccine confidence, socioeconomic status and sources of trust, derived from multiple survey questions. Results: Seventy-eight per cent reported being likely to receive a SARS-CoV-2 vaccine. Higher SARS-CoV-2 vaccine intentions were associated with: increasing age (OR: 2.01 (95% CI 1.77 to 2.77)), being male (1.37 (95% CI 1.08 to 1.72)), residing in least disadvantaged area quintile (2.27 (95% CI 1.53 to 3.37)) and a self-perceived high risk of getting COVID-19 (1.52 (95% CI 1.08 to 2.14)). However, 72% did not believe they were at a high risk of getting COVID-19. Findings regarding vaccines in general were similar except there were no sex differences. For both the SARS-CoV-2 vaccine and vaccines in general, there were no differences in intentions to vaccinate as a function of education level, perceived income level and rurality. Knowing that the vaccine is safe and effective and that getting vaccinated will protect others, trusting the company that made it and vaccination recommended by a doctor were reported to influence a large proportion of the study cohort to uptake the SARS-CoV-2 vaccine. Seventy-eight per cent reported the intent to continue engaging in virus-protecting behaviours (mask wearing, social distancing, etc) postvaccine. Conclusions: Most Australians are likely to receive a SARS-CoV-2 vaccine. Key influencing factors identified (eg, knowing vaccine is

Background: Risk prediction models incorporating single nucleotide polymorphisms (SNPs) could lead to individualized prevention of colorectal cancer (CRC). However, the added value of incorporating SNPs into models with only traditional risk factors is still not clear. Hence, our primary aim was to summarize literature on risk prediction models including genetic variants for CRC, while our secondary aim was to evaluate the improvement of discriminatory accuracy when adding SNPs to a prediction model with only traditional risk factors. Methods: We conducted a systematic review on prediction models incorporating multiple SNPs for CRC risk prediction. We tested whether a significant trend in the increase of Area Under Curve (AUC) according to the number of SNPs could be observed, and estimated the correlation between AUC improvement and number of SNPs. We estimated pooled AUC improvement for SNP-enhanced models compared with non-SNP-enhanced models using random effects meta-analysis, and conducted meta-regression to investigate the association of specific factors with AUC improvement. Results: We included 33 studies, 78.79% using genetic risk scores to combine genetic data. We found no significant trend in AUC improvement according to the number of SNPs (p for trend = 0.774), and no correlation between the number of SNPs and AUC improvement (p = 0.695). Pooled AUC improvement was 0.040 (95% CI: 0.035, 0.045), and the number of cases in the study and the AUC of the starting model were inversely associated with AUC improvement obtained when adding SNPs to a prediction model. In addition, models constructed in Asian individuals achieved better AUC improvement with the incorporation of SNPs compared with those developed among individuals of European ancestry. Conclusions: Though not conclusive, our results provide insights on factors influencing discriminatory accuracy of SNP-enhanced models. Genetic variants might be useful to inform stratified CRC screening in the future

Background: The COVID-19 pandemic affected healthcare systems worldwide. Predictive models developed by Artificial Intelligence (AI) and based on timely, centralized and standardized real world patient data could improve management of COVID-19 to achieve better clinical outcomes. The objectives of this manuscript are to describe the structure and technologies used to construct a COVID-19 Data Mart architecture and to present how a large hospital has tackled the challenge of supporting daily management of COVID-19 pandemic emergency, by creating a strong retrospective knowledge base, a real time environment and integrated information dashboard for daily practice and early identification of critical condition at patient level. This framework is also used as an informative, continuously enriched data lake, which is a base for several on-going predictive studies. Methods: The information technology framework for clinical practice and research was described. It was developed using SAS Institute software analytics tool and SAS® Vyia® environment and Open-Source environment R ® and Python ® for fast prototyping and modeling. The included variables and the source extraction procedures were presented. Results: The Data Mart covers a retrospective cohort of 5528 patients with SARS-CoV-2 infection. People who died were older, had more comorbidities, reported more frequently dyspnea at onset, had higher D-dimer, C-reactive protein and urea nitrogen. The dashboard was developed to support the management of COVID-19 patients at three levels: hospital, single ward and individual care level. Interpretation: The COVID-19 Data Mart based on integration of a large collection of clinical data and an AI-based integrated framework has been developed, based on a set of automated procedures for data mining and retrieval, transformation and integration, and has been embedded in the clinical practice to help managing daily care. Benefits from the availability of a Data Mart include the oppor

Background: Health Technology Assessment (HTA) is a multidisciplinary process that synthesizes, with a systematic, transparent, impartial and robust methodological approach, the main information on the medical, economic, ethical and social implications of the use and dissemination of a health technology. Its aim is to support decision-makers in identifying safe, effective, patient-centered and best-value health policies, in order to promote an equitable, efficient, and high-quality health system. Given the continued application of innovative technologies into clinical practice, healthcare professionals need to be able to adequately evaluate these technologies using evidence-based approaches such as HTA. Therefore, the implementation of training in HTA is crucial. The aim of this study was to investigate existing HTA training initiatives for healthcare professionals provided by international HTA agencies and organizations around the world. Methods: From March to November 2020, the websites of HTA agencies and organizations belonging to the European network for HTA (EUnetHTA) and to the International Network of Agencies for HTA (INAHTA), and the website of the HTA International (HTAi), were explored for identifying the HTA training initiatives directed to healthcare professionals. In addition, we screened the training initiatives proposed at European level by EUnetHTA as part of its Joint Actions and conducted in collaboration with its public-private partners. Specific keywords were searched in English and adapted to French, Portuguese, Spanish, Italian and German. Data extraction of the retrieved training initiatives was conducted from November 2020 to February 2021 and considered the following information: agency, country, website, coordinator, type of initiative, target, topic, main contents, and language. Results: Out of 124 agencies/organizations/EUnetHTA public-private partners screened, only 21 provided training initiatives for healthcare professionals. A total

Introduction. Citizens’ literacy in the field of genomics represents one of the cornerstones of proper implementation of genomics in healthcare services. In order to identify the most effective tools by which to elevate citizens’ literacy in genomics, we conducted a survey among the group of multidisciplinary experts within the Italian Network of Genomics in Public Health (GENISAP). Methods. Two rounds of Delphi surveys were carried out in order to identify the main topics, tools, settings, and healthcare professionals’ backgrounds that might usefully be included in citizens’ training initiatives in genomics. To this end, we distributed a questionnaire with 39 items that are scored on a 5-point scale. Results. By the end of the Delphi process, 43 items were selected (19 for the topics, 6 for the tools, 9 for settings, and 9 for the healthcare professionals’ backgrounds). Genomic tests and counseling were among the main topics included, while in terms of tools, faceto-face discussion with healthcare professionals was prioritized by the experts. Among the most appropriate platforms, the group suggested internet/social media and healthcare settings. The healthcare professional considered to have the most relevant role in terms of citizens’ education was a medical doctor with a specialism in clinical genetics. Discussion. Our study attempted to identify the main characteristics that could guide the design of interventions to promote public literacy regarding the field of genomics . Specifically, we have identified the main topics to be included in an educational program for citizens, the tools and settings to consider when providing educational initiatives on genomics, and the healthcare professionals who need to be involved in these initiatives. Therefore, the results of our study provide the necessary basis for the realization of new training initiatives on genomics to be proposed and offered to citizens, these initiatives to be implemented at a national and internati

The disruptive advances in genomics contributed to achieve higher levels of precision in the diagnosis and treatment of cancer. This scientific advance entails the need for greater literacy for all healthcare professionals. Our study summarizes the training initiatives conducted worldwide in cancer genomics field for healthcare professionals. We conducted a web search of the training initiatives aimed at improving healthcare professionals’ literacy in cancer genomics undertaken worldwide by using two search engines (Google and Bing) in English language and conducted from 2003 to 2021. A total of 85,649 initiatives were identified. After the screening process, 36 items were included. The majority of training programs were organized in the United States (47%) and in the United Kingdom (28%). Most of the initiatives were conducted in the last five years (83%) by universities (30%) and as web-based modalities (80%). In front of the technological advances in genomics, education in cancer genomics remains fundamental. Our results may contribute to provide an update on the development of educational programs to build a skilled and appropriately trained genomics health workforce in the future.

OBJECTIVE: To develop a deep learning-based decision tree for the primary care setting, to stratify adult patients with confirmed and unconfirmed coronavirus disease 2019 (COVID-19), and to predict the need for hospitalization or home monitoring.PATIENTS AND METHODS: We performed a retrospective cohort study on data from patients admitted to a COVID hospital in Rome, Italy, between 5 March 2020 and 5 June 2020. A confirmed case was defined as a patient with a positive nasopharyngeal RT-PCR test result, while an unconfirmed case had negative results on repeated swabs. Patients' medical history and clinical, laboratory and radiological findings were collected, and the dataset was used to train a predictive model for COVID-19 severity.RESULTS: Data of 198 patients were included in the study. Twenty-eight (14.14%) had mild disease, 62 (31.31%) had moderate disease, 64 (32.32%) had severe disease, and 44 (22.22%) had critical disease. The G(2) value assessed the contribution of each collected value to decision tree building. On this basis, SpO2 (%) with a cut point at 92 was chosen for the optimal first split. Therefore, the decision tree was built using values maximizing G(2) and LogWorth. After the tree was built, the correspondence between inputs and outcomes was validated.CONCLUSIONS: We developed a machine learning-based tool that is easy to understand and apply. It provides good discrimination in stratifying confirmed and unconfirmed COVID-19 patients with different prognoses in every context. Our tool might allow general practitioners visiting patients at home to decide whether the patient needs to be hospitalized.

OBJECTIVE: To develop a deep learning-based decision tree for the primary care setting, to stratify adult patients with confirmed and unconfirmed coronavirus disease 2019 (COVID-19), and to predict the need for hospitalization or home monitoring.PATIENTS AND METHODS: We performed a retrospective cohort study on data from patients admitted to a COVID hospital in Rome, Italy, between 5 March 2020 and 5 June 2020. A confirmed case was defined as a patient with a positive nasopharyngeal RT-PCR test result, while an unconfirmed case had negative results on repeated swabs. Patients' medical history and clinical, laboratory and radiological findings were collected, and the dataset was used to train a predictive model for COVID-19 severity.RESULTS: Data of 198 patients were included in the study. Twenty-eight (14.14%) had mild disease, 62 (31.31%) had moderate disease, 64 (32.32%) had severe disease, and 44 (22.22%) had critical disease. The G(2) value assessed the contribution of each collected value to decision tree building. On this basis, SpO2 (%) with a cut point at 92 was chosen for the optimal first split. Therefore, the decision tree was built using values maximizing G(2) and LogWorth. After the tree was built, the correspondence between inputs and outcomes was validated.CONCLUSIONS: We developed a machine learning-based tool that is easy to understand and apply. It provides good discrimination in stratifying confirmed and unconfirmed COVID-19 patients with different prognoses in every context. Our tool might allow general practitioners visiting patients at home to decide whether the patient needs to be hospitalized.

OBJECTIVE: To develop a deep learning-based decision tree for the primary care setting, to stratify adult patients with confirmed and unconfirmed coronavirus disease 2019 (COVID-19), and to predict the need for hospitalization or home monitoring. PATIENTS AND METHODS: We performed a retrospective cohort study on data from patients admitted to a COVID hospital in Rome, Italy, between 5 March 2020 and 5 June 2020. A confirmed case was defined as a patient with a positive nasopharyngeal RT-PCR test result, while an unconfirmed case had negative results on repeated swabs. Patients’ medical history and clinical, laboratory and radiological findings were collected, and the dataset was used to train a predictive model for COVID-19 severity. RESULTS: Data of 198 patients were included in the study. Twenty-eight (14.14%) had mild disease, 62 (31.31%) had moderate disease, 64 (32.32%) had severe disease, and 44 (22.22%) had critical disease. The G2 value assessed the contribution of each collected value to decision tree building. On this basis, SpO2 (%) with a cut point at 92 was chosen for the optimal first split. Therefore, the decision tree was built using values maximizing G2 and LogWorth. After the tree was built, the correspondence between inputs and outcomes was validated. CONCLUSIONS: We developed a machine learning-based tool that is easy to understand and apply. It provides good discrimination in stratifying confirmed and unconfirmed COVID-19 patients with different prognoses in every context. Our tool might allow general practitioners visiting patients at home to decide whether the patient needs to be hospitalized.

Healthcare workers are at the forefront against COVID-19, worldwide. Since Fondazione Policlinico Universitario A. Gemelli (FPG) IRCCS was enlisted as a COVID-19 hospital, the healthcare workers deployed to COVID-19 wards were separated from those with limited/no exposure, whereas the administrative staff were designated to work from home. Between 4 June and 3 July 2020, an investigation was conducted to evaluate the seroprevalence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) immunoglobulin (IgG) antibodies among the employees of the FPG using point-of-care (POC) and venous blood tests. Sensitivity, specificity, and predictive values were determined with reverse-transcription polymerase chain reaction on nasal/oropharyngeal swabs as the diagnostic gold standard. The participants enrolled amounted to 4777. Seroprevalence was 3.66% using the POC test and 1.19% using the venous blood test, with a significant difference (p < 0.05). The POC test sensitivity and specificity were, respectively, 63.64% (95% confidence interval (CI): 62.20% to 65.04%) and 96.64% (95% CI: 96.05% to 97.13%), while those of the venous blood test were, respectively, 78.79% (95% CI: 77.58% to 79.94%) and 99.36% (95% CI: 99.07% to 99.55%). Among the low-risk populations, the POC test’s predictive values were 58.33% (positive) and 98.23% (negative), whereas those of the venous blood test were 92.86% (positive) and 98.53% (negative). According to our study, these serological tests cannot be a valid alternative to diagnose COVID-19 infection in progress.

The COVID-19 pandemic is impressively challenging the healthcare system. Several prognostic models have been validated but few of them are implemented in daily practice. The objective of the study was to validate a machine-learning risk prediction model using easy-to-obtain parameters to help to identify patients with COVID-19 who are at higher risk of death. The training cohort included all patients admitted to Fondazione Policlinico Gemelli with COVID-19 from March 5, 2020, to November 5, 2020. Afterward, the model was tested on all patients admitted to the same hospital with COVID-19 from November 6, 2020, to February 5, 2021. The primary outcome was in-hospital case-fatality risk. The out-of-sample performance of the model was estimated from the training set in terms of Area under the Receiving Operator Curve (AUROC) and classification matrix statistics by averaging the results of fivefold cross validation repeated 3-times and comparing the results with those obtained on the test set. An explanation analysis of the model, based on the SHapley Additive exPlanations (SHAP), is also presented. To assess the subsequent time evolution, the change in paO2/FiO2 (P/F) at 48 h after the baseline measurement was plotted against its baseline value. Among the 921 patients included in the training cohort, 120 died (13%). Variables selected for the model were age, platelet count, SpO2, blood urea nitrogen (BUN), hemoglobin, C-reactive protein, neutrophil count, and sodium. The results of the fivefold cross-validation repeated 3-times gave AUROC of 0.87, and statistics of the classification matrix to the Youden index as follows: sensitivity 0.840, specificity 0.774, negative predictive value 0.971. Then, the model was tested on a new population (n = 1463) in which the case-fatality rate was 22.6%. The test model showed AUROC 0.818, sensitivity 0.813, specificity 0.650, negative predictive value 0.922. Considering the first quartile of the predicted risk score (low-risk sc

Purpose. A practice synthesis of available evidence-based medicine data in ovarian cancer (OC), aiming to provide directions for future research. Materials and Methods. We performed a systematic review. PubMed was searched for relevant OC trials between January 2000 and December 2019. Results. Out of 865 references screened, 199 trials were found eligible for inclusion. Most trials were multicenter (83.9%). There was a trend reduction in the number of patients enrolled/per study over the years. Studies testing targeted/biological therapies dominated the second decade (60 trials in 2010-2019 versus 2 trials in 2000-2009). The proportion of trials with positive survival and clinical outcomes significantly increased from 23.8% in early 2000s to 54.1% in the last 5 years. Trials with histology/molecular biomarker criteria were more likely to meet progression-free survival endpoint than those without these selection criteria (69.2% versus 32.6%). Conclusion. This systematic review suggests a trend of increased positive studies, mainly linked to precision medicine.

The objectives of the study were to calculate the standardised mortality rates (SMRs) for COVID-19 in European Union/European Economic Area countries plus the UK and Switzerland and to evaluate the correlation between SMRs and selected indicators in the first versus the subsequent waves until 23 June 2021. We used indirect standardisation (using Italy as the reference) to compute SMRs and considered 16 indicators of health and social well-being, health system capacity and COVID-19 response. The highest SMRs were in Belgium, the UK and Spain in the first wave (1.20-1.84) and in Hungary, Czechia and Slovakia in the subsequent waves (2.50-2.69). Human Development Index (HDI), life expectancy, urbanisation and healthcare expenditure had positive correlations with SMR in the first wave (rho=0.30-0.46), but negative correlations (rho=-0.67 to -0.47) in the subsequent waves. Retail/recreation mobility and transit mobility were negatively correlated with SMR in the first wave, while transit mobility was inversely correlated with SMR in the subsequent waves. The first wave hit most hard countries with high HDI, high life expectancy, high urbanisation, high health expenditures and high tourism. This pattern may reflect higher early community seeding and circulation of the virus. Conversely, in the subsequent waves, this pattern was completely inversed: countries with more resources and better health status did better than eastern European countries. While major SMR differences existed across countries in the first wave, these differences largely dissipated by 23 June 2021, with few exceptions.

There are controversial results about the role of “ex novo” HLA-DR expression by tumor cells and its correlation with the oncological outcomes. Unfortunately, little is known about HLA-DR expression in laryngeal cancer tumor cells. The main purpose of this retrospective study is to strengthen the usefulness of studying “ex novo” HLA-DR expression on tumor cells from primary laryngeal squamous cell carcinoma (LSCC) patients and investigate its correlation with clinical outcome. We analyzed HLA-DR expression by immunohistochemical analysis in 56 patients with LSCC. The “ex novo” HLA-DR expression on laryngeal cancer tumor cells, assessing non-neoplastic LSCC – adjacent tissue, and the association of HLA-DR expression (HLA-DR+) with clinical outcomes were investigated. HLA-DR+ tumor cells were detected in 18/56 LSCC patients (32.1%). All specimens of non-neoplastic laryngeal carcinoma-adjacent tissue resulted HLA-DR negative (HLA-DR-). A statistically significant association was observed between HLA-DR + and well differentiated tumors (G1) (p<0.001). The Kaplan-Meier method showed how HLA-DR+ is significantly associated with both a better disease specific survival (HLA-DR+=100% vs. HLA-DR-=77.4%; p=0.047) and a better relapse free survival (HLA-DR+=100% vs. HLA-DR-=72.3%; p=0.021). Cox regression univariate analysis for death of disease confirmed a higher HR for HLA-DR absence on the surface of epithelial tumor cell [HR:37.489; 95% CI:0.750-18730.776; p=0.253] and for high-grade (G3) tumors [HR:18.601; 95% CI:3.613-95.764; p<0.0001]. Our results confirm that MHC class II HLA-DR expression is activated in a sub-set of LSCC patients. Evaluation of HLA-DR expression in LSCC could be useful for prognosis and future approaches towards personalized therapy.

Introduction: Population awareness and empowerment in omics sciences represent a fundamental driver to increase the adoption of evidence-based approaches in personalized medicine. In this context, a pivotal role is played by citizens’ literacy, and educational initiatives carried out in this context are key assets to drive future effective interventions. With the present study, we summarized the educational initiatives conducted worldwide aimed at increasing citizens’ literacy in omics sciences. Materials and Methods: We conducted a web search of the educational initiatives aimed at improving citizens’ literacy in omics sciences undertaken worldwide, by using three search engines (Google, Bing, and Yahoo Search), in English and in Italian languages. Results: We identified five initiatives in Europe, 22 in non-European countries, and 13 in Italy. Overall, the majority (69%) were web-based initiatives, while 31% required in-person attendance. The online initiatives included web pages for reading, online lessons/courses, web portals, videos/short movies, animations, and apps for mobile devices. The residential initiatives, on the other hand, included exhibitions, seminars, courses, symposia, information stands in public places, guided visits to research laboratories, and interactive laboratories. All the initiatives were highly heterogeneous in terms of methodologies and the topics addressed. Discussion and Conclusion: Overall, we identified a variety of initiatives aimed at improving citizens’ literacy in omics sciences, with the largest majority carried out in the United States and being web-based. Our results showed heterogeneity among the initiatives as to the dealt topics and the adopted methods. Further research is needed, however, to quantitatively assess the effectiveness of educational initiatives to improve citizens’ literacy in omics sciences.

No abstract available

Breast Cancer (BC) is the leading cause of death due to cancer in women. Ensuring equitable, quality-assured and effective care has increased the complexity of BC management. This systematic review reports on the state-of-the art of available literature investigating the enactment of personalized treatment and patient-centered care models in BC clinical practice, building a framework for the delivery of personalized BC care within a Patient-Centered model. Databases were searched for articles (from the inception to December 2020) reporting on Patient-Centered or Personalized Medicine BC management models, assessing success factors or limits. Out of 1885 records, 25 studies were included in our analysis. The main success factors include clearly defined roles and responsibilities within a multi-professional collaboration, appropriate training programs and adequate communication strategies and adopting a universal genomic language to improve patients’ involvement in the decision-making process. Among detected barriers, delays in the use of genetic testing were linked to the lack of public reimbursement schemes and of clear indications in timing and appropriateness. Overall, both care approaches are complementary and necessary to effectively improve BC patient management. Our framework attempts to bridge the gap in assigning a central role played by shared decision-making, still scarcely investigated in literature.

Background: Patient portals are becoming increasingly popular worldwide even though their impact on individual health and health system efficiency is still unclear. Objective: The aim of this systematic review was to summarize evidence on the impact of patient portals on health outcomes and health care efficiency, and to examine user characteristics, attitudes, and satisfaction. Methods: We searched the PubMed and Web of Science databases for articles published from January 1, 2013, to October 31, 2019. Eligible studies were primary studies reporting on the impact of patient portal adoption in relation to health outcomes, health care efficiency, and patient attitudes and satisfaction. We excluded studies where portals were not accessible for patients and pilot studies, with the exception of articles evaluating patient attitudes. Results: Overall, 3456 records were screened, and 47 articles were included. Among them, 11 studies addressed health outcomes reporting positive results, such as better monitoring of health status, improved patient-doctor interaction, and improved quality of care. Fifteen studies evaluated the impact of digital patient portals on the utilization of health services with mixed results. Patient characteristics were described in 32 studies, and it was reported that the utilization rate usually increases with age and female gender. Finally, 30 studies described attitudes and defined the main barriers (concerns about privacy and data security, and lack of time) and facilitators (access to clinical data and laboratory results) to the use of a portal. Conclusions: Evidence regarding health outcomes is generally favorable, and patient portals have the potential to enhance the doctor-patient relationship, improve health status awareness, and increase adherence to therapy. It is still unclear whether the use of patient portals improves health service utilization and efficiency.

Purpose: Neuroendocrine neoplasia (NEN) has been displaying an incremental trend along the last two decades. This phenomenon is poorly understood, and little information is available on risk factor for neuroendocrine neoplasia development. Aim of this work is to elucidate the role of potentially modifiable risk factors for pancreatic and pulmonary NEN. Methods: We conducted a case–control study on 184 patients with NEN (100 pancreas and 84 lung) and 248 controls. The structured questionnaire included 84 queries on socio-demographic, behavioral, dietary and clinical information. Results: Increased risk was associated with history of cancer (“other tumor”, lung OR = 7.18; 95% CI: 2.55–20.20 and pancreas OR = 5.88; 95% CI: 2.43–14.22; “family history of tumor”, lung OR = 2.66; 95% CI: 1.53–4.64 and pancreas OR = 1.94; 95% CI: 1.19–3.17; “family history of lung tumor”, lung OR = 2.56; 95% CI: 1.05–6.24 and pancreas OR = 2.60; 95% CI: 1.13–5.95). Type 2 diabetes mellitus associated with an increased risk of pancreatic NEN (OR = 3.01; 95% CI: 1.15–7.89). Conclusions: Besides site-specific risk factors, there is a significant link between neuroendocrine neoplasia and cancer in general, pointing to a shared cancer predisposition.

In order to reduce the burden on healthcare systems and to support differential diagnosis with COVID-19, influenza and pneumococcal vaccinations were strongly recommended during the COVID-19 pandemic, especially in vulnerable groups. However, no univocal and conclusive evidence on the relationship between influenza and pneumococcal vaccinations and COVID‐19 outcomes exists. We evaluated the association between such vaccinations, COVID-19 hospitalization, intensive care unit admissions and deaths in a cohort (N = 741) of COVID-19 patients who had access to the emergency room of a large Italian University hospital between March 1, 2020 and June 1, 2020. Results show that influenza and pneumococcal vaccinations did not affect hospitalization, intensive care unit admission and deaths in COVID-19 patients in the overall sample and in those ≥65 years. The same pattern of results was confirmed considering timing of influenza vaccine administration, vaccination type, and number of uptakes in the last five vaccination campaigns. In conclusion, our study does not support an impact of influenza and pneumococcal vaccinations on COVID-19 outcomes.

Background: Gastric cancer pathogenesis represents a complex interaction of host genetic determinants, microbial virulence factors and environmental exposures. Our primary aim was to determine the association between occupations/occupational exposures and odds of gastric cancer. Methods: We conducted a pooled-analysis of individual-level data harmonized from 11 studies in the Stomach cancer Pooling Project. Multivariable logistic regression was used to estimate the odds ratio (OR) of gastric cancer adjusted for relevant confounders. Results: A total of 5279 gastric cancer cases and 12 297 controls were analysed. There were higher odds of gastric cancer among labour-related occupations, including: agricultural and animal husbandry workers [odds ratio (OR) 1.33, 95% confidence interval (CI): 1.06-1.68]; miners, quarrymen, well-drillers and related workers (OR 1.70, 95% CI: 1.01-2.88); blacksmiths, toolmakers and machine-tool operators (OR 1.41, 95% CI: 1.05-1.89); bricklayers, carpenters and construction workers (OR 1.30, 95% CI: 1.06-1.60); and stationary engine and related equipment operators (OR 6.53, 95% CI: 1.41-30.19). The ORs for wood-dust exposure were 1.51 (95% CI: 1.01-2.26) for intestinal-type and 2.52 (95% CI: 1.46-4.33) for diffuse-type gastric cancer. Corresponding values for aromatic amine exposure were 1.83 (95% CI: 1.09-3.06) and 2.92 (95% CI: 1.36-6.26). Exposure to coal derivatives, pesticides/herbicides, chromium, radiation and magnetic fields were associated with higher odds of diffuse-type, but not intestinal-type gastric cancer. Conclusions: Based on a large pooled analysis, we identified several occupations and related exposures that are associated with elevated odds of gastric cancer. These findings have potential implications for risk attenuation and could be used to direct investigations evaluating the impact of targeted gastric cancer prevention/early detection programmes based on occupation.

LEGAL RESPONSIBILITY OF VACCINATING DOCTOR. The legal responsibility of the vaccinating doctor is one of the central issues in the current setting of the Covid-19 pandemic. The aim of this statement is to outline the profiles of the medical legal liability, with a focus on the figure of the vaccinating physician, in criminal, civil, and disciplinary terms, based on the Italian legislation in force. The vaccinating doctor responds for his work in the field of vaccination in the same way as any other health service should perform (diagnostic, therapeutic, etc.). Helpful in this context is the adoption of the L. 76/2021; it was developed to find a balance between safeguarding the person privacy and greater guarantees for the doctor. This law introduces a criminal shield that can put a limit to litigation, curbing the phenomenon of so-called defensive medicine. The climate of uncertainty and fear of legal repercussions for the doctors, and the constant updating and redefinition of the indications of operability in the vaccination campaigns, underline the need to focus on the knowledge of the responsibilities and the safeguard of the vaccinating doctors. In addition to the regulatory cornerstones, the statement also addresses the issue of informed consent and the role of the occupational doctor as a central figure in the vaccination campaign in the workplace.

Objectives: Most countries initially deployed COVID-19 vaccines preferentially in elderly populations. We aimed to evaluate whether population-level vaccine effectiveness is heralded by an increase in the relative proportion of deaths among non-elderly populations that were less covered by vaccination programs. Eligible data: We collected data from 40 countries on age-stratified COVID-19 deaths during the vaccination period (1/14/2021-5/31/2021) and two control periods (entire pre-vaccination period and excluding the first wave). Main outcome measures: We meta-analyzed the proportion of deaths in different age groups in vaccination versus control periods in (1) countries with low vaccination rates; (2) countries with age-independent vaccination policies; and (3) countries with standard age-dependent vaccination policies. Results: Countries that prioritized vaccination among older people saw an increasing share of deaths among 0-69 year old people in the vaccination versus the two control periods (summary proportion ratio 1.32 [95 CI% 1.24-1.41] and 1.35 [95 CI% 1.26-1.44)]. No such change was seen on average in countries with age-independent vaccination policies (1.05 [95 CI% 0.78-1.41 and 0.97 [95 CI% 0.95-1.00], respectively) and limited vaccination (0.93 [95 CI% 0.85-1.01] and 0.95 [95 CI% 0.87-1.03], respectively). Proportion ratios were associated with the difference of vaccination rates in elderly versus non-elderly people. No significant changes occurred in the share of deaths in age 0-49 among all 0-69 deaths in the vaccination versus pre-vaccination periods. Conclusions: The substantial shift in the age distribution of COVID-19 deaths in countries that rapidly implemented vaccination predominantly among elderly provides evidence for the population level-effectiveness of COVID-19 vaccination and a favorable evolution of the pandemic towards endemicity with fewer elderly deaths. Keywords: COVID-19; Death; Population data; Vaccination.

Research is still required to establish the relationship between family history (FH) and gastric cancer (GC) in relation to different histological types and anatomical sites. The present work aimed to examine the influence of first-degree FH on the risk of GC, also according to the GC location and histological type, including 5946 cases and 12,776 controls from 17 studies of 11 countries in three continents participating in the Stomach Cancer Pooling (StoP) Project consortium. This analysis confirms the effect of FH on the risk of GC, reporting an approximately doubled risk, and provides further quantification of the risk of GC according to the subsite and histotype. Although there is a clear relationship between family history (FH) and the risk of gastric cancer (GC), quantification is still needed in relation to different histological types and anatomical sites, and in strata of covariates. The objective was to analyze the risk of GC according to first-degree FH in a uniquely large epidemiological consortium of GC. This investigation includes 5946 cases and 12,776 controls from 17 studies of the Stomach Cancer Pooling (StoP) Project consortium. Summary odds ratios (OR) and the corresponding 95% confidence intervals (CIs) were calculated by pooling study-specific ORs using fixed-effect model meta-analysis techniques. Stratified analyses were carried out by sex, age, tumor location and histological type, smoking habit, socioeconomic status, alcohol intake and fruit consumption. The pooled OR for GC was 1.84 (95% CI: 1.64-2.04; I2 = 6.1%, P heterogeneity = 0.383) in subjects with vs. those without first-degree relatives with GC. No significant differences were observed among subgroups of sex, age, geographic area or study period. Associations tended to be stronger for non-cardia (OR = 1.82; 95% CI: 1.59-2.05 for subjects with FH) than for cardia GC (OR = 1.38; 95% CI: 0.98-1.77), and for the intestinal (OR = 1.92; 95% CI: 1.62-2.23) than for the diffuse histotype (OR

Sustainable nutrition, equaling earth health, involves a personalized approach designed in terms of precision and avoidance of still cogent but unjustified dogmas, equaling public health. For instance, current dietary recommendations continue to dwell on the need to limit as much as possible the intake of saturated fatty acids (SFA), notwithstanding the mounting evidence that the effects of food on health cannot be predicted from the content of single nutrients without considering the overall macronutrient composition and the role of the food matrix. The traditional recommendation to restrict SFA ignores that their effects on health depend on the interaction between naturally occurring food components and those introduced by food processing. It is warranted to modify the still widely promoted dietary guidelines based upon such single nutrients as SFA and instead personalize dietary habits on the basis of the whole pattern of the food matrix. Accordingly, the double edge of malnutrition, that involves deficiency as well as excess and materializes in many individuals throughout their life course, might be tackled by implementing sustainability, with the additional effect of overcoming global inequalities. Within this context SFA may regain their position of tasty and cheap sources of energy to be adapted to each individual lifestyle.

Background: The aim of this study was to investigate the relationship between high-risk genotypes of Human Papilloma Virus (HPV) and cancer of different subsites of the oral cavity. Material and methods: A pooled analysis of five studies included on the International Head and Neck Cancer Epidemiology (INHANCE) Consortium was conducted. HPV 16 and HPV 18 were considered. Adjusted odds ratios (ORs) and corresponding 95 % confidence intervals (CIs) for HPV and each oral cavity subsites were simultaneously estimated using multinomial logistic regression models. Results: The analysis included 1157 cases and 3272 controls. This study showed a slightly higher prevalence of HPV infection among oral cancer cases than controls. In particular, an increased risk of other and not otherwise specified (NOS) sites within the oral cavity, oral tongue, palate and floor of mouth cancer was observed for overall HPV16 positivity (OR = 1.66, 95 % CI: 1.01−2.72; OR = 1.97, 95 % CI: 1.36−2.85; OR = 2.48, 95 % CI: 1.50−4.11; OR = 2.71, 95 % CI: 1.06−6.95, respectively). In particular, HPV16E7 was related to cancer of floor of mouth, oral cavity NOS and palate (OR = 2.71, 95 % CI: 1.06−6.95; OR = 3.32, 95 % CI:1.53−7.19; OR = 3.34, 95 % CI:1.38−8.06). Results were inconsistent for HPV18 due to low prevalence of infection. Conclusion: Our study suggests that HPV16 infection may increase the risk of developing floor of mouth, gum, tongue, and palate cancers. Clinical relevance: Subjects with HPV infection have a higher risk of cancer from all sites of the oral cavity.

We conducted an umbrella review which synthetizes the findings of systematic reviews available in the literature that investigate the prognostic role of miRNAs as potential biomarkers in the field of tertiary prevention of head and neck Cancer (HNC). We selected systematic reviews in English related to HNC, with meta-analysis of observational studies that reported quantitative prognostic measures, hazard ratios (HRs), overall survival (OS) or disease-free survival (DFS). The methodological quality of the included reviews was assessed by using the AMSTAR-2 tool. The most reported miRNAs were the following: miRNA2, Let7 family and miR17, etc. Four out of six reviews particularly emphasized the link between miRNA21 expression and HNC patients. Re-cently the cumulative effects of sets of miRNAs have been increasingly studied and might be a stronger predictor of survival than single miRNA.

Introduction Gastric cancer (GC) is the fifth diagnosed cancer worldwide and the third leading cause of death for cancer. Recent reports suggest that metabolic syndrome (MetS) has a role in etiology, progression or prognosis on GC. The aim of this study is to systematically review the evidence on the association between MetS and GC risk and prognosis. Methods Literature search was performed using the electronic databases Pubmed, Web of Knowledge, Embase and Cinahl Complete until December 2019. Cohort and case-control studies were included. Study-specific association measures were pooled using a random-effect model. Results A total of 14 studies included in the qualitative synthesis of which nine were meta-analyzed. The majority were cohort studies (92%) and set in Asia (57%). The pooled analysis reported no association between MetS and GC risk [hazard ratio (HR) 1.05, 95% confidence interval (CI) 0.92-1.18; I2= 74.2%, P < 0.001], however when the analysis was stratified according to the geographic area and sex, Western women with MetS had an increased risk of GC (HR 1.24, 95% CI 1.05-1.47; I2= 4.6%, P = 0.351). We did not observe an increased risk of unfavorable prognosis for individuals with MetS (HR 1.23, 95% CI 0.25-6.08). Conclusion This systematic review and meta-analysis suggests that GC risk might be associated with MetS in women although larger studies are needed. Preventing and treating MetS, however, might have overall beneficial effect on several noncommunicable diseases and in this sense should be pursued.

Precision health requires citizens that are empowered to orient health decisions towards their personal values, aware of the benefits and risks, and committed to sharing their personal data to trustful institutions. Effective citizen engagement initiatives are fundamental for the success of a precision health approach. To provide an overview of citizen engagement initiatives in precision health in European Union (EU) member states. Scoping review. The electronic databases PubMed, Web of Science, CINAHL and Embase were searched to include articles published in English. Furthermore, desk research was conducted in English, Dutch, French, Italian and Spanish. Articles or reports regarding ongoing initiatives of citizen engagement in precision health conducted in EU member states and published from January 2015 to July 2020 were considered eligible. A quality assessment of the retrieved entries using Critical Appraisal Skills Programme tool was conducted. We identified nine documents, which reported eight ongoing citizen engagement initiatives, with substantial variability. Government agencies, non-governmental organisations and scientific societies were the main organisers and funders. Most of the initiatives were conducted in the UK. Genomics was the most emphasised aspect of precision health in these initiatives. Among the identified initiatives, both in-person and digital means were reported. Our work provides an overview of current citizen engagement initiatives in the EU that can be useful for stakeholders interested in designing and developing precision health projects enriched by meaningful citizen participation. CRD42020193866.

Head and neck squamous cell carcinoma (HNSCC), which includes cancers of the oral cavity and oropharynx, is a cause of substantial global morbidity and mortality. Strategies to reduce disease burden include discovery of novel therapies and repurposing of existing drugs. Statins are commonly prescribed for lowering circulating cholesterol by inhibiting HMG-CoA reductase (HMGCR). Results from some observational studies suggest that statin use may reduce HNSCC risk. We appraised the relationship of genetically-proxied cholesterol-lowering drug targets and other circulating lipid traits with oral (OC) and oropharyngeal (OPC) cancer risk using two-sample Mendelian randomization (MR). For the primary analysis, germline genetic variants in HMGCR, NPC1L1, CETP, PCSK9 and LDLR were used to proxy the effect of low-density lipoprotein cholesterol (LDL-C) lowering therapies. In secondary analyses, variants were used to proxy circulating levels of other lipid traits in a genome-wide association study (GWAS) meta-analysis of 188,578 individuals. Both primary and secondary analyses aimed to estimate the downstream causal effect of cholesterol lowering therapies on OC and OPC risk. The second sample for MR was taken from a GWAS of 6,034 OC and OPC cases and 6,585 controls (GAME-ON). Analyses were replicated in UK Biobank, using 839 OC and OPC cases and 372,016 controls and the results of the GAME-ON and UK Biobank analyses combined in a fixed-effects meta-analysis. We found limited evidence of a causal effect of genetically-proxied LDL-C lowering using HMGCR, NPC1L1, CETP or other circulating lipid traits on either OC or OPC risk. Genetically-proxied PCSK9 inhibition equivalent to a 1 mmol/L (38.7 mg/dL) reduction in LDL-C was associated with an increased risk of OC and OPC combined (OR 1.8 95%CI 1.2, 2.8, p = 9.31 x10-05), with good concordance between GAME-ON and UK Biobank (I2 = 22%). Effects for PCSK9 appeared stronger in relation to OPC (OR 2.6 95%CI 1.4, 4.9) than OC (OR 1.4

The continuous development and use of genomic sequencing requires healthcare professionals to constantly integrate these advancements into their clinical practice. There is a documented lack of cancer genomics contents in the teaching and learning programs. We aimed to identify the core competencies in cancer genomics for non-genetic healthcare professionals. We performed a literature review in PubMed, SCOPUS, and Web of Science databases to retrieve articles published from 2000 to 2018, in English or Italian language. We included articles that reported the competencies for non-genetic healthcare professionals in cancer genomics. A web-based modified Delphi survey was conducted, aiming to define, through consensus, a set of core competencies that should be covered in the curricula. The international expert panel included specialists in genetics, genomics, oncology, and medical specialists. In the literature review, we retrieved nine articles, from which we identified core competencies for general physicians and nurses. The competencies were organized in three main domains: knowledge, attitudes, and practical abilities. In the second round of Delphi survey, consensus of 83.3% was reached for the definition of the core competencies. Thirty-seven items were defined as the competencies required for physicians and forty-two items for nurses. Through a consensus-based approach, a set of core competencies in cancer genomics for non-genetic healthcare professionals has been identified. Our findings could benchmark standards for curriculum development and future educational strategies.

[This corrects the article DOI: 10.1155/2020/2291759.].

Background: The rapid spread of personalized medicine requires professionals to manage the “omics revolution.” Therefore, the genetics/genomics literacy of healthcare professionals should be in line with the continuous advances in this field, in order to implement its potential implications for diagnosis, control and treatment of diseases. The present study investigates the effectiveness of a distance learning course on genetics and genomics targeted at medical doctors. Methods: In the context of a project funded by the Italian Ministry of Health, we developed a distance learning course, entitled Genetics and Genomics practice. The course focused on genetic/genomics testing, pharmacogenetics and oncogenomics and was developed according to andragogical training methods (Problem-based Learning and Case-based Learning). We used a pre-test vs. post-test study design to assess knowledge improvement on a set of 10 Multiple Choice Questions (MCQs). We analyzed the proportion of correct answers for each question pre and post-test and the mean score difference stratified by gender, age, professional status and medical discipline. Moreover, the test was submitted to the participants 8 months after the conclusion of the course (follow-up), in order to assess the retained knowledge. Results: The course was completed by 1,637 Italian physicians, most of which were primary care physicians (20.8%), public health professionals (11.5%) and specialist pediatricians (10.6%). The proportion of correct answers increased in the post-test for all the MCQs. The overall mean score significantly increased, from 59.46 in the pre-test to 71.42 in the post-test (p < 0.0001). The comparison in test performance between follow-up and pre-test demonstrated an overall knowledge improvement. Conclusion: Genomics literacy among healthcare professionals is essential to ensure optimal translation to healthcare delivery of research. The results of this course suggest that distance-learning training in

Pancreatic neuroendocrine tumors (PanNETs) display variable aggressive behavior. A major predictor of survival is tumor grade based on the Ki67 proliferation index. As information on transcriptomic profiles of PanNETs with different tumor grades is limited, we investigated 29 PanNETs (17 G1, 7 G2, 5 G3) for their expression profiles, mutations in 16 PanNET relevant genes and LINE‐1 DNA methylation profiles. A total of 3050 genes were differentially expressed between tumors with different grades (p < 0.05): 1279 in G3 vs. G2; 2757 in G3 vs. G1; and 203 in G2 vs. G1. Mutational analysis showed 57 alterations in 11 genes, the most frequent being MEN1 (18/29), DAXX (7/29), ATRX (6/29) and MUTYH (5/29). The presence and type of mutations did not correlate with the specific expression profiles associated with different grades. LINE‐1 showed significantly lower methylation in G2/G3 versus G1 tumors (p = 0.007). The expression profiles of matched primaries and metastasis (nodal, hepatic and colorectal wall) of three cases confirmed the role of Ki67 in defining specific expression profiles, which clustered according to tumor grades, independently from anatomic location or patient of origin. Such data call for future exploration of the role of Ki67 in tumor progression, given its involvement in chromosomal stability.

"Integrating China in the International Consortium for Personalized Medicine"(IC2PerMed) is a coordination and support action funded within the Horizon 2020 work program. Following the guidance of the International Consortium for Personalized Medicine (ICPerMed), the project's overarching aim is to align the European Union and China's research agendas in the field of personalized medicine (PM) to enable a swift development of PM approaches in the EU with strong leverage upon EU-Chinese collaboration. Living in the CO-VID-19 era, we are witnessing how the challenges imposed by the pandemic all around the globe have been acting as a catalyst for collaborations and knowledge sharing among national health systems worldwide. Given the strong interest on behalf of both Europe and China in the advancement of PM approaches, now more than ever, a cross-border collaboration between the 2 powers can accelerate the effective translation of such innovation to healthcare systems, advance research, and ensure that such change follows the directions toward the path of sustainability. IC2PerMed developments will be led by European and Chinese experts equally assembled into 3 Working Groups: (1) people and organization, (2) innovation and market, and (3) research and clinical studies in PM. This complex and dynamic network of actions thrives on dialog, cooperation, and alignment of research at national and global levels; work in the direction taken by IC2PerMed shall pave the way toward the realization of PM's full potential, prevent it from becoming a burden for healthcare systems, and, rather, prove that it provides an essential and irreplaceable contribution to their effectiveness, efficiency, and sustainability.

The development of high-throughput omics technologies represents an unmissable opportunity for evidence-based prevention of adverse effects on human health. However, the applicability and access to multi-omics tests are limited. In Italy, this is due to the rapid increase of knowledge and the high levels of skill and economic investment initially necessary. The fields of human genetics and public health have highlighted the relevance of an implementation strategy at a national level in Italy, including integration in sanitary regulations and governance instruments. In this review, the emerging field of public health genomics is discussed, including the polygenic scores approach, epigenetic modulation, nutrigenomics, and microbiomes implications. Moreover, the Italian state of implementation is presented. The omics sciences have important implications for the prevention of both communicable and noncommunicable diseases, especially because they can be used to assess the health status during the whole course of life. An effective population health gain is possible if omics tools are implemented for each person after a preliminary assessment of effectiveness in the medium to long term.

Background: Italy was the first European country to implement a national lockdown because of the COVID-19 pandemic. Worldwide, this pandemic had a huge impact on the mental health of people in many countries causing similar reaction in terms of emotions and concerns at the population level. Our study investigated the impact of the COVID-19 pandemic on psychological well-being in a cohort of Italian university students. Methods: We conducted a cross-sectional survey in the period immediately after the first lockdown through the administration of a questionnaire on the personal websites of students attending their undergraduate courses at the Università Cattolica del Sacro Cuore. We used the Patient-Health-Engagement-Scale, Self-Rating-Anxiety-Scale, and Self-Rating-Depression-Scale to assess engagement, anxiety symptoms, and depression symptoms of our sample. Results: The sample size was 501 subjects, of which 35.33% were classified as anxious and 72.93% as depressed. Over 90% of respondents had good understanding of the preventive measures despite over 70% suffered from the impossibility of physically seeing friends and partners. Around 55% of students would have been willing to contribute much more to face the pandemic. An increase in the occurrences of anxiety was associated with being female, being student of the Rome campus, suffering from the impossibility of attending university, being distant from colleagues, and being unable of physically seeing one’s partner. Performing physical activity reduced this likelihood. Conclusion: University students are at risk of psychological distress in the case of traumatic events. The evolution of the pandemic is uncertain and may have long-term effects on mental health. Therefore, it is crucial to study the most effective interventions to identify vulnerable subgroups and to plan for acute and long-term psychological services to control and reduce the burden of psychological problems.

Squamous cell carcinomas (SqCC) of the aerodigestive tract have similar etiological risk factors. Although genetic risk variants for individual cancers have been identified, an agnostic, genome-wide search for shared genetic susceptibility has not been performed. To identify novel and pleotropic SqCC risk variants, we performed a meta-analysis of GWAS data on lung SqCC (LuSqCC), oro/pharyngeal SqCC (OSqCC), laryngeal SqCC (LaSqCC) and esophageal SqCC (ESqCC) cancers, totaling 13,887 cases and 61,961 controls of European ancestry. We identified one novel genome-wide significant (Pmeta<5x10-8) aerodigestive SqCC susceptibility loci in the 2q33.1 region (rs56321285, TMEM273). Additionally, three previously unknown loci reached suggestive significance (Pmeta<5x10-7): 1q32.1 (rs12133735, near MDM4), 5q31.2 (rs13181561, TMEM173) and 19p13.11 (rs61494113, ABHD8). Multiple previously identified loci for aerodigestive SqCC also showed evidence of pleiotropy in at least another SqCC site, these include: 4q23 (ADH1B), 6p21.33 (STK19), 6p21.32 (HLA-DQB1), 9p21.33 (CDKN2B-AS1) and 13q13.1(BRCA2). Gene-based association and gene set enrichment identified a set of 48 SqCC-related genes to DNA damage and epigenetic regulation pathways. Our study highlights the importance of cross-cancer analyses to identify pleiotropic risk loci of histology-related cancers arising at distinct anatomical sites.

Objective: To summarize the latest evidence on head and neck cancer epidemiology from the International Head and Neck Cancer Epidemiology (INHANCE) consortium. Subjects and Methods: INHANCE was established in 2004 to elucidate the etiology of head and neck cancer through pooled analyses of individual-level data on a large scale. We summarize results from recent INHANCE-based publications updating our 2015 overview. Results: Seventeen papers were published between 2015 and May 2020. These studies further define the nature of risks associated with tobacco and alcohol, and occupational exposures on head and neck cancer. The beneficial effects on incidence of head and neck cancer were identified for good oral health, endogenous and exogenous hormonal factors, and selected aspects of diet related to fruit and vegetables. INHANCE has begun to develop risk prediction models and to pool follow-up data on their studies, finding that ~30% of cases had cancer recurrence and 9% second primary cancers, with overall- and disease-specific 5-year-survival of 51% and 57%, respectively. Conclusions: The number and importance of INHANCE scientific findings provides further evidence of the advantages of large-scale internationally collaborative projects and will support the development of prevention strategies.

Background: Europe overall suffered greatly in the early stages of the COVID-19 pandemic but the impact of different countries varied. Italy was in the forefront, but there too there were differences, with the Lombardy region the epicentre of the pandemic. Methods: We report Crude Mortality Rates (CMRs) from deaths reported as due to COVID-19 and, in five countries where age-specific data are available, Standardized Mortality Rates (SMRs) in the European Union and United Kingdom. Results: As of 30th August 2020, Belgium was the country with the highest cumulative CMR (86.3/100,000), but the Lombardy region reached almost double this figure (167.6/100,000), far ahead of the corresponding figure for the rest of Italy at 37.0/100,000. SMRs could be calculated for five countries (Italy, Portugal, Sweden, Germany, and Netherlands). Among them, Sweden had the highest SMR (61.6/100,000). The corresponding figures for Italy, Netherlands, Portugal and Germany were 50.2, 41.4, 15.9, and 10.1 per 100,000, respectively. Conclusion: It is clear that countries within Europe have performed very differently in their responses to the COVID-19 pandemic, but the many limitations in the available data must be addressed before a definitive assessment of the reasons for these differences can be made.