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.

Expression of immune-related genes and breast cancer recurrence in women with ductal carcinoma in situ.

BACKGROUND AND AIM: Ductal carcinoma in situ (DCIS) is a non-obligate precursor of invasive breast cancer with highly variable clinical behavior, but risk stratification is still challenging. We sought to identify immune-related gene expression signatures of pure DCIS associated with different risks of breast cancer recurrence. METHODS: A retrospective nested case-control study of 143 pure DCIS was performed including 70 women with subsequent ipsilateral breast event (IBE, in situ or invasive; cases) and 73 DCIS women with no IBE and matched for age, tumor size, treatment, hormone receptors/HER2 status, and follow-up time (controls). RNA was extracted from DCIS samples and subjected to next-generation sequencing gene expression analysis of 395 immune-related genes. Correlations between DCIS immune-related gene expression and IBE were analyzed using weighted Cox regression for nested case-control data. RESULTS: Eight immune-related genes were differentially expressed between cases and controls. MAGEA10 expression (present vs. absent) and high expression levels of IFNA17 and CBLB (Q4 vs. Q1) were observed more frequently in DCIS of women with subsequent IBE, mainly invasive (p-valueFDR < 0.05). Conversely, expression of IL3RA1, TAGAP, TNFAIP8, and high expression levels of CCL2 and LRP1 were associated with a lower risk of IBE (p-valueFDR < 0.05). CONCLUSION: This exploratory analysis of pure DCIS showed significant differences in immune-related gene expression profiles between women with and with no subsequent IBE, particularly as invasive IBE. These results, after additional validation, could improve risk stratification and management of DCIS patients.

Association between Contrast-Enhanced Computed Tomography Radiomic Features, Genomic Alterations and Prognosis in Advanced Lung Adenocarcinoma Patients.

Non-invasive methods to assess mutational status, as well as novel prognostic biomarkers, are warranted to foster therapy personalization of patients with advanced non-small cell lung cancer (NSCLC). This study investigated the association of contrast-enhanced Computed Tomography (CT) radiomic features of lung adenocarcinoma lesions, alone or integrated with clinical parameters, with tumor mutational status (EGFR, KRAS, ALK alterations) and Overall Survival (OS). In total, 261 retrospective and 48 prospective patients were enrolled. A Radiomic Score (RS) was created with LASSO-Logistic regression models to predict mutational status. Radiomic, clinical and clinical-radiomic models were trained on retrospective data and tested (Area Under the Curve, AUC) on prospective data. OS prediction models were trained and tested on retrospective data with internal cross-validation (C-index). RS significantly predicted each alteration at training (radiomic and clinical-radiomic AUC 0.95-0.98); validation performance was good for EGFR (AUC 0.86), moderate for KRAS and ALK (AUC 0.61-0.65). RS was also associated with OS at univariate and multivariable analysis, in the latter with stage and type of treatment. The validation C-index was 0.63, 0.79, and 0.80 for clinical, radiomic, and clinical-radiomic models. The study supports the potential role of CT radiomics for non-invasive identification of gene alterations and prognosis prediction in patients with advanced lung adenocarcinoma, to be confirmed with independent studies.

Sports activity limitation during the COVID-19 pandemic in young Italian athletes: impact on mental health in children, adolescents, and young adults.

Introduction: The closure of sports centres was implemented as a preventive measure to mitigate the transmission of SARS-CoV-2. Given the observed global decline in physical activity and concurrent rise in sedentary behaviour, even among younger age groups, a retrospective cross-sectional study was undertaken to evaluate the effects of this measure on mental health in children, adolescents, and young adults during the initial phases of the COVID-19 pandemic. Methods: A total of 1,717 non-professional athletes (age range: 6-25; 53.9% males, 44.6% females) completed an online questionnaire including widely used and validated measures for mental health assessment (SDQ and PGWB-S) and questions regarding sociodemographic characteristics (such as gender), physical activity, and screen time. The association between mental health and sociodemographic characteristics, physical activity, and screen time was evaluated by using univariate and multivariable logistic regression models. Results: In children and adolescents, the incidence of psychological difficulties was associated with not being physically active (OR = 1.49; 95% CI: 1.09, 2.07; p = 0.015). Engaging in physical activity during the period of closures, particularly if more than twice a week, was significantly associated with less psychological difficulties for children/adolescents (OR = 0.54; 95% CI: 0.35, 0.82; p = 0.004) and psychological symptoms (i.e., psychological well-being lower than the median) for youth/young adults (OR = 0.25; 95% CI: 0.14, 0.45; p < 0.001). More psychological difficulties were also found in males for children and adolescents (OR = 1.37; 95% CI: 1.06, 1.79; p = 0.018). However, young adult males showed less psychological symptoms than females (OR = 0.35; 95% CI: 0.22, 0.55; p = 0.001). Additionally, a greater amount of screen time was associated with a higher incidence of psychological symptoms in the whole sample. Conclusions: Our results confirm the positive impact of physical activity on mental health during the COVID-19 pandemic among younger age groups. They also provide valuable insights into the risk-benefit relationship of interrupting sports activities as a preventive measure for infectious diseases.

Blood- and Imaging-Derived Biomarkers for Oncological Outcome Modelling in Oropharyngeal Cancer: Exploring the Low-Hanging Fruit.

AIMS: To assess whether CT-based radiomics and blood-derived biomarkers could improve the prediction of overall survival (OS) and locoregional progression-free survival (LRPFS) in patients with oropharyngeal cancer (OPC) treated with curative-intent RT. METHODS: Consecutive OPC patients with primary tumors treated between 2005 and 2021 were included. Analyzed clinical variables included gender, age, smoking history, staging, subsite, HPV status, and blood parameters (baseline hemoglobin levels, neutrophils, monocytes, and platelets, and derived measurements). Radiomic features were extracted from the gross tumor volumes (GTVs) of the primary tumor using pyradiomics. Outcomes of interest were LRPFS and OS. Following feature selection, a radiomic score (RS) was calculated for each patient. Significant variables, along with age and gender, were included in multivariable analysis, and models were retained if statistically significant. The models' performance was compared by the C-index. RESULTS: One hundred and five patients, predominately male (71%), were included in the analysis. The median age was 59 (IQR: 52-66) years, and stage IVA was the most represented (70%). HPV status was positive in 63 patients, negative in 7, and missing in 35 patients. The median OS follow-up was 6.3 (IQR: 5.5-7.9) years. A statistically significant association between low Hb levels and poorer LRPFS in the HPV-positive subgroup (p = 0.038) was identified. The calculation of the RS successfully stratified patients according to both OS (log-rank p < 0.0001) and LRPFS (log-rank p = 0.0002). The C-index of the clinical and radiomic model resulted in 0.82 [CI: 0.80-0.84] for OS and 0.77 [CI: 0.75-0.79] for LRPFS. CONCLUSIONS: Our results show that radiomics could provide clinically significant informative content in this scenario. The best performances were obtained by combining clinical and quantitative imaging variables, thus suggesting the potential of integrative modeling for outcome predictions in this setting of patients.

The role of radiomics in tongue cancer: A new tool for prognosis prediction.

BACKGROUND: Radiomics represents an emerging field of precision-medicine. Its application in head and neck is still at the beginning. METHODS: Retrospective study about magnetic resonance imaging (MRI) based radiomics in oral tongue squamous cell carcinoma (OTSCC) surgically treated (2010-2019; 79 patients). All preoperative MRIs include different sequences (T1, T2, DWI, ADC). Tumor volume was manually segmented and exported to radiomic-software, to perform feature extraction. Statistically significant variables were included in multivariable analysis and related to survival endpoints. Predictive models were elaborated (clinical, radiomic, clinical-radiomic models) and compared using C-index. RESULTS: In almost all clinical-radiomic models radiomic-score maintained statistical significance. In all cases C-index was higher in clinical-radiomic models than in clinical ones. ADC provided the best fit to the models (C-index 0.98, 0.86, 0.84 in loco-regional recurrence, cause-specific mortality, overall survival, respectively). CONCLUSION: MRI-based radiomics in OTSCC represents a promising noninvasive method of precision medicine, improving prognosis prediction before surgery.

The Impact of Sport Activity Shut down during the COVID-19 Pandemic on Children, Adolescents, and Young Adults: Was It Worthwhile?

We conducted a national retrospective survey of 1764 athletes aged ≤25 years to investigate the benefit-risk balance of sport closure during the COVID-19 pandemic peaks in Italy. Univariate and multivariable analyses were carried out to investigate the association between sport practice during the study period and (1) the risk of SARS-CoV-2 infection in athletes and their families and (2) body mass index (BMI) change, and adherence to World Health Organization (WHO) guidelines for physical activity. The percentage of subjects with a positive SARS-CoV-2 test was similar in those participating and not taking part into sport activities (11% vs. 12%, respectively, p = 0.31). Restricting the analysis to subjects who practiced sports within an organized sport society/center, the risk of SARS-CoV-2 positivity was reduced for athletes who had never stopped their training (odds ratio (OR); 95% confidence intervals (CI): 0.62; 0.41-0.93). On the other side, responders who had stopped sport activity showed a 1% increase in BMI. Adherence to WHO guidelines for physical activity was significantly higher for athletes who had continued sport activities. In conclusion, sport closure and limitations had an important negative impact on the overall health of young athletes, being also not effective in reducing the spread of COVID-19.

CT-Based Radiomics and Deep Learning for BRCA Mutation and Progression-Free Survival Prediction in Ovarian Cancer Using a Multicentric Dataset.

PURPOSE: Build predictive radiomic models for early relapse and BRCA mutation based on a multicentric database of high-grade serous ovarian cancer (HGSOC) and validate them in a test set coming from different institutions. METHODS: Preoperative CTs of patients with HGSOC treated at four referral centers were retrospectively acquired and manually segmented. Hand-crafted features and deep radiomics features were extracted respectively by dedicated software (MODDICOM) and a dedicated convolutional neural network (CNN). Features were selected with and without prior harmonization (ComBat harmonization), and models were built using different machine learning algorithms, including clinical variables. RESULTS: We included 218 patients. Radiomic models showed low performance in predicting both BRCA mutation (AUC in test set between 0.46 and 0.59) and 1-year relapse (AUC in test set between 0.46 and 0.56); deep learning models demonstrated similar results (AUC in the test of 0.48 for BRCA and 0.50 for relapse). The inclusion of clinical variables improved the performance of the radiomic models to predict BRCA mutation (AUC in the test set of 0.74). CONCLUSIONS: In our multicentric dataset, representative of a real-life clinical scenario, we could not find a good radiomic predicting model for PFS and BRCA mutational status, with both traditional radiomics and deep learning, but the combination of clinical and radiomic models improved model performance for the prediction of BRCA mutation. These findings highlight the need for standardization through the whole radiomic pipelines and robust multicentric external validations of results.

SARS-CoV-2 Circulation in the School Setting: A Systematic Review and Meta-Analysis.

The contribution of children to viral spread in schools is still debated. We conducted a systematic review and meta-analysis of studies to investigate SARS-CoV-2 transmission in the school setting. Literature searches on 15 May 2021 yielded a total of 1088 publications, including screening, contact tracing, and seroprevalence studies. MOOSE guidelines were followed, and data were analyzed using random-effects models. From screening studies involving more than 120,000 subjects, we estimated 0.31% (95% confidence interval (CI) 0.05-0.81) SARS-CoV-2 point prevalence in schools. Contact tracing studies, involving a total of 112,622 contacts of children and adults, showed that onward viral transmission was limited (2.54%, 95% CI 0.76-5.31). Young index cases were found to be 74% significantly less likely than adults to favor viral spread (odds ratio (OR) 0.26, 95% CI 0.11-0.63) and less susceptible to infection (OR 0.60; 95% CI 0.25-1.47). Lastly, from seroprevalence studies, with a total of 17,879 subjects involved, we estimated that children were 43% significantly less likely than adults to test positive for antibodies (OR 0.57, 95% CI 0.49-0.68). These findings may not applied to the Omicron phase, we further planned a randomized controlled trial to verify these results.

Deep transcranial magnetic stimulation in combination with skin thermography in obesity: a window on sympathetic nervous system.

AIMS: Obesity is known to be associated with an altered thermoregulation as well as a dysregulation of sympathetic nervous system (SNS). Considering the ability of deep transcranial magnetic stimulation (dTMS) to modulate the SNS, we hypothesized a potential role of dTMS in affecting thermoregulation in obesity. Aims of the study were to monitor the effect of a single session of dTMS on body temperature in subjects with obesity, and to correlate the dTMS-induced changes in body temperature with activation of the SNS (epinephrine and norepinephrine release). METHODS: Twenty-nine subjects with obesity [5 M, 24 F; age 50 (IQR: 58, 38) yrs; BMI 36.1 (IQR: 33.9, 38.7) kg/m2] were randomized into 2 groups receiving a single session of high frequency stimulation (HF) or sham stimulation. Under neutral thermal conditions, infrared thermography was utilized to assess bilateral fingernail-beds and abdominal temperature. RESULTS: During a single session HF, the average temperature of both fingernail-beds decreased. Right-hand temperature difference was statistically greater in HF vs Sham: median = - 1.45 (IQR: - 2.0, - 1.0)  °C for HF, p = 0.009. While temperature variation in the fingernail-bed of left hand was not statistically significant in HF compared to Sham: median = - 1.26 (IQR: - 1.6, -0.5) °C, p = 0.064. Concurrently, when estimating the effect of norepinephrine variation on temperature change of fingernail-bed of left hand, a borderline significant positive association was estimated (beta = 1.09, p = 0.067) in HF. CONCLUSIONS: Deep TMS revealed to be effective in modulating temperature in subjects with obesity, partially reversing obesity-induced alterations in heat production and dissipation with a potential SNS-mediated mechanism.

Quitting Smoking At or Around Diagnosis Improves the Overall Survival of Lung Cancer Patients: A Systematic Review and Meta-Analysis.

INTRODUCTION: Lung cancer (LC) remains a disease with poor prognosis despite recent advances in treatments. Here, we aimed at summarizing the current scientific evidence on whether quitting smoking at or around diagnosis has a beneficial effect on the survival of LC patients. METHODS: We searched MEDLINE and EMBASE for articles published until 31st October, 2021, that quantified the impact on LC patients' survival of quitting smoking at or around diagnosis or during treatment. Study-specific data were pooled into summary relative risk (SRR) and corresponding 95% confidence intervals (CI) using random effect meta-analysis models. RESULTS: Twenty-one articles published between 1980 and 2021 were included, which encompassed a total of over 10,000 LC patients. There was substantial variability across studies in terms of design, patients' characteristics, treatments received, criteria used to define smoking status (quitters or continued), and duration of follow-up. Quitting smoking at or around diagnosis was significantly associated with improved overall survival (SRR 0.71, 95% CI 0.64-0.80), consistently among patients with non-small cell LC (SRR 0.77, 95% CI 0.66-0.90, n studies = 8), small cell LC (SRR 0.75, 95% CI 0.57-0.99, n studies = 4), or LC of both or unspecified histological type (SRR 0.81, 95% CI 0.68-0.96, n studies = 6). CONCLUSIONS: Quitting smoking at or around diagnosis is associated with a beneficial effect on the survival of LC patients. Treating physicians should educate LC patients about the benefits of quitting smoking even after diagnosis and provide them with the necessary smoking cessation support.