A Multimorbidity Analysis of Hospitalized Patients With COVID-19 in Northwest Italy: Longitudinal Study Using Evolutionary Machine Learning and Health Administrative Data.

BACKGROUND: Multimorbidity is a significant public health concern, characterized by the coexistence and interaction of multiple preexisting medical conditions. This complex condition has been associated with an increased risk of COVID-19. Individuals with multimorbidity who contract COVID-19 often face a significant reduction in life expectancy. The postpandemic period has also highlighted an increase in frailty, emphasizing the importance of integrating existing multimorbidity details into epidemiological risk assessments. Managing clinical data that include medical histories presents significant challenges, particularly due to the sparsity of data arising from the rarity of multimorbidity conditions. Also, the complex enumeration of combinatorial multimorbidity features introduces challenges associated with combinatorial explosions. OBJECTIVE: This study aims to assess the severity of COVID-19 in individuals with multiple medical conditions, considering their demographic characteristics such as age and sex. We propose an evolutionary machine learning model designed to handle sparsity, analyzing preexisting multimorbidity profiles of patients hospitalized with COVID-19 based on their medical history. Our objective is to identify the optimal set of multimorbidity feature combinations strongly associated with COVID-19 severity. We also apply the Apriori algorithm to these evolutionarily derived predictive feature combinations to identify those with high support. METHODS: We used data from 3 administrative sources in Piedmont, Italy, involving 12,793 individuals aged 45-74 years who tested positive for COVID-19 between February and May 2020. From their 5-year pre-COVID-19 medical histories, we extracted multimorbidity features, including drug prescriptions, disease diagnoses, sex, and age. Focusing on COVID-19 hospitalization, we segmented the data into 4 cohorts based on age and sex. Addressing data imbalance through random resampling, we compared various machine learning algorithms to identify the optimal classification model for our evolutionary approach. Using 5-fold cross-validation, we evaluated each model's performance. Our evolutionary algorithm, utilizing a deep learning classifier, generated prediction-based fitness scores to pinpoint multimorbidity combinations associated with COVID-19 hospitalization risk. Eventually, the Apriori algorithm was applied to identify frequent combinations with high support. RESULTS: We identified multimorbidity predictors associated with COVID-19 hospitalization, indicating more severe COVID-19 outcomes. Frequently occurring morbidity features in the final evolved combinations were age>53, R03BA (glucocorticoid inhalants), and N03AX (other antiepileptics) in cohort 1; A10BA (biguanide or metformin) and N02BE (anilides) in cohort 2; N02AX (other opioids) and M04AA (preparations inhibiting uric acid production) in cohort 3; and G04CA (Alpha-adrenoreceptor antagonists) in cohort 4. CONCLUSIONS: When combined with other multimorbidity features, even less prevalent medical conditions show associations with the outcome. This study provides insights beyond COVID-19, demonstrating how repurposed administrative data can be adapted and contribute to enhanced risk assessment for vulnerable populations.

[The physical activity paradox.] / Il paradosso dell'attività fisica.

Recent discoveries have shown that the effects of physical activity on health are not the same in all its domains. In particular, the health effects of physical activity differ not only in terms of modality and intensity, but also based on the context in which it is carried out. Several studies have observed that those who do a lot of physical activity at work tend to have worse health outcomes than those who do less physical activity at work but more exercise in their free time. This phenomenon has been defined as the "physical activity paradox". However, it is worth reporting that differences in health outcomes have been observed for different socioeconomic positions and that more favorable socioeconomic positions tend to have healthier lifestyles.

Contextual and individual inequalities in breast cancer screening participation and outcomes in Turin (North-West Italy).

Breast cancer incidence and screening participation exhibit an unequal distribution in the population. This study aims to investigate the impact of socioeconomic position (SEP) on three breast screening indicators (participation, recall, and cancer detection rates) among women aged 50-69 in the city of Turin between 2010 and 2019. The study also aims to determine whether contextual factors (deprivation index) or individual factors (educational level) have a greater influence. The data used in this study are sourced from the Turin Breast Screening Program (TBSP) and the Turin Longitudinal Study (TLS). To test the hypothesis and account for the hierarchical structure of the data, multilevel models were used. Both contextual and individual SEP were found to be associated with screening participation. Participation increased with higher levels of deprivation (odds ratio for most deprived: 1.13; 95% CI 1.11-1.16) and decreased with higher educational levels (OR for low educated: 1.37; 95% CI 1.34-1.40). Contextual SEP did not show any association with recall or cancer detection rates, but individual SEP had an impact. Women with lower educational levels had a statistically significant 19% lower odds of being recalled and a statistically significant 20% lower odds of being diagnosed with cancer. Additionally, immigrant women were less likely to participate in screening, be recalled, or receive a cancer diagnosis. Educational level consistently influenced the analyzed screening indicators, while contextual deprivation appeared to have less importance. It is likely that women living in less deprived areas and with higher education have greater access to opportunistic screening.

Healthy lifestyle change and all-cause and cancer mortality in the European Prospective Investigation into Cancer and Nutrition cohort.

BACKGROUND: Healthy lifestyles are inversely associated with the risk of noncommunicable diseases, which are leading causes of death. However, few studies have used longitudinal data to assess the impact of changing lifestyle behaviours on all-cause and cancer mortality. METHODS: Within the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort, lifestyle profiles of 308,497 cancer-free adults (71% female) aged 35-70 years at recruitment across nine countries were assessed with baseline and follow-up questionnaires administered on average of 7 years apart. A healthy lifestyle index (HLI), assessed at two time points, combined information on smoking status, alcohol intake, body mass index, and physical activity, and ranged from 0 to 16 units. A change score was calculated as the difference between HLI at baseline and follow-up. Associations between HLI change and all-cause and cancer mortality were modelled with Cox regression, and the impact of changing HLI on accelerating mortality rate was estimated by rate advancement periods (RAP, in years). RESULTS: After the follow-up questionnaire, participants were followed for an average of 9.9 years, with 21,696 deaths (8407 cancer deaths) documented. Compared to participants whose HLIs remained stable (within one unit), improving HLI by more than one unit was inversely associated with all-cause and cancer mortality (hazard ratio [HR]: 0.84; 95% confidence interval [CI]: 0.81, 0.88; and HR: 0.87; 95% CI: 0.82, 0.92; respectively), while worsening HLI by more than one unit was associated with an increase in mortality (all-cause mortality HR: 1.26; 95% CI: 1.20, 1.33; cancer mortality HR: 1.19; 95% CI: 1.09, 1.29). Participants who worsened HLI by more than one advanced their risk of death by 1.62 (1.44, 1.96) years, while participants who improved HLI by the same amount delayed their risk of death by 1.19 (0.65, 2.32) years, compared to those with stable HLI. CONCLUSIONS: Making healthier lifestyle changes during adulthood was inversely associated with all-cause and cancer mortality and delayed risk of death. Conversely, making unhealthier lifestyle changes was positively associated with mortality and an accelerated risk of death.

The impact of COVID-19 pandemic on gambling: A systematic review.

BACKGROUND AND AIMS: Since the COVID-19 outbreak, people's habits changed radically. In fact, to limit the spread of SARS-CoV-2, governments implemented restrictive measures that influenced the lives of individuals. The aim of this systematic review is to analyze the impact of COVID-19 on gambling by examining three different outcomes: frequency, expenditure, and transition among possible types of gambling. METHODS: All studies assessing the impact of restrictive measures implemented to limit the spread of SARS-CoV-2 on gambling were included. For the search, two different databases were used: Pubmed and CINAHL. Moreover, two different populations were analyzed: the general population, and subjects who used to gamble before SARS-CoV-2 pandemic. All qualitative studies, reports not based on peer-review, and papers in which the statistical unit was not the subject but the gambling or wagering operators were excluded. RESULTS: From the search, 408 reports were identified. Of these, 28 were included in the systematic review. From the studies, a strong reduction in the frequency and expenditure of land-based gambling emerged, while the results about online gambling were different among the studies. However, a reduction was observed assessing sports betting, and an increase emerged considering online casino and skill games. Finally, a significant migration from land-based gambling to online platforms was identified. The main reasons for these findings were the physical closures of land-based gambling venues and the more time spent at home, the suspension or cancelation of sporting events on which subjects used to bet, and more mental health issues during this challenging period. CONCLUSIONS: The COVID-19 pandemic greatly affected subjects' habits, including gambling, by reducing land-based gambling and sports betting, and increasing gambling on online platforms. This shift poses significant challenges, requiring a comprehensive approach to monitor and mitigate the negative consequences of this increase in online gambling caused by the pandemic.

Adherence to Diet Quality Indices and Breast Cancer Risk in the Italian ORDET Cohort.

Breast cancer (BC) is the most common cancer in women, with 2.3 million diagnoses in 2020. There is growing evidence that lifestyle factors, including dietary factors, particularly the complex interactions and synergies between different foods and nutrients (and not a single nutrient or food), may be associated with a higher risk of BC. The aim of this work was to evaluate how the Italian Mediterranean Index (IMI), the Greek Mediterranean Index, the DASH score, and the EAT-Lancet score can help lower the risk of BC, and analyze if chronic low-grade inflammation may be one of the possible mechanisms through which dietary patterns influence breast cancer risk. We evaluated the effect of adherence to these four dietary quality indices in the 9144 women of the ORDET cohort who completed a dietary questionnaire. The effect of adherence to dietary patterns on chronic inflammation biomarkers was evaluated on a subsample of 552 participants. Hazard ratios (HRs) with 95% confidence intervals (CIs) for BC risk in relation to the index score categories used were estimated using multivariable Cox models adjusted for potential confounders. Regression coefficients (ß), with 95% CI for C-reactive protein (CRP), TNF-α, IL-6, leptin, and adiponectin levels in relation to adherence to dietary patterns were evaluated with the linear regression model adjusted for potential confounders. IMI was inversely associated with BC in all women (HR: 0.76, 95% CI: 0.60-0.97, P trend = 0.04), particularly among postmenopausal women (HR: 0.64, 95% CI: 0.42-0.98, P trend = 0.11). None of the other dietary patterns was associated with BC risk. Higher IMI and Greek Mediterranean Index scores were inversely associated with circulating CRP (ß: -0.10, 95% CI: -0.18, -0.02, and ß: -0.13, 95% CI: -0.21, -0.04). The higher score of the EAT-Lancet Index was instead associated with a higher concentration of circulating levels of CRP (ß: 0.10, 95% CI: 0.02, 0.18). In conclusion, these results suggest that adherence to a typical Italian Mediterranean diet protects against BC development, especially among postmenopausal women, possibly through modulation of chronic low-grade inflammation.

Multimorbidity in middle-aged women and COVID-19: binary data clustering for unsupervised binning of rare multimorbidity features and predictive modeling.

BACKGROUND: Multimorbidity is typically associated with deficient health-related quality of life in mid-life, and the likelihood of developing multimorbidity in women is elevated. We address the issue of data sparsity in non-prevalent features by clustering the binary data of various rare medical conditions in a cohort of middle-aged women. This study aims to enhance understanding of how multimorbidity affects COVID-19 severity by clustering rare medical conditions and combining them with prevalent features for predictive modeling. The insights gained can guide the development of targeted interventions and improved management strategies for individuals with multiple health conditions. METHODS: The study focuses on a cohort of 4477 female patients, (aged 45-60) in Piedmont, Italy, and utilizes their multimorbidity data prior to the COVID-19 pandemic from their medical history from 2015 to 2019. The COVID-19 severity is determined by the hospitalization status of the patients from February to May 2020. Each patient profile in the dataset is depicted as a binary vector, where each feature denotes the presence or absence of a specific multimorbidity condition. By clustering the sparse medical data, newly engineered features are generated as a bin of features, and they are combined with the prevalent features for COVID-19 severity predictive modeling. RESULTS: From sparse data consisting of 174 input features, we have created a low-dimensional feature matrix of 17 features. Machine Learning algorithms are applied to the reduced sparsity-free data to predict the Covid-19 hospital admission outcome. The performance obtained for the corresponding models are as follows: Logistic Regression (accuracy 0.72, AUC 0.77, F1-score 0.69), Linear Discriminant Analysis (accuracy 0.7, AUC 0.77, F1-score 0.67), and Ada Boost (accuracy 0.7, AUC 0.77, F1-score 0.68). CONCLUSION: Mapping higher-dimensional data to a low-dimensional space can result in information loss, but reducing sparsity can be beneficial for Machine Learning modeling due to improved predictive ability. In this study, we addressed the issue of data sparsity in electronic health records and created a model that incorporates both prevalent and rare medical conditions, leading to more accurate and effective predictive modeling. The identification of complex associations between multimorbidity and the severity of COVID-19 highlights potential areas of focus for future research, including long COVID and intervention efforts.

Hypertension and Risk of Endometrial Cancer: A Pooled Analysis in the Epidemiology of Endometrial Cancer Consortium (E2C2).

BACKGROUND: The incidence rates of endometrial cancer are increasing, which may partly be explained by the rising prevalence of obesity, an established risk factor for endometrial cancer. Hypertension, another component of metabolic syndrome, is also increasing in prevalence, and emerging evidence suggests that it may be associated with the development of certain cancers. The role of hypertension independent of other components of metabolic syndrome in the etiology of endometrial cancer remains unclear. In this study, we evaluated hypertension as an independent risk factor for endometrial cancer and whether this association is modified by other established risk factors. METHODS: We included 15,631 endometrial cancer cases and 42,239 controls matched on age, race, and study-specific factors from 29 studies in the Epidemiology of Endometrial Cancer Consortium. We used multivariable unconditional logistic regression models to estimate ORs and 95% confidence intervals (CI) to evaluate the association between hypertension and endometrial cancer and whether this association differed by study design, race/ethnicity, body mass index, diabetes status, smoking status, or reproductive factors. RESULTS: Hypertension was associated with an increased risk of endometrial cancer (OR, 1.14; 95% CI, 1.09-1.19). There was significant heterogeneity by study design (Phet < 0.01), with a stronger magnitude of association observed among case-control versus cohort studies. Stronger associations were also noted for pre-/perimenopausal women and never users of postmenopausal hormone therapy. CONCLUSIONS: Hypertension is associated with endometrial cancer risk independently from known risk factors. Future research should focus on biologic mechanisms underlying this association. IMPACT: This study provides evidence that hypertension may be an independent risk factor for endometrial cancer.

Lifestyle changes in middle age and risk of cancer: evidence from the European Prospective Investigation into Cancer and Nutrition.

In this study, we aimed to provide novel evidence on the impact of changing lifestyle habits on cancer risk. In the EPIC cohort, 295,865 middle-aged participants returned a lifestyle questionnaire at baseline and during follow-up. At both timepoints, we calculated a healthy lifestyle index (HLI) score based on cigarette smoking, alcohol consumption, body mass index and physical activity. HLI ranged from 0 (most unfavourable) to 16 (most favourable). We estimated the association between HLI change and risk of lifestyle-related cancers-including cancer of the breast, lung, colorectum, stomach, liver, cervix, oesophagus, bladder, and others-using Cox regression models. We reported hazard ratios (HR) with 95% confidence intervals (CI). Median time between the two questionnaires was 5.7 years, median age at follow-up questionnaire was 59 years. After the follow-up questionnaire, we observed 14,933 lifestyle-related cancers over a median follow-up of 7.8 years. Each unit increase in the HLI score was associated with 4% lower risk of lifestyle-related cancers (HR 0.96; 95%CI 0.95-0.97). Among participants in the top HLI third at baseline (HLI > 11), those in the bottom third at follow-up (HLI ≤ 9) had 21% higher risk of lifestyle-related cancers (HR 1.21; 95%CI 1.07-1.37) than those remaining in the top third. Among participants in the bottom HLI third at baseline, those in the top third at follow-up had 25% lower risk of lifestyle-related cancers (HR 0.75; 95%CI 0.65-0.86) than those remaining in the bottom third. These results indicate that lifestyle changes in middle age may have a significant impact on cancer risk.

International Pooled Analysis of Leisure-Time Physical Activity and Premenopausal Breast Cancer in Women From 19 Cohorts.

PURPOSE: There is strong evidence that leisure-time physical activity is protective against postmenopausal breast cancer risk but the association with premenopausal breast cancer is less clear. The purpose of this study was to examine the association of physical activity with the risk of developing premenopausal breast cancer. METHODS: We pooled individual-level data on self-reported leisure-time physical activity across 19 cohort studies comprising 547,601 premenopausal women, with 10,231 incident cases of breast cancer. Multivariable Cox regression was used to estimate hazard ratios (HRs) and 95% CIs for associations of leisure-time physical activity with breast cancer incidence. HRs for high versus low levels of activity were based on a comparison of risk at the 90th versus 10th percentiles of activity. We assessed the linearity of the relationship and examined subtype-specific associations and effect modification across strata of breast cancer risk factors, including adiposity. RESULTS: Over a median 11.5 years of follow-up (IQR, 8.0-16.1 years), high versus low levels of leisure-time physical activity were associated with a 6% (HR, 0.94 [95% CI, 0.89 to 0.99]) and a 10% (HR, 0.90 [95% CI, 0.85 to 0.95]) reduction in breast cancer risk, before and after adjustment for BMI, respectively. Tests of nonlinearity suggested an approximately linear relationship (Pnonlinearity = .94). The inverse association was particularly strong for human epidermal growth factor receptor 2-enriched breast cancer (HR, 0.57 [95% CI, 0.39 to 0.84]; Phet = .07). Associations did not vary significantly across strata of breast cancer risk factors, including subgroups of adiposity. CONCLUSION: This large, pooled analysis of cohort studies adds to evidence that engagement in higher levels of leisure-time physical activity may lead to reduced premenopausal breast cancer risk.

Consumption of ultra-processed foods and risk of multimorbidity of cancer and cardiometabolic diseases: a multinational cohort study.

Background: It is currently unknown whether ultra-processed foods (UPFs) consumption is associated with a higher incidence of multimorbidity. We examined the relationship of total and subgroup consumption of UPFs with the risk of multimorbidity defined as the co-occurrence of at least two chronic diseases in an individual among first cancer at any site, cardiovascular disease, and type 2 diabetes. Methods: This was a prospective cohort study including 266,666 participants (60% women) free of cancer, cardiovascular disease, and type 2 diabetes at recruitment from seven European countries in the European Prospective Investigation into Cancer and Nutrition (EPIC) study. Foods and drinks consumed over the previous 12 months were assessed at baseline by food-frequency questionnaires and classified according to their degree of processing using Nova classification. We used multistate modelling based on Cox regression to estimate cause-specific hazard ratios (HR) and their 95% confidence intervals (CI) for associations of total and subgroups of UPFs with the risk of multimorbidity of cancer and cardiometabolic diseases. Findings: After a median of 11.2 years of follow-up, 4461 participants (39% women) developed multimorbidity of cancer and cardiometabolic diseases. Higher UPF consumption (per 1 standard deviation increment, ∼260 g/day without alcoholic drinks) was associated with an increased risk of multimorbidity of cancer and cardiometabolic diseases (HR: 1.09, 95% CI: 1.05, 1.12). Among UPF subgroups, associations were most notable for animal-based products (HR: 1.09, 95% CI: 1.05, 1.12), and artificially and sugar-sweetened beverages (HR: 1.09, 95% CI: 1.06, 1.12). Other subgroups such as ultra-processed breads and cereals (HR: 0.97, 95% CI: 0.94, 1.00) or plant-based alternatives (HR: 0.97, 95% CI: 0.91, 1.02) were not associated with risk. Interpretation: Our findings suggest that higher consumption of UPFs increases the risk of cancer and cardiometabolic multimorbidity. Funding: Austrian Academy of Sciences, Fondation de France, Cancer Research UK, World Cancer Research Fund International, and the Institut National du Cancer.

Prediagnostic selenium status, selenoprotein gene variants and association with breast cancer risk in a European cohort study.

Selenium (Se) may help prevent breast cancer (BC) development. Owing to limited observational evidence, we investigated whether prediagnostic Se status and/or variants in the selenoprotein genes are associated with BC risk in a large European cohort. Se status was assessed by plasma measures of Se and its major circulating proteins, selenoprotein P (SELENOP) and glutathione peroxidase 3 (GPX3), in matched BC case-control pairs (2208 for SELENOP; 1785 for GPX3 and Se) nested within the European Prospective Investigation into Cancer and Nutrition (EPIC). Single nucleotide polymorphisms (SNPs, n = 452) in 55 selenoprotein and Se metabolic pathway genes and an additional 18 variants previously associated with Se concentrations were extracted from existing genotyping data within EPIC for 1564 case-control pairs. Multivariable-adjusted logistic regression models were used to calculate the odds ratios (ORs) and 95 % confidence intervals (CIs) of the association between Se status markers, SNP variants and BC risk. Overall, there was no statistically significant association of Se status with BC risk. However, higher GPX3 activity was associated with lower risk of premenopausal BC (4th versus 1st quartile, OR = 0.54, 95 % CI: 0.30-0.98, Ptrend = 0.013). While none of the genetic variant associations (P ≤ 0.05) retained significance after multiple testing correction, rs1004243 in the SELENOM selenoprotein gene and two SNPs in the related antioxidant TXN2 gene (rs4821494 and rs5750261) were associated with respective lower and higher risks of BC at a significance threshold of P ≤ 0.01. Fourteen SNPs in twelve Se pathway genes (P ≤ 0.01) in interaction with Se status were also associated with BC risk. Higher Se status does not appear to be associated with BC risk, although activity of the selenoenzyme GPX3 may be inversely associated with premenopausal BC risk, and SNPs in the Se pathway alone or in combination with suboptimal Se status may influence BC risk.

Body mass index and cancer risk among adults with and without cardiometabolic diseases: evidence from the EPIC and UK Biobank prospective cohort studies.

BACKGROUND: Whether cancer risk associated with a higher body mass index (BMI), a surrogate measure of adiposity, differs among adults with and without cardiovascular diseases (CVD) and/or type 2 diabetes (T2D) is unclear. The primary aim of this study was to evaluate separate and joint associations of BMI and CVD/T2D with the risk of cancer. METHODS: This is an individual participant data meta-analysis of two prospective cohort studies, the UK Biobank (UKB) and the European Prospective Investigation into Cancer and nutrition (EPIC), with a total of 577,343 adults, free of cancer, T2D, and CVD at recruitment. We used Cox proportional hazard regressions to estimate multivariable-adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) for associations between BMI and incidence of obesity-related cancer and in turn overall cancer with a multiplicative interaction between BMI and the two cardiometabolic diseases (CMD). HRs and 95% CIs for separate and joint associations for categories of overweight/obesity and CMD status were estimated, and additive interaction was quantified through relative excess risk due to interaction (RERI). RESULTS: In the meta-analysis of both cohorts, BMI (per ~ 5 kg/m2) was positively associated with the risk of obesity-related cancer among participants without a CMD (HR: 1.11, 95%CI: 1.07,1.16), among participants with T2D (HR: 1.11, 95% CI: 1.05,1.18), among participants with CVD (HR: 1.17, 95% CI: 1.11,1.24), and suggestively positive among those with both T2D and CVD (HR: 1.09, 95% CI: 0.94,1.25). An additive interaction between obesity (BMI ≥ 30 kg/m2) and CVD with the risk of overall cancer translated into a meta-analytical RERI of 0.28 (95% CI: 0.09-0.47). CONCLUSIONS: Irrespective of CMD status, higher BMI increased the risk of obesity-related cancer among European adults. The additive interaction between obesity and CVD suggests that obesity prevention would translate into a greater cancer risk reduction among population groups with CVD than among the general population.

Identifying MicroRNAs Suitable for Detection of Breast Cancer: A Systematic Review of Discovery Phases Studies on MicroRNA Expression Profiles.

The analysis of circulating tumor cells and tumor-derived materials, such as circulating tumor DNA, circulating miRNAs (cfmiRNAs), and extracellular vehicles provides crucial information in cancer research. CfmiRNAs, a group of short noncoding regulatory RNAs, have gained attention as diagnostic and prognostic biomarkers. This review focuses on the discovery phases of cfmiRNA studies in breast cancer patients, aiming to identify altered cfmiRNA levels compared to healthy controls. A systematic literature search was conducted, resulting in 16 eligible publications. The studies included a total of 585 breast cancer cases and 496 healthy controls, with diverse sample types and different cfmiRNA assay panels. Several cfmiRNAs, including MIR16, MIR191, MIR484, MIR106a, and MIR193b, showed differential expressions between breast cancer cases and healthy controls. However, the studies had a high risk of bias and lacked standardized protocols. The findings highlight the need for robust study designs, standardized procedures, and larger sample sizes in discovery phase studies. Furthermore, the identified cfmiRNAs can serve as potential candidates for further validation studies in different populations. Improving the design and implementation of cfmiRNA research in liquid biopsies may enhance their clinical diagnostic utility in breast cancer patients.

Predictors of Condom Use Among Youth of the Rural Tigray, Northern Ethiopia: Community-Based Cross-Sectional Study.

Background: Condom is one of the most commonly used and cost-effective HIV preventive measures, particularly in low-income countries. Despite the proven effect of condoms for STI/HIV prevention, there are limited data on its utilization. Hence, this community-based study aimed to assess the level and determinant factors of condom utilization among the youth of the rural Tigray. Methods: This study was part of a large community-based cross-sectional study conducted to assess the utilization of adolescent and youth-friendly health services among randomly selected 631 youth aged 15-24 years from May 23 to June 30, 2018. We used 273 youth who reported having a history of sexual activity during the study period. The data were collected using an interviewer-administered structured questionnaire. Logistic regression analysis was used to determine the independent predictors of the outcome variable and the level of significance was declared at a P-value of <0.05. Results: A total of 273 participants were included in the study. The mean age (+SD) of the respondents was 19.14 (±2.74) years. Only one-third (35.2%) of the respondents used a condom during their last sexual encounter and 51 (53.1%) of them used it consistently. Being married (AOR = 0.17; 95% CI: 0.04, 0.60), respondent's partner attained primary education (AOR = 0.14; 95% CI: 0.04, 0.50), and having multiple sexual partners (AOR = 6.97; 95% CI: 2.09, 23.20) were found to be the determinants of condom utilization. Conclusion: The study participants had a low level of condom utilization. Social and sexual related factors were the major predictors of condom use among the youth. Therefore, focused interventions need to be designed specifically to strengthen condom promotion campaigns.

Exploratory Genome-Wide Association Analysis to Identify Pharmacogenetic Determinants of Response to R-CHOP in Diffuse Large B-Cell Lymphoma.

R-CHOP standard chemotherapy is successful in about 60% of diffuse large B-cell lymphoma (DLBCL) patients. Unresponsive patients have a poor prognosis, and predictive biomarkers of response to R-CHOP are lacking. We conducted the first prospective GWAS study aimed at exploring constitutional biomarkers predictive of R-CHOP efficacy and toxicity. Overall, 216 any-stage chemonaïve DLBCL patients candidate to R-CHOP were enrolled. The median age of the 185 eligible patients was 59.2 years, 49.7% were women and 45.4% were stage I-II patients. According to the Revised International Prognostic Index (R-IPI), 14.1%, 56.8% and 29.2% were in the very good, good and poor prognosis groups, respectively. Of the patients, 85.9% produced a complete response. Highly significant associations (i.e., p < 5 × 10-8) were found between progression-free survival (PFS) and six SNPs (i.e., rs116665727, rs1607795, rs75614943, rs77241831, rs117500207, rs78466241). Additionally, five SNPs (i.e., rs74832512, rs117500207, rs35789195, rs11721010, rs12356569) were highly associated with overall survival (OS). Wild-type patients showed a prolonged PFS or OS compared with patients carrying deleterious alleles (p < 0.001). No association with the adequate significant threshold was observed between SNPs and the objective response or toxicity. In the future, these SNPs, alone or in combination, after a proper validation in an independent cohort, could contribute to improving the prediction of R-CHOP response.

Cardiovascular Risk Factors and Family History of Major Thrombotic Events in Children with Migraine: A 12-Year Retrospective Single-Centre Study.

BACKGROUND: Migraine is one of the most frequent primary headaches in childhood. The role of thrombotic predisposition in its pathogenesis is debated. Our aim was to analyse the cardiovascular risk factors and family history of major thrombotic events in children with migraine. METHODS: A retrospective, single-centre study was performed over 12 years. Our headache centre record database was screened for migraine with aura (MA) and migraine without aura (MO) on the basis of the ICHD-II (until 2013) and III criteria. A control group of otherwise healthy children was recruited. Descriptive and multivariate analyses are provided; significance was set at p < 0.05. RESULTS: Migraine was diagnosed in 930 children (24.7% MA); 73.3% were 9-14 years old. Children with MA were older (p < 0.001). A family history of cerebral ischemic events at ≤50 years old was more commonly reported by children with MA than those with MO (p < 0.001) and those in the control group (p = 0.001). Children with MA showed a higher risk of a family history of cerebral ischemic events at ≤50 years old than children with MO (OR: 2.6) and those in the control group (OR: 3.1). When comparing the family history of DVT, we observed a significantly increased risk for MA vs. MO (OR: 2.9). CONCLUSION: A family history of cerebral ischemic events at ≤50 years old leads to an increased risk of MA. Further studies are needed to explore such an association.

Health inequalities and social determinants of health: The role of syndemics in rheumatic diseases.

A syndemic is the co-existence of two or more health problems (including both social and biological features) that adversely influence each other with negative consequences on disease outcomes and perpetuation of inequalities. The syndemic approach can be applied to better understand the course of rheumatic musculoskeletal diseases (RMD) involving the study of adverse biological pathways and social determinants of health (SDH) all under the same framework. Identifying if a syndemic exists within RMDs may include investigating the synergic interactions between comorbidity (e.g., diabetes, obesity, chronic kidney diseases) and the concomitant of other adverse conditions (e.g., drug non-adherence, substance abuse), along with SDHs such as low household income, unemployment, low education, limited access to health care, as well as racial/ethnic discrimination. For decades, the understanding of RMDs progression has been based on causality, rather than investigating the kaleidoscopic web of connections that can potentially influence a disease course. The co-existence of health burdens in vulnerable populations, including those with RMD, specifically in certain socioeconomic groups, calls for new ways and strategies of thinking to improve our understanding of risk factors and co-morbidities to offer tailored interventions for clinical medicine and public health policy.

An Epidemiological Systematic Review with Meta-Analysis on Biomarker Role of Circulating MicroRNAs in Breast Cancer Incidence.

Breast cancer (BC) is a multifactorial disease caused by an interaction between genetic predisposition and environmental exposures. MicroRNAs are a group of small non-coding RNA molecules, which seem to have a role either as tumor suppressor genes or oncogenes and seem to be related to cancer risk factors. We conducted a systematic review and meta-analysis to identify circulating microRNAs related to BC diagnosis, paying special attention to methodological problems in this research field. A meta-analysis was performed for microRNAs analyzed in at least three independent studies where sufficient data to make analysis were presented. Seventy-five studies were included in the systematic review. A meta-analysis was performed for microRNAs analyzed in at least three independent studies where sufficient data to make analysis were presented. Seven studies were included in the MIR21 and MIR155 meta-analysis, while four studies were included in the MIR10b metanalysis. The pooled sensitivity and specificity of MIR21 for BC diagnosis were 0.86 (95%CI 0.76-0.93) and 0.84 (95%CI 0.71-0.92), 0.83 (95%CI 0.72-0.91) and 0.90 (95%CI 0.69-0.97) for MIR155, and 0.56 (95%CI 0.32-0.71) and 0.95 (95%CI 0.88-0.98) for MIR10b, respectively. Several other microRNAs were found to be dysregulated, distinguishing BC patients from healthy controls. However, there was little consistency between included studies, making it difficult to identify specific microRNAs useful for diagnosis.