Understanding small-scale COVID-19 transmission dynamics with the Granger causality test.

Mobility patterns have been broadly studied and deeply altered due to the coronavirus disease (COVID-19). In this paper, we study small-scale COVID-19 transmission dynamics in the city of Valencia and the potential role of subway stations and healthcare facilities in this transmission. A total of 2,398 adult patients were included in the analysis. We study the temporal evolution of the pandemic during the first six months at a small-area level. Two Voronoi segmentations of the city (based on the location of subway stations and healthcare facilities) have been considered, and we have applied the Granger causality test at the Voronoi cell level, considering both divisions of the study area. Considering the output of this approach, the so-called 'donor stations' are subway stations that have sent more connections than they have received and are mainly located in interchanger stations. The transmission in primary healthcare facilities showed a heterogeneous pattern. Given that subway interchange stations receive many cases from other regions of the city, implementing isolation measures in these areas might be beneficial for the reduction of transmission.

Home Blood Pressure Self-monitoring plus Self-titration of Antihypertensive Medication for Poorly Controlled Hypertension in Primary Care: the ADAMPA Randomized Clinical Trial.

BACKGROUND: Patient empowerment through pharmacological self-management is a common strategy in some chronic diseases such as diabetes, but it is rarely used for controlling blood pressure. OBJECTIVE: This study aimed to assess self-monitoring plus self-titration of antihypertensive medication versus usual care for reducing systolic blood pressure (SBP) at 12 months in poorly controlled hypertensive patients. DESIGN: The ADAMPA study was a pragmatic, controlled, randomized, non-masked clinical trial with two parallel arms in Valencia, Spain. PARTICIPANTS: Hypertensive patients older than 40 years, with SBP over 145 mmHg and/or diastolic blood pressure (DBP) over 90 mmHg, were recruited from July 2017 to June 2018. INTERVENTION: Participants were randomized 1:1 to usual care versus an individualized, pre-arranged plan based on self-monitoring plus self-titration. MAIN MEASURE: The primary outcome was the adjusted mean difference (AMD) in SBP between groups at 12 months. KEY RESULTS: Primary outcome data were available for 312 patients (intervention n=156, control n=156) of the 366 who were initially recruited. The AMD in SBP at 12 months (main analysis) was -2.9 mmHg (95% CI, -5.9 to 0.1, p=0.061), while the AMD in DBP was -1.9 mmHg (95% CI, -3.7 to 0.0, p=0.052). The results of the subgroup analysis were consistent with these for the main outcome measures. More patients in the intervention group achieved good blood pressure control (<140/90 mmHg) at 12 months than in the control group (55.8% vs 42.3%, difference 13.5%, 95% CI, 2.5 to 24.5%, p=0.017). At 12 months, no differences were observed in behavior, quality of life, use of health services, or adverse events. CONCLUSION: Self-monitoring plus self-titration of antihypertensive medication based on an individualized pre-arranged plan used in primary care may be a promising strategy for reducing blood pressure at 12 months compared to usual care, without increasing healthcare utilization or adverse events. TRIAL REGISTRATION: EudraCT, number 2016-003986-25 (registered 17 March 2017) and clinicaltrials.gov , NCT03242785.

A mechanistic spatio-temporal modeling of COVID-19 data.

Understanding the evolution of an epidemic is essential to implement timely and efficient preventive measures. The availability of epidemiological data at a fine spatio-temporal scale is both novel and highly useful in this regard. Indeed, having geocoded data at the case level opens the door to analyze the spread of the disease on an individual basis, allowing the detection of specific outbreaks or, in general, of some interactions between cases that are not observable if aggregated data are used. Point processes are the natural tool to perform such analyses. We analyze a spatio-temporal point pattern of Coronavirus disease 2019 (COVID-19) cases detected in Valencia (Spain) during the first 11 months (February 2020 to January 2021) of the pandemic. In particular, we propose a mechanistic spatio-temporal model for the first-order intensity function of the point process. This model includes separate estimates of the overall temporal and spatial intensities of the model and a spatio-temporal interaction term. For the latter, while similar studies have considered different forms of this term solely based on the physical distances between the events, we have also incorporated mobility data to better capture the characteristics of human populations. The results suggest that there has only been a mild level of spatio-temporal interaction between cases in the study area, which to a large extent corresponds to people living in the same residential location. Extending our proposed model to larger areas could help us gain knowledge on the propagation of COVID-19 across cities with high mobility levels.

Clinical and molecular characteristics of estrogen receptor-positive ultralow risk breast cancer tumors identified by the 70-gene signature.

The metastatic potential of estrogen receptor (ER)-positive breast cancers is heterogeneous and distant recurrences occur months to decades after primary diagnosis. We have previously shown that patients with tumors classified as ultralow risk by the 70-gene signature have a minimal long-term risk of fatal breast cancer. Here, we evaluate the previously unexplored underlying clinical and molecular characteristics of ultralow risk tumors in 538 ER-positive patients from the Stockholm tamoxifen randomized trial (STO-3). Out of the 98 ultralow risk tumors, 89% were luminal A molecular subtype, whereas 26% of luminal A tumors were of ultralow risk. Compared to other ER-positive tumors, ultralow risk tumors were significantly (Fisher's test, P < .05) more likely to be of smaller tumor size, lower grade, progesterone receptor (PR)-positive, human epidermal growth factor 2 (HER2)-negative and have low Ki-67 levels (proliferation-marker). Moreover, ultralow risk tumors showed significantly lower expression scores of multi-gene modules associated with the AKT/mTOR-pathway, proliferation (AURKA), HER2/ERBB2-signaling, IGF1-pathway, PTEN-loss and immune response (IMMUNE1 and IMMUNE2) and higher expression scores of the PIK3CA-mutation-associated module. Furthermore, 706 genes were significantly (FDR < 0.001) differentially expressed in ultralow risk tumors, including lower expression of genes involved in immune response, PI3K/Akt/mTOR-pathway, histones, cell cycle, DNA repair, apoptosis and higher expression of genes coding for epithelial-to-mesenchymal transition and homeobox proteins, among others. In conclusion, ultralow risk tumors, associated with minimal long-term risk of fatal disease, differ from other ER-positive tumors, including luminal A molecular subtype tumors. Identification of these characteristics is important to improve our prediction of nonfatal vs fatal breast cancer.

Clinical characteristics of COVID-19 hospitalized patients associated with mortality: A cohort study in Spain.

Background: The heterogeneity of patients with COVID-19 may explain the wide variation of mortality rate due to the population characteristics, presence of comorbidities and clinical manifestations. Methods: In this study, we analyzed 5342 patients' recordings and selected a cohort of 177 hospitalized patients with a poor prognosis at an early stage. We assessed during 6 months their symptomatology, coexisting health conditions, clinical measures and health assistance related to mortality. Multiple Cox proportional hazards models were built to identify the associated factors with mortality risk. Results: We observed that cough and kidney failure triplicate the mortality risk and both bilirubin levels and oncologic condition are shown as the most associated with the demise, increasing in four and ten times the risk, respectively. Other clinical characteristics such as fever, diabetes mellitus, breathing frequency, neutrophil-lymphocyte ratio, oxygen saturation, and troponin levels, were also related to mortality risk of in-hospital death. Conclusions: The present study shows that some symptomatology, comorbidities and clinical measures could be the target of prevention tools to improve survival rates.

COVID-19 psychological impact in 3109 healthcare workers in Spain: The PSIMCOV group.

BACKGROUND: The current coronavirus disease (COVID-19) has a great impact worldwide. Healthcare workers play an essential role and are one of the most exposed groups. Information about the psychosocial impact on healthcare workers is limited. METHODS: 3109 healthcare workers completed a national, internet-based, cross-sectional 45-item survey between 9 and 19 April 2020. The objective is to assess the psychological impact of the COVID-19 pandemic in Spanish healthcare workers. A Psychological Stress and Adaptation at work Score (PSAS) was defined combining four modified versions of validated psychological assessment tests (A) Healthcare Stressful Test, (B) Coping Strategies Inventory, (C) Font-Roja Questionnaire and (D) Trait Meta-Mood Scale. RESULTS: The highest psychosocial impact was perceived in Respiratory Medicine, the mean (S.D.) PSAS was 48.3 (13.6) and Geriatrics 47.6 (16.4). Higher distress levels were found in the geographical areas with the highest incidence of COVID-19 (>245.5 cases per 100 000 people), PSAS 46.8 (15.2); p < 0.001. The least stress respondents were asymptomatic workers PSAS, 41.3 (15.4); p < 0.001, as well as those above 60 years old, PSAS, 37.6 (16); p < 0.001. Workers who needed psychological therapy and did not receive it, were more stressed PSAS 52.5 (13.6) than those who did not need it PSAS 39.7 (13.9); p < 0.001. CONCLUSIONS: The psychological impact in healthcare workers in Spain during COVID-19 emergency has been studied. The stress perceived is parallel to the number of cases per 100 000 people. Psychotherapy could have a major role to mitigate the experimented stress level.

A comparison of multiple neighborhood matrix specifications for spatio-temporal model fitting: a case study on COVID-19 data.

Establishing proper neighbor relations between a set of spatial units under analysis is essential when carrying out a spatial or spatio-temporal analysis. However, it is usual that researchers choose some of the most typical (and simple) neighborhood structures, such as the first-order contiguity matrix, without exploring other options. In this paper, we compare the performance of different neighborhood matrices in the context of modeling the weekly relative risk of COVID-19 over small areas located in or near Valencia, Spain. Specifically, we construct contiguity-based, distance-based, covariate-based (considering mobility flows and sociodemographic characteristics), and hybrid neighborhood matrices. We evaluate the goodness of fit, the overall predictive quality, the ability to detect high-risk spatio-temporal units, the capability to capture the spatio-temporal autocorrelation in the data, and the goodness of smoothing for a set of spatio-temporal models based on each of the neighborhood matrices. The results show that contiguity-based matrices, some of the distance-based matrices, and those based on sociodemographic characteristics perform better than the matrices based on k-nearest neighbors and those involving mobility flows. In addition, we test the linear combination of some of the constructed neighborhood matrices and the reweighting of these matrices after eliminating weak neighbor relations, without any model improvement.

Association of Vitamin K and Non-Vitamin K Oral Anticoagulant Use and Cancer Incidence in Atrial Fibrillation Patients.

The association between the use of vitamin K antagonists (VKAs) and cancer risk reduction remains unclear. We aimed to assess the association between the use of VKAs or direct oral anticoagulants (DOACs) and the incidence of cancer in a large cohort of patients with atrial fibrillation (AF) by means of a population-based, propensity-weighted cohort study using population-wide databases including patients diagnosed with nonvalvular AF (NVAF) followed for up of 5 years (median 2.94 years). We created two cohorts based on the initiation therapy (VKA or DOAC). Initiation with VKA or DOAC was defined as filling a prescription with no previous exposure in the preceding 12 months. Cancer diagnoses of any type and for specific tumors (lung, colon, prostate, bladder, and breast). We included 39,989 patients, 31,200 (78.0%) in the VKA cohort. Incidence rate for any cancer was 12.45 per 1,000 person-year in the DOAC cohort vs. 14.55 in the VKA cohort (adjusted hazard ratio (HR): 1.16, 95% confidence interval (CI): 1.02-1.32). In secondary outcomes, no differences were found for specific types of cancer, such as lung (HR: 1.28, CI: 0.89-1.83), colon (HR: 0.84, CI: 0.62-1.13), prostate (HR: 1.40, CI: 0.94-2.10), bladder (HR: 1.07, CI: 0.76-1.52), and breast (HR: 1.05, CI: 0.66-1.69). Sensitivity analyses yielded similar results. Subgroup analyses also produced consistent findings, except for men, for whom VKA was associated with a lower risk of colon cancer (HR: 0.68, 95% CI: 0.48-0.96). Our results do not confirm a chemoprotective effect of VKA when compared with DOAC in a large, real-world cohort of patients with NVAF followed for up to 5 years.

Rapid and sustainable self-questionnaire for large-scale psychological screening in pandemic conditions for healthcare workers.

Background: The pandemic caused by a coronavirus (COVID-19) has shocked healthcare systems worldwide. However, the psychological stressors remain unclear. The objective of this study was to assess the impact of a major pandemic on healthcare workers. We hypothesized that exposure to the virus would be the primary cause of psychological stress perceived by healthcare workers. Methods: A national cross-sectional study conducted via an online questionnaire was distributed between April 9 and April 19, 2020 with a non-probabilistic sample technique. A structural equation model (SEM) was built with the variable "exposure to the virus" and the Psychological Stress and Adaptation at work Score (PSAS). "Exposure to the virus" was defined as the combined factors of 'personal-sphere', "work-related stress" and "hospital characteristics." A generalized linear model (GLM) was also tested. Results: A total of 2,197 participants filled in the questionnaire and were analyzed. The exploratory factor analysis showed statistically significant variables related to the personal-sphere, work-related stress and the hospital's characteristics, although the confirmatory factor analysis showed only the work-related stress factors to be significant. The GLM showed that personal-sphere-related variables (P < .001), stress at work (P < 0.001) and age (P < 0.001) were statistically significant. Conclusion: Physical exposure to the virus is an essential factor that contributes to the psychological impact perceived during the pandemic by healthcare professionals. A combination of personal-sphere variables, work-related stress and hospital characteristics is a significant factor correlating with the degree of stress measured by PSAS, a new and fast instrument to assess stress in healthcare workers.

Trends in Incidence and Transmission Patterns of COVID-19 in Valencia, Spain.

Importance: Limited information on the transmission and dynamics of SARS-CoV-2 at the city scale is available. Objective: To describe the local spread of SARS-CoV-2 in Valencia, Spain. Design, Setting, and Participants: This single-center epidemiological cohort study of patients with SARS-CoV-2 was performed at University General Hospital in Valencia (population in the hospital catchment area, 364 000), a tertiary hospital. The study included all consecutive patients with COVID-19 isolated at home from the start of the COVID-19 pandemic on February 19 until August 31, 2020. Exposures: Cases of SARS-CoV-2 infection confirmed by the presence of IgM antibodies or a positive polymerase chain reaction test result on a nasopharyngeal swab were included. Cases in which patients with negative laboratory results met diagnostic and clinical criteria were also included. Main Outcomes and Measures: The primary outcome was the characterization of dissemination patterns and connections among the 20 neighborhoods of Valencia during the outbreak. To recreate the transmission network, the inbound and outbound connections were studied for each region, and the relative risk of infection was estimated. Results: In total, 2646 patients were included in the analysis. The mean (SD) age was 45.3 (22.5) years; 1203 (46%) were male and 1442 (54%) were female (data were missing for 1); and the overall mortality was 3.7%. The incidence of SARS-CoV-2 cases was higher in neighborhoods with higher household income (ß2 [for mean income per household] = 0.197; 95% CI, 0.057-0.351) and greater population density (ß1 [inhabitants per km2] = 0.228; 95% CI, 0.085-0.387). Correlations with meteorological variables were not statistically significant. Neighborhood 3, where the hospital and testing facility were located, had the most outbound connections (14). A large residential complex close to the city (neighborhood 20) had the fewest connections (0 outbound and 2 inbound). Five geographically unconnected neighborhoods were of strategic importance in disrupting the transmission network. Conclusions and Relevance: This study of local dissemination of SARS-COV-2 revealed nonevident transmission patterns between geographically unconnected areas. The results suggest that tailor-made containment measures could reduce transmission and that hospitals, including testing facilities, play a crucial role in disease transmission. Consequently, the local dynamics of SARS-CoV-2 spread might inform the strategic lockdown of specific neighborhoods to stop the contagion and avoid a citywide lockdown.

Assessment of 25-Year Survival of Women With Estrogen Receptor-Positive/ERBB2-Negative Breast Cancer Treated With and Without Tamoxifen Therapy: A Secondary Analysis of Data From the Stockholm Tamoxifen Randomized Clinical Trial.

Importance: Clinically used breast cancer markers, such as tumor size, tumor grade, progesterone receptor (PR) status, and Ki-67 status, are known to be associated with short-term survival, but the association of these markers with long-term (25-year) survival is unclear. Objective: To assess the association of clinically used breast cancer markers with long-term survival and treatment benefit among postmenopausal women with lymph node-negative, estrogen receptor [ER]-positive and ERBB2-negative breast cancer who received tamoxifen therapy. Design, Setting, and Participants: This study was a secondary analysis of data from a subset of 565 women with ER-positive/ERBB2-negative breast cancer who participated in the Stockholm tamoxifen (STO-3) randomized clinical trial. The STO-3 clinical trial was conducted from 1976 to 1990 and comprised 1780 postmenopausal women with lymph node-negative breast cancer who were randomized to receive adjuvant tamoxifen therapy or no endocrine therapy. Complete 25-year follow-up data through December 31, 2016, were obtained from Swedish national registers. Immunohistochemical markers were reannotated in 2014. Data were analyzed from April to December 2020. Interventions: Patients in the original STO-3 clinical trial were randomized to receive 2 years of tamoxifen therapy vs no endocrine therapy. In 1983, patients who received tamoxifen therapy without cancer recurrence during the 2-year treatment and who consented to continued participation in the STO-3 study were further randomized to receive 3 additional years of tamoxifen therapy or no endocrine therapy. Main Outcomes and Measures: Distant recurrence-free interval (DRFI) by clinically used breast cancer markers was assessed using Kaplan-Meier and multivariable Cox proportional hazards analyses adjusted for age, period of primary diagnosis, tumor size (T1a and T1b [T1a/b], T1c, and T2), tumor grade (1-3), PR status (positive vs negative), Ki-67 status (low vs medium to high), and STO-3 clinical trial arm (tamoxifen treatment vs no adjuvant treatment). A recursive partitioning analysis was performed to evaluate which markers were able to best estimate long-term DRFI. Results: The study population comprised 565 postmenopausal women (mean [SD] age, 62.0 [5.3] years) with lymph node-negative, ER-positive/ERBB2-negative breast cancer. A statistically significant difference in long-term DRFI was observed by tumor size (88% for T1a/b vs 76% for T1c vs 63% for T2 tumors; log-rank P < .001) and tumor grade (81% for grade 1 vs 77% for grade 2 vs 65% for grade 3 tumors; log-rank P = .02) but not by PR status or Ki-67 status. Patients with smaller tumors (hazard ratio [HR], 0.31 [95% CI, 0.17-0.55] for T1a/b tumors and 0.58 [95% CI, 0.38-0.88] for T1c tumors) and grade 1 tumors (HR, 0.48; 95% CI, 0.24-0.95) experienced a significant reduction in the long-term risk of distant recurrence compared with patients with larger (T2) tumors and grade 3 tumors, respectively. A significant tamoxifen treatment benefit was observed among patients with larger tumors (HR, 0.53 [95% CI, 0.32-0.89] for T1c tumors and 0.34 [95% CI, 0.16-0.73] for T2 tumors), lower tumor grades (HR, 0.24 [95% CI, 0.07-0.82] for grade 1 tumors and 0.50 [95% CI, 0.31-0.80] for grade 2 tumors), and PR-positive status (HR, 0.38; 95% CI, 0.24-0.62). The recursive partitioning analysis revealed that tumor size was the most important characteristic associated with long-term survival, followed by clinical trial arm among patients with larger tumors. Conclusions and Relevance: This secondary analysis of data from the STO-3 clinical trial indicated that, among the selected subgroup of patients, tumor size followed by tumor grade were the markers most significantly associated with long-term survival. Furthermore, a significant long-term tamoxifen treatment benefit was observed among patients with larger tumors, lower tumor grades, and PR-positive tumors.

Characterization of Benign Breast Diseases and Association With Age, Hormonal Factors, and Family History of Breast Cancer Among Women in Sweden.

Importance: Benign breast diseases (BBDs) are common and associated with breast cancer risk, yet the etiology and risk of BBDs have not been extensively studied. Objective: To investigate the risk of BBDs by age, hormonal factors, and family history of breast cancer. Design, Setting, and Participants: This retrospective cohort study assessed 70 877 women from the population-based Karolinska Mammography Project for Risk Prediction of Breast Cancer (KARMA) who attended mammographic screening or underwent clinical mammography from January 1, 2011, to March 31, 2013, at 4 Swedish hospitals. Participants took part in a comprehensive questionnaire on recruitment. All participants had complete follow-up through high-quality Swedish national registers until December 31, 2015. Pathology medical records on breast biopsies were obtained for the participants, and BBD subtypes were classified according to the latest European guidelines. Analyses were conducted from January 1 to July 31, 2020. Exposures: Hormonal risk factors and family history of breast cancer. Main Outcomes and Measures: For each BBD subtype, incidence rates (events per 100 000 person-years) and multivariable Cox proportional hazards ratios (HRs) with time-varying covariates were estimated between the ages of 25 and 69 years. Results: A total of 61 617 women within the mammographic screening age of 40 to 69 years (median age, 53 years) at recruitment with available questionnaire data were included in the study. Incidence rates and risk estimates varied by age and BBD subtype. At premenopausal ages, nulliparity (compared with parity ≥3) was associated with reduced risk of epithelial proliferation without atypia (EP; HR, 0.62; 95% CI, 0.46-0.85) but increased risk of cysts (HR, 1.38; 95% CI, 1.03-1.85). Current and long (≥8 years) oral contraceptive use was associated with reduced premenopausal risk of fibroadenoma (HR, 0.65; 95% CI, 0.47-0.90), whereas hormone replacement therapy was associated with increased postmenopausal risks of epithelial proliferation with atypia (EPA; HR, 1.81; 95% CI, 1.07-3.07), fibrocystic changes (HR, 1.60; 95% CI, 1.03-2.48), and cysts (HR, 1.98; 95% CI, 1.40-2.81). Furthermore, predominantly at premenopausal ages, obesity was associated with reduced risk of several BBDs (eg, EPA: HR, 0.31; 95% CI, 0.17-0.56), whereas family history of breast cancer was associated with increased risk (eg, EPA: HR, 2.11; 95% CI, 1.48-3.00). Conclusions and Relevance: These results suggest that the risk of BBDs varies by subtype, hormonal factors, and family history of breast cancer and is influenced by age. Better understanding of BBDs is important to improve the understanding of benign and malignant breast diseases.

Professional counseling in women with serious mental illness: achieving a shift toward a more effective contraceptive method.

OBJECTIVES: Mental disorders in reproductive-aged women have significant implications for the risk of unintended pregnancies. The objective of this study is to assess the professional counseling in clinical practice based on motivational interview in women with serious mental illness (SMI) in order to achieve a change to a more effective contraceptive method. STUDY DESIGN: A prospective observational cohort study (2012-2017) was conducted in a convenience sample of women with severe-moderate psychiatric disorders (n = 91). Information related to psychiatric health, contraceptive use, sexual and reproductive health and socio-demographics was collected. To assess the variation in the contraceptive method, follow-up visits were planned before and after medical counseling. All participants underwent an evidence-based individual motivational interview for contraception counseling. A multivariate logistic model was carried out to identify the factors involved in changing to a more effective contraceptive method. RESULTS: After evidence-based counseling, 51.6% of participants changed their contraceptive method to a more effective one. This change was associated with gender violence (ß coefficient = 1.58, p value = .006). The relation between changing to a more effective contraceptive method and both previous abortions and having children was also positive, although the coefficients did not reach statistical significance. CONCLUSIONS: Evidence-based contraception counseling in clinical practice, based on an adapted protocol to patients with SMI, has shown, in this study, to be adequate to promote the shift to more effective contraceptive methods, avoiding the need of daily compliance in this population. Gender violence has been significantly associated with the shift to very high effectiveness methods as well as previous abortions and having children, not significantly.

Assessment of Long-term Distant Recurrence-Free Survival Associated With Tamoxifen Therapy in Postmenopausal Patients With Luminal A or Luminal B Breast Cancer.

IMPORTANCE: Patients with estrogen receptor (ER)-positive breast cancer have a long-term risk for fatal disease. However, the tumor biological factors that influence the long-term risk and the benefit associated with endocrine therapy are not well understood. OBJECTIVE: To compare the long-term survival from tamoxifen therapy for patients with luminal A or luminal B tumor subtype. DESIGN, SETTING, AND PARTICIPANTS: Secondary analysis of patients from the Stockholm Tamoxifen (STO-3) trial conducted from 1976 to 1990, which randomized postmenopausal patients with lymph node-negative breast cancer to receive adjuvant tamoxifen or no endocrine therapy. Tumor tissue sections were assessed in 2014 using immunohistochemistry and Agilent microarrays. Only patients with luminal A or B subtype tumors were evaluated. Complete long-term follow-up data up to the end of the STO-3 trial on December 31, 2012, were obtained from the Swedish National registers. Data analysis for the secondary analysis was conducted in 2017 and 2018. INTERVENTIONS: Patients were randomized to receive at least 2 years of tamoxifen therapy or no endocrine therapy; patients without recurrence who reconsented were further randomized to 3 additional years of tamoxifen therapy or no endocrine therapy. MAIN OUTCOMES AND MEASURES: Distant recurrence-free interval (DRFI) by luminal A and luminal B subtype and trial arm was assessed by Kaplan-Meier analyses and time-dependent flexible parametric models to estimate time-varying hazard ratios (HRs) that were adjusted for patient and tumor characteristics. RESULTS: In the STO-3 treated trial arm, 183 patients had luminal A tumors and 64 patients had luminal B tumors. In the untreated arm, 153 patients had luminal A tumors and 62 had luminal B tumors. Age at diagnosis ranged from 45 to 73 years. A statistically significant difference in DRFI by trial arm was observed (log rank, P < .001 [luminal A subtype, n = 336], P = .04 [luminal B subtype, n = 126]): the 25-year DRFI for luminal A vs luminal B subtypes was 87% (95% CI, 82%-93%) vs 67% (95% CI, 56%-82%) for treated patients, and 70% (95% CI, 62%-79%) vs 54% (95% CI, 42%-70%) for untreated patients, respectively. Patients with luminal A tumors significantly benefited from tamoxifen therapy for 15 years after diagnosis (HR, 0.57; 95% CI, 0.35-0.94), and those with luminal B tumors benefited from tamoxifen therapy for 5 years (HR, 0.38; 95% CI, 0.24-0.59). CONCLUSIONS AND RELEVANCE: Patients with luminal A subtype tumors had a long-term risk of distant metastatic disease, which was reduced by tamoxifen treatment, whereas patients with luminal B tumors had an early risk of distant metastatic disease, and tamoxifen benefit attenuated over time.

Noise Disturbances and Calls for Police Service in València (Spain): A Logistic Model with Spatial and Temporal Effects.

The purpose of this paper is to explore the presence of spatial and temporal effects on the calls for noise disturbance service reported to the Local Police of València (Spain) in the time period from 2014 to 2015, and investigate how some socio-demographic and environmental variables affect the noise phenomenon. The analysis is performed at the level of València's boroughs. It has been carried out using a logistic model after dichotomization of the noise incidence variable. The spatial effects consider first- and second-order neighbors. The temporal effects are included in the model by means of one- and two-week temporal lags. Our model confirms the presence of strong spatio-temporal effects. We also find significant associations between noise incidence and specific age groups, socio-economic status, land uses, and recreational activities, among other variables. The results suggest that there is a problem of "social" noise in València that is not exclusively a consequence of coexistence between local residents. External factors such as the increasing number of people on the streets during weekend nights or during summer months severely increase the chances of expecting a noise incident.

Strategic procedure in three stages for the selection of variables to obtain balanced results in public health research.

Multidisciplinary research in public health is approached using methods from many scientific disciplines. One of the main characteristics of this type of research is dealing with large data sets. Classic statistical variable selection methods, known as "screen and clean", and used in a single-step, select the variables with greater explanatory weight in the model. These methods, commonly used in public health research, may induce masking and multicollinearity, excluding relevant variables for the experts in each discipline and skewing the result. Some specific techniques are used to solve this problem, such as penalized regressions and Bayesian statistics, they offer more balanced results among subsets of variables, but with less restrictive selection thresholds. Using a combination of classical methods, a three-step procedure is proposed in this manuscript, capturing the relevant variables of each scientific discipline, minimizing the selection of variables in each of them and obtaining a balanced distribution that explains most of the variability. This procedure was applied on a dataset from a public health research. Comparing the results with the single-step methods, the proposed method shows a greater reduction in the number of variables, as well as a balanced distribution among the scientific disciplines associated with the response variable. We propose an innovative procedure for variable selection and apply it to our dataset. Furthermore, we compare the new method with the classic single-step procedures.

Detecting spatio-temporal mortality clusters of European countries by sex and age.

BACKGROUND: Mortality decreased in European Union (EU) countries during the last century. Despite these similar trends, there are still considerable differences in the levels of mortality between Eastern and Western European countries. Sub-group analysis of mortality in Europe for different age and sex groups is common, however to our knowledge a spatio-temporal methodology as in this study has not been applied to detect significant spatial dependence and interaction with time. Thus, the objective of this paper is to quantify the dynamics of mortality in Europe and detect significant clusters of mortality between European countries, applying spatio-temporal methodology. In addition, the joint evolution between the mortality of European countries and their neighbours over time was studied. METHODS: The spatio-temporal methodology used in this study takes into account two factors: time and the geographical location of countries and, consequently, the neighbourhood relationships between them. This methodology was applied to 26 European countries for the period 1990-2012. RESULTS: Principally, for people older than 64 years two significant clusters were obtained: one of high mortality formed by Eastern European countries and the other of low mortality composed of Western countries. In contrast, for ages below or equal to 64 years only the significant cluster of high mortality formed by Eastern European countries was observed. In addition, the joint evolution between the 26 European countries and their neighbours during the period 1990-2012 was confirmed. For this reason, it can be said that mortality in EU not only depends on differences in the health systems, which are a subject to national discretion, but also on supra-national developments. CONCLUSIONS: This paper proposes statistical tools which provide a clear framework for the successful implementation of development public policies to help the UE meet the challenge of rethinking its social model (Social Security and health care) and make it sustainable in the medium term.

Energy intensity modeling for wastewater treatment technologies.

Wastewater treatment plants (WWTPs) are energy intensive facilities; therefore increased pressure has been placed on managers and policy makers to reduce the facilities' energy use. Several studies were conducted to compare the energy intensity (EI) of WWTPs, which showed large dispersion in EI among the facilities. In the present study, the degree EI influenced WWTPs was tested using a set of technical variables by modeling the EI of a 305 WWTP sample grouped into five secondary treatment technologies. Results indicated the following two major findings: i) WWTPs using conventional activated sludge, extended aeration, trickling biofilters, and biodisks exhibited significant economies of scale in energy use; and ii) pollutant removal efficiency demonstrated low impacts on WWTP EI. The methodology and results of this study are of value to policy makers in planning new WWTPs and developing management plans to improve energy efficiency of wastewater treatment.

Strategic procedure in three stages for the selection of variables to obtain balanced results in public health research / Procedimiento estratégico en tres fases para la selección de variables, con el fin de obtener resultados equilibrados en investigación sobre salud pública / Procedimento estratégico em três estágios de seleção de variáveis para a obtenção de resultados equilibrados na pesquisa em saúde pública

Multidisciplinary research in public health is approached using methods from many scientific disciplines. One of the main characteristics of this type of research is dealing with large data sets. Classic statistical variable selection methods, known as "screen and clean", and used in a single-step, select the variables with greater explanatory weight in the model. These methods, commonly used in public health research, may induce masking and multicollinearity, excluding relevant variables for the experts in each discipline and skewing the result. Some specific techniques are used to solve this problem, such as penalized regressions and Bayesian statistics, they offer more balanced results among subsets of variables, but with less restrictive selection thresholds. Using a combination of classical methods, a three-step procedure is proposed in this manuscript, capturing the relevant variables of each scientific discipline, minimizing the selection of variables in each of them and obtaining a balanced distribution that explains most of the variability. This procedure was applied on a dataset from a public health research. Comparing the results with the single-step methods, the proposed method shows a greater reduction in the number of variables, as well as a balanced distribution among the scientific disciplines associated with the response variable. We propose an innovative procedure for variable selection and apply it to our dataset. Furthermore, we compare the new method with the classic single-step procedures.

La investigación multidisciplinaria en salud pública se enfoca usando métodos de muchas disciplinas científicas. Una de las principales características de este tipo de investigación es lidiar con conjuntos voluminosos de datos. Los métodos clásicos estadísticos de selección de variables, conocidos como "screen and clean", y utilizados en un solo paso, seleccionan las variables con mayor peso explicativo en su modelo. Estos métodos, comúnmente usados en investigación pública en salud, pueden inducir a enmascarar la multicolinealidad, excluyendo variables relevantes para los expertos en cada disciplina y sesgando el resultado. Se usan algunas técnicas específicas para resolver este problema, como las regresiones penalizadas y estadísticas bayesianas, que ofrecen resultados más equilibrados entre subconjuntos de variables, pero con umbrales menos restrictivos de selección. Usando la combinación de métodos clásicos, se propone en este trabajo un tercer paso en el procedimiento, recogiendo variables relevantes de cada disciplina científica, minimizando la selección de variables en cada una de ellas y obteniendo una distribución equilibrada que explica la mayor parte de la variabilidad. Este procedimiento fue aplicado en un conjunto de datos de una investigación en salud pública. Comparando los resultados con los métodos de un solo paso, el método propuesto expone una gran reducción en el número de variables, así como la distribución equilibrada entre las disciplinas científicas asociadas con la variable de respuesta. Proponemos un procedimiento innovador para la selección de variables y aplicarlo a nuestro conjunto de datos. Asimismo, comparamos el nuevo método con los procedimientos clásicos de un solo paso.

A pesquisa multidisciplinar em saúde pública emprega métodos provenientes de diversas disciplinas científicas. Uma das principais características desse tipo de pesquisa é o fato de lidar com conjuntos de dados grandes. Os métodos clássicos de seleção de variáveis estatísticas, conhecidos como "screen and clean" (filtrar e limpar), e aplicados a partir de um passo único, selecionam as variáveis com o maior peso explanatório no modelo. Esses métodos, amplamente disseminados na pesquisa em saúde pública, podem induzir ao mascaramento e à multi-colinearidade, excluindo variáveis que seriam relevantes para os especialistas em cada disciplina e enviesando os resultados. Algumas técnicas específicas usadas para resolver esse problema, como regressões penalizadas e estatísticas Bayesianas, oferecem resultados mais equilibrados entre subconjuntos de variáveis, porém com limiares de seleção menos restritivos. O artigo propõe um procedimento com três passos, usando uma combinação de métodos clássicos, captando as variáveis relevantes de cada disciplina científica, minimizando a seleção de variáveis em cada disciplina e obtendo uma distribuição equilibrada que explica a maior parte da variabilidade. O procedimento foi aplicado a um conjunto de dados de uma pesquisa em saúde pública. Ao comparar os resultados com os métodos que utilizam um único passo, o método proposto demonstra maior redução no número de variáveis, assim como, uma distribuição equilibrada entre as disciplinas científicas relacionadas à variável dependente. Propomos um procedimento inovador para a seleção de variáveis, que aplicamos depois ao nosso conjunto de dados. Além disso, comparamos o método novo com os procedimentos clássicos de apenas um estágio.

Space-time airborne disease mapping applied to detect specific behaviour of varicella in Valencia, Spain.

Airborne diseases are one of humanity's most feared sicknesses and have regularly caused concern among specialists. Varicella is an airborne disease which usually affects children before the age of 10. Because of its nature, varicella gives rise to interesting spatial, temporal and spatio-temporal patterns. This paper studies spatio-temporal exploratory analysis tools to detect specific behaviour of varicella in the city of Valencia, Spain, from 2008 to 2013. These methods have shown a significant association between the spatial and the temporal component, confirmed by the space-time models applied to the data. High relative risk of varicella is observed in economically disadvantaged regions, areas less involved in vaccination programmes.