Purpose This study aimed to evaluate the preliminary effectiveness of an educational intervention using a web-app to improve knowledge of breast cancer risk factors and symptoms and adherence to healthy eating and physical activity among women without breast cancer diagnosis in Asturias (Spain). Methods A pragmatic randomized pilot trial was conducted to evaluate the impact of a web-app-based intervention for women without breast cancer diagnosis. Women in the intervention group participated in a 6-month intervention web-app based on the Behaviour Change Wheel Model. The web-app includes information about breast cancer risk factors, early detection, physical activity and diet. Results Two hundred and eighty-fifth women aged 25-50 were invited to join the study. Two hundred and twenty-four were randomly assigned to either the intervention group (IG = 134) or control group (CG = 90) according to their place of residence. Adherence among women in the IG increased significantly from pre- to post-intervention for eight of the 12 healthy behaviors and for the identification of six risk factors and six symptoms compared to women in the CG and, among whom adherence only increased for two behaviors, the identification of one risk factor and 0 symptoms. The intervention significantly improved the mean number of risk factors + 1.06 (p < 0.001) and symptoms + 1.18 (p < 0.001) identified by women in the IG. Conclusions The preliminary results of this study suggest that an educational intervention using a web-app and based on the Behaviour Change Wheel model could be useful to improve knowledge of breast cancer risk factors and symptoms and to improve adherence to a healthy diet and physical activity in women without a previous breast cancer diagnosis.

Simple Summary Triple-negative breast cancer (TNBC) is currently in the clinical research spotlight because of the tumor’s aggressive and invasive nature and the scarcity of therapeutic targets. Despite recent advances in identifying reliable prognostic biomarkers in the tumor microenvironment (TME), rigorous evaluation of their predictive capacity remains challenging. We describe the immune cellular and genetic profile of the residual tumor of TNBC that does not achieve a pathological complete response (pCR) after neoadjuvant chemotherapy (NAC). A high concentration of lymphocytes and dendritic cells, as well as genetic TME markers such as MUC-1 and CXCL13 in the residual tumor, are valuable prognostic factors of survival and relapse in TNBC patients. From a clinical health perspective, a thorough understanding of the composition of the TME and its prognostic implications might yield relevant immunological information and reveal key predictive biomarkers. This could ultimately help substantially improve the outcomes of residual cancer-burdened TNBC patients after NAC. With a high risk of relapse and death, and a poor or absent response to therapeutics, the triple-negative breast cancer (TNBC) subtype is particularly challenging, especially in patients who cannot achieve a pathological complete response (pCR) after neoadjuvant chemotherapy (NAC). Although the tumor microenvironment (TME) is known to influence disease progression and the effectiveness of therapeutics, its predictive and prognostic potential remains uncertain. This work aimed to define the residual TME profile after NAC of a retrospective cohort with 96 TNBC patients by immunohistochemical staining (cell markers) and chromogenic in situ hybridization (genetic markers). Kaplan-Meier curves were used to estimate the influence of the selected TME markers on five-year overall survival (OS) and relapse-free survival (RFS) probabilities. The risks of each variable being associated with relapse and death were determined through univariate and multivariate Cox analyses. We describe a unique tumor-infiltrating immune profile with high levels of lymphocytes (CD4, FOXP3) and dendritic cells (CD21, CD1a and CD83) that are valuable prognostic factors in post-NAC TNBC patients. Our study also demonstrates the value of considering not only cellular but also genetic TME markers such as MUC-1 and CXCL13 in routine clinical diagnosis to refine prognosis modelling.

ObjectiveTo investigate longitudinal changes in the liver stiffness measurement (LSM) in the general adult population without known liver disease and to describe its association with metabolic risk factors, with a special focus on subjects with non-alcoholic fatty liver disease (NAFLD) and dysglycemia. Material and MethodsA longitudinal adult population-based cohort study was conducted in Catalonia. LSM was measured by transient elastography (TE) at baseline and follow-up (median: 4.2 years). Subgroup with NAFLD and dysglycemia were analyzed. Moderate-to-advanced liver fibrosis was defined as LSM >= 8.0 kPa and LSM >= 9.2 kPa respectively. ResultsAmong 1.478 subjects evaluated, the cumulative incidence of LSM >= 8.0 kPa and >= 9.2 kPa at follow-up was 2.8% and 1.9%, respectively. This incidence was higher in NAFLD (7.1% for LSM >= 8.0 kPa and 5% for LSM >= 9.2 kPa) and dysglycemia (6.2% for LSM >= 8.0 kPa and 4.7% for LSM >= 9.2 kPa) subgroups. In the global cohort, the multivariate analyses showed that dysglycemia, abdominal obesity and atherogenic dyslipidemia were significantly associated with progression to moderate-to-advanced liver fibrosis. Female sex was negatively associated. In subjects with NAFLD, abdominal obesity and dysglycemia were associated with changes in LSM to >= 8.0 kPa and >= 9.2 kPa at follow-up. A decline in LSM value to ConclusionsIn this population study, the presence of abdominal obesity and dysglycemia were the main risk metabolic factors associated with moderate-to-advanced liver fibrosis development over time in general populations as well as in subjects with NAFLD.

To date, odor research has primarily focused on the behavioral effects of common odors on consumer perception and choices. We report a study that examines, for the first time, the effects of human body odor cues on consumer purchase behaviors. The influence of human chemosignals produced in three conditions, namely happiness, fear, a relaxed condition (rest), and a control condition (no odor), were examined on willingness to pay (WTP) judgments across various products. We focused on the speed with which participants reached such decisions. The central finding revealed that participants exposed to human odors reached decisions significantly faster than the no odor control group. The main driving force is that human body odors activate the presence of others during decision-making. This, in turn, affects response speed. The broader implications of this finding for consumer behavior are discussed.

Short summaryWe investigated changes in serologic measurements after COVID-19 vaccination in 19,422 subjects. An individual-level analysis was performed on standardized measurements. Age, infection, vaccine doses, time between doses and serologies, and vaccine type were associated with changes in serologic levels within 13 months. BackgroundPersistence of vaccine immunization is key for COVID-19 prevention. MethodsWe investigated the difference between two serologic measurements of anti-COVID-19 S1 antibodies in an individual-level analysis on 19,422 vaccinated healthcare workers (HCW) from Italy, Spain, Romania, and Slovakia, tested within 13 months from first dose. Differences in serologic levels were divided by the standard error of the cohort-specific distribution, obtaining standardized measurements. We fitted multivariate linear regression models to identify predictors of difference between two measurements. ResultsWe observed a progressively decreasing difference in serologic levels from <30 days to 210-240 days. Age was associated with an increased difference in serologic levels. There was a greater difference between the two serologic measurements in infected HCW than in HCW who had never been infected; before the first measurement, infected HCW had a relative risk (RR) of 0.81 for one standard deviation in the difference [95% confidence interval (CI) 0.78-0.85]. The RRs for a 30-day increase in time between first dose and first serology, and between the two serologies, were 1.08 (95% CI 1.07-1.10) and 1.04 (95% CI 1.03-1.05), respectively. The first measurement was a strong predictor of subsequent antibody decrease (RR 1.60; 95% CI 1.56-1.64). Compared with Comirnaty, Spikevax (RR 0.83, 95% CI 0.75-0.92) and mixed vaccines (RR 0.61, 95% CI 0.51-0.74) were smaller decrease in serological level (RR 0.46; 95% CI 0.40-0.54). ConclusionsAge, COVID-19 infection, number of doses, time between first dose and first serology, time between serologies, and type of vaccine were associated with differences between the two serologic measurements within a 13-month period.

Background: Multimorbidity and frailty are characteristics of aging that need individualized evaluation, and there is a 2-way causal relationship between them. Thus, considering frailty in analyses of multimorbidity is important for tailoring social and health care to the specific needs of older people.Objective: This study aimed to assess how the inclusion of frailty contributes to identifying and characterizing multimorbidity patterns in people aged 65 years or older.Methods: Longitudinal data were drawn from electronic health records through the SIDIAP (Sistema d’Informacio pel Desenvolupament de la Investigacio a l’Atencio Primaria) primary care database for the population aged 65 years or older from 2010 to 2019 in Catalonia, Spain. Frailty and multimorbidity were measured annually using validated tools (eFRAGICAP, a cumulative deficit model; and Swedish National Study of Aging and Care in Kungsholmen [SNAC-K], respectively). Two sets of 11 multimorbidity patterns were obtained using fuzzy c-means. Both considered the chronic conditions of the participants. In addition, one set included age, and the other included frailty. Cox models were used to test their associations with death, nursing home admission, and home care need. Trajectories were defined as the evolution of the patterns over the follow-up period.Results: The study included 1,456,052 unique participants (mean follow-up of 7.0 years). Most patterns were similar in both sets in terms of the most prevalent conditions. However, the patterns that considered frailty were better for identifying the population whose main conditions imposed limitations on daily life, with a higher prevalence of frail individuals in patterns like chronic ulcers & peripheral vascular. This set also included a dementia-specific pattern and showed a better fit with the risk of nursing home admission and home care need. On the other hand, the risk of death had a better fit with the set of patterns that did not include frailty. The change in patterns when considering frailty also led to a change in trajectories. On average, participants were in 1.8 patterns during their follow-up, while 45.1% (656,778/1,456,052) remained in the same pattern.Conclusions: Our results suggest that frailty should be considered in addition to chronic diseases when studying multimorbidity patterns in older adults. Multimorbidity patterns and trajectories can help to identify patients with specific needs. The patterns that considered frailty were better for identifying the risk of certain age-related outcomes, such as nursing home admission or home care need, while those considering age were better for identifying the risk of death. Clinical and social intervention guidelines and resource planning can be tailored based on the prevalence of these patterns and trajectories.

BACKGROUND: Different multimorbidity patterns present with different prognoses, but it is unknown to what extent they may influence the effectiveness of an individualized multicomponent exercise program offered to hospitalized older adults. METHODS: This study is a secondary analysis of a randomized controlled trial conducted in the Department of Geriatric Medicine of a tertiary hospital. In addition to the standard care, an exercise-training multicomponent program was delivered to the intervention group during the acute hospitalization period. Multimorbidity patterns were determined through fuzzy c-means cluster analysis, over 38 chronic diseases. Functional, cognitive and affective outcomes were considered. RESULTS: Three hundred and six patients were included in the analyses (154 control; 152 intervention), with a mean age of 87.2 years, and 58.5% being female. Four patterns of multimorbidity were identified: heart valves and prostate diseases (26.8%); metabolic diseases and colitis (20.6%); psychiatric, cardiovascular and autoimmune diseases (16%); and an unspecific pattern (36.6%). The Short Physical Performance Battery (SPPB) test improved across all patterns, but the intervention was most effective for patients in the metabolic/colitis pattern (2.48-point difference between intervention/control groups, 95% CI 1.60-3.35). Regarding the Barthel Index and the Mini Mental State Examination (MMSE), the differences were significant for all multimorbidity patterns, except for the psychiatric/cardio/autoimmune pattern. Differences concerning quality of life were especially high for the psychiatric/cardio/autoimmune pattern (16.9-point difference between intervention/control groups, 95% CI 4.04, 29.7). CONCLUSIONS: Patients in all the analyzed multimorbidity patterns improved with this tailored program, but the improvement was highest for those in the metabolic pattern. Understanding how different chronic disease combinations are associated with specific functional and cognitive responses to a multicomponent exercise intervention may allow further tailoring such interventions to older patients’ clinical profile.

Objective: An increased interarm blood pressure difference (IAD) (>= 10 mmHg) has been associa-ted with increased cardiovascular morbidity and mortality. There are few studies determining how IAD has to be measured and its reliability between visits. The objectives of our study were twofold. First, to evaluate the concordance between two automatic oscillometric devices for IAD measurement (two OMRON devices and one Microlife WatchBPTM device (WBPTM)) and to analyse the reproducibility of IAD between visits in the general population attending a primary care centre.Design: Descriptive cross-sectional study of concordance between the two methods and repro-ducibility of IAD between two visits separated by one week.Site: Parets del Valles primary care centre (Barcelona).Participants: General population aged 35-74 years. Interventions and main measurements: One hundred and forty-nine patients completed the two visits. At each visit, IAD was measured three times with both methods and the mean of the three determinations was considered. Other variables such as sociodemographic and anth-ropometric variables, pathological antecedents and pharmacological treatment were collected through a review of the medical history and an interview with the patient. Concordance between the two devices and between visits reproducibility were calculated using the Lin concordance coefficient (CCL) for IAD expressed continuously and kappa(k) indices for IAD categorised as normal or pathological.Results: Concordance for IAD expressed continuously was low: CCL = 0.13 (0.02-0.24). Concor-dance was also low for IAD categorised as normal or pathological (k = -0.03 (-0.05-0.00)). Reproducibility between visits was low for both methods and for both continuous and cate-gorised IAD: with OMRONTM CCL = 0.19 (0.03-0.34) and k = -0.02 (-0.16-0.12) and for WBPTM CCL = 0.14 (-0.01-0.29) and k = 0.49 (0.33-0.64).Conclusions: Concordance between two automatic oscillometers in the simultaneous IAD mea-surement was low. Reproducibility between visits was also low for both methods.(c) 2022 The Authors. Published by Elsevier Espana, S.L.U. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Background: The persistence of antibody levels after COVID-19 vaccination has public health relevance. We analyzed the determinants of quantitative serology at 9 months after vaccination in a multicenter cohort. Methods: We analyzed data on anti-SARS-CoV-2 spike antibody levels at 9 months from the first dose of vaccinated HCW from eight centers in Italy, Germany, Spain, Romania and Slovakia. Serological levels were log-transformed to account for the skewness of the distribution and normalized by dividing them by center-specific standard errors. We fitted center-specific multivariate regression models to estimate the cohort-specific relative risks (RR) of an increase of one standard deviation of log antibody level and the corresponding 95% confidence interval (CI), and combined them in random-effects meta-analyses. Finally, we conducted a trend analysis of 1 to 7 months’ serology within one cohort. Results: We included 20,216 HCW with up to two vaccine doses and showed that high antibody levels were associated with female sex (p = 0.01), age (RR = 0.87, 95% CI = 0.86-0.88 per 10-year increase), 10-day increase in time since last vaccine (RR = 0.97, 95% CI 0.97-0.98), previous infection (3.03, 95% CI = 2.92-3.13), two vaccine doses (RR = 1.22, 95% CI = 1.09-1.36), use of Spikevax (OR = 1.51, 95% CI = 1.39-1.64), Vaxzevria (OR = 0.57, 95% CI = 0.44-0.73) or heterologous vaccination (OR = 1.33, 95% CI = 1.12-1.57), compared to Comirnaty. The trend in the Bologna cohort, based on 3979 measurements, showed a decrease in mean standardized antibody level from 8.17 to 7.06 (1-7 months, p for trend 0.005). Conclusions: Our findings corroborate current knowledge on the determinants of COVID-19 vaccine-induced immunity and declining trend with time.