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Objectives: This study aimed to investigate the relationship between trial registration, trial discrepancy from registered protocol, and spin in nonpharmacological trials. Study Design and Setting: Recent psychotherapy trials on depression (2015–2018) were analyzed regarding their registration status and its relationship to discrepancies between registered and published primary outcomes and to spin (discrepancy between the nonsignificant finding in a study and an overly beneficial interpretation of the effect of the treatment). Results: A total of 196 trials were identified, of which 78 (40%) had been registered prospectively and 56 (29%) had been registered retrospectively. In 102 (76%) of 134 registered trials, discrepancies between trial and protocol were present. Of 72 trials with a nonsignificant difference between treatments for the primary outcome, 68 trials (94%) showed spin. Discrepancies from protocol were less frequent in prospectively than in retrospectively registered trials (odds ratio= 0.19; 95% confidence interval [CI]: 0.07–0.52), but regarding the amount of spin, there was no difference between prospectively and retrospectively registered trials (rb = −0.12; 95% CI: −0.41 to 0.19) or between registered and unregistered trials (rb = −0.22, 95% CI −0.49 to 0.08). Conclusion: Protocol discrepancies and spin have a high prevalence in psychotherapy outcome research. The results show no relation between registration and spin, but prospective registration may prevent discrepancies from protocol.

Applying the growing body of coronavirus disease 2019 imaging evidence to daily clinical practice requires thoughtful use of established clinical epidemiology principles.

Objective: To assess the relative importance of A MeaSurement Tool to Assess systematic Reviews 2 (AMSTAR2) items.Study Design and Setting: A best-worst scaling object case was conducted among a sample of experts in the field of systematic reviews (SRs) and meta-analyses (MAs). Respondents were asked in a series of 15 choice tasks to choose the most and the least important item from a set of four items from the master list, which included the 16 AMSTAR2 items. Hierarchical Bayes analysis was used to generate the relative importance score for each item.Results: The most important items highlighted by our 242 experts to conduct overview of reviews and critically assess SRs/MAs were the appropriateness of statistical analyses and adequacy of the literature search, followed by items regarding the assessment of risk of bias, the research protocol, and the assessment of heterogeneity (relative importance score >6.5). Items related to funding sources and the assessment of study selection and data extraction in duplicate were rated as least important.Conclusion: Although all AMSTAR2 items can be considered as important, our results highlighted the importance of keeping the two items (the appropriateness of statistical analyses and the adequacy of the literature search) among the critical items proposed by AMSTAR2 to critically appraise SRs/MAs. (C) 2020 Elsevier Inc. All rights reserved.

Monkeypox research was mostly of academic interest until the 1980s when with the global waning of smallpox, monkeypox emerged as the most important Orthopoxvirus of public health importance [1,2]. ...

The construct of embodiment captures a broad range of experiences of living in the body. The present program of research involved developing and evaluating a fully structured measure of the experience of embodiment construct, the Experience of Embodiment Scale (EES), via four independent samples of women. Study 1 (N = 92) provided initial support for the internal consistency and convergent validity of the EES. Study 2 (N = 412) involved factor analyses of the EES, leading to the emergence of 6 factors, reflecting different aspects of the experience of embodiment. Further, this study supported the internal consistency of the EES and its subscales, as well as its construct and discriminant validity. As expected, the EES correlated with measures of body- and self-esteem, body connection, sexual assertiveness, among other measures, and did not correlate with the Perfectionism Personal Standards Scale. Study 3 (N = 348) confirmed the factor structure of the scale from Study 2. Study 4 (N = 76) demonstrated that EES scores were stable over a 3-week period. The EES can be used by researchers and clinicians interested in capturing individuals’ range of experiences of living in their bodies, both positive and negative.

Ambitious World Health Organization targets for disease elimination require monitoring of epidemics using routine health data in settings of decreasing and low incidence. We evaluated 2 methods commonly applied to routine testing results to estimate incidence rates that assume a uniform probability of infection between consecutive negative and positive tests based on 1) the midpoint of this interval and 2) a randomly selected point in this interval. We compared these with an approximation of the Poisson binomial distribution, which assigns partial incidence to time periods based on the uniform probability of occurrence in these intervals. We assessed bias, variance, and convergence of estimates using simulations of Weibull-distributed failure times with systematically varied baseline incidence and varying trend. We considered results for quarterly, half-yearly, and yearly incidence estimation frequencies. We applied the methods to assess human immunodeficiency virus (HIV) incidence in HIV-negative patients from the Treatment With Antiretrovirals and Their Impact on Positive and Negative Men (TAIPAN) Study, an Australian study of HIV incidence in men who have sex with men, between 2012 and 2018. The Poisson binomial method had reduced bias and variance at low levels of incidence and for increased estimation frequency, with increased consistency of estimation. Application of methods to real-world assessment of HIV incidence found decreased variance in Poisson binomial model estimates, with observed incidence declining to levels where simulation results had indicated bias in midpoint and random-point methods.

Epidemiologists are often confronted with datasets to analyse which contain measurement error due to, for instance, mistaken data entries, inaccurate recordings and measurement instrument or procedural errors. If the effect of measurement error is misjudged, the data analyses are hampered and the validity of the study’s inferences may be affected. In this paper, we describe five myths that contribute to misjudgments about measurement error, regarding expected structure, impact and solutions to mitigate the problems resulting from mismeasurements. The aim is to clarify these measurement error misconceptions. We show that the influence of measurement error in an epidemiological data analysis can play out in ways that go beyond simple heuristics, such as heuristics about whether or not to expect attenuation of the effect estimates. Whereas we encourage epidemiologists to deliberate about the structure and potential impact of measurement error in their analyses, we also recommend exercising restraint when making claims about the magnitude or even direction of effect of measurement error if not accompanied by statistical measurement error corrections or quantitative bias analysis. Suggestions for alleviating the problems or investigating the structure and magnitude of measurement error are given.

Prevailing dietary guidelines have widely recommended diets relatively low in red and processed meats and high in minimally processed plant foods for the prevention of chronic diseases. However, an ad hoc research group called the Nutritional Recommendations (NutriRECS) consortium recently issued “new dietary guidelines” encouraging individuals to continue their current meat consumption habits due to “low certainty” of the evidence, difficulty of altering meat eaters’ habits and preferences, and the lack of need to consider environmental impacts of red meat consumption. These recommendations are not justified, in large part because of the flawed methodologies used to review and grade nutritional evidence. The evidence evaluation was largely based on the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) criteria, which are primarily designed to grade the strength of evidence for clinical interventions especially pharmacotherapy. However, the infeasibility for conducting large, long-term randomized clinical trials on most dietary, lifestyle, and environmental exposures makes the criteria inappropriate in these areas. A separate research group proposed a modified and validated system for rating the meta-evidence on nutritional studies (NutriGRADE) to address several limitations of the GRADE criteria. Applying NutriGRADE, the evidence on the positive association between red and processed meats and type 2 diabetes was rated to be of “high quality,” while the evidence on the association between red and processed meats and mortality was rated to be of “moderate quality.” Another important limitation is that inadequate attention was paid to what might be replacing red meat, be it plant-based proteins, refined carbohydrates, or other foods. In summary, the red/processed meat recommendations by NutriRECS suffer from important methodological limitations and involve misinterpretations of nutritional evidence. To improve human and planetary health, dietary guidelines should continue to emphasize dietary patterns low in red and processed meats and high in minimally processed plant foods such as fruits and vegetables, whole grains, nuts, and legumes.

Background Estimating the strength of causal effects is an important component of epidemiologic research, and causal graphs provide a key tool for optimizing the validity of these effect estimates. Although a large literature exists on the mathematical theory underlying the use of causal graphs, including directed acyclic graphs, to assess and describe causal assumptions, and translate these assumptions into appropriate statistical analysis plans, less literature exists to aid applied researchers in understanding how best to develop and use causal graphs in their research projects. Objective We sought to understand this gap by surveying practicing epidemiologists and medical researchers on their knowledge, level of interest, attitudes, and practices towards the use of causal graphs in applied epidemiology and health research. Methods We conducted an anonymous survey of self-identified epidemiology and health researchers via Twitter and via the Society of Epidemiologic Research membership listserv. The survey was conducted using Qualtrics and asked a series of multiple choice and open-ended questions about causal graphs. Results In total, 439 responses were collected. Overall, a majority of participants reported being comfortable with using causal graphs and reported using them ‘sometimes’, ‘often’, or ‘always’ in their research. Almost three quarters of respondents had received formal training on causal graphs (typically causal directed acyclic graphs). Having received training appeared to improve comprehension of the underlying assumptions of causal graphs. Many of the respondents who did not use causal graphs reported lack of knowledge as a barrier to using DAGs in their research. Of the participants who did not use DAGs, many expressed that trainings, either in-person or online, would be useful resources to help them use causal graphs more often in their research. Conclusion Causal graphs are of interest to epidemiologists and medical researchers, but there are several barriers to their uptake. Additional training and clearer guidance are needed. In addition, methodological developments regarding visualization of effect measure modification and interaction on causal graphs is needed.

Education of medical students requires teaching students how to navigate in the broad field of medical research. The objective of this article is to provide an overview about medical research and to show how to denote a medical study in a concise fashion. Medical research can be classified into categories according to the object of investigation. Examples for medical research categories are therapeutic, diagnostic and prognostic studies, epidemiological studies, animal and in vitro studies etc. Each research category uses a specific set of study types with names such as cross-sectional study, case-control study etc. The article describes the principles of the study types. Together, research category and study type briefly describe the design of a medical study.

Coffee consumption has been inversely associated with various diseases, however, the underlying mechanisms are not entirely clear. We used data of 17,752 Third National Health and Nutrition Examination Survey participants to investigate the association of 245 metabolites, nutrients, and lifestyle factors with coffee consumption. We used data from the first phase (n = 8825) to identify factors with a false discovery rate of &lt, 5%. We then replicated our results using data from the second phase (n = 8927). Regular coffee consumption was positively associated with active and passive smoking, serum lead and urinary cadmium concentrations, dietary intake of potassium and magnesium, and aspirin intake. In contrast, regular coffee consumption was inversely associated with serum folate and red blood cell folate levels, serum vitamin E and C, and beta-cryptoxanthin concentrations, Healthy Eating Index score, and total serum bilirubin. Most of the aforementioned associations were also observed for caffeinated beverage intake. In our assessment of the association between coffee consumption and selected metabolites, nutrients, and lifestyle factors, we observed that regular coffee and caffeinated beverage consumption was strongly associated with smoking, serum lead levels, and poorer dietary habits.

For outbreaks of gastrointestinal disease, rapid identification of the source is crucial to enable public health intervention and prevent further cases. Outbreak investigation comprises analyses of exposure information from cases and, if required, undertaking analytical epidemiological studies. Hypothesis generation has been reliant on empirical knowledge of exposures historically associated with a given pathogen. Epidemiology studies are resource-intensive and prone to bias, one of the reasons being the difficulties in recruiting appropriate controls. For this paper, the information from cases was compared against pre-defined background exposure information. As exemplars, three past outbreaks were used, one of common and two of rare exposures. Information from historical case trawling questionnaires was used to define background exposure having removed any exposures implicated with the outbreak. The case-background approach showed good sensitivity and specificity, identifying correctly all outbreak-related exposures. One additional exposure related to a retailer was identified and four food items where all cases had been exposed. In conclusion, the case-background method, a development of the case-case design, can be used to assist with hypothesis generation or when a case-control study may not be possible to carry out.

Contains fulltext : 220949.pdf (Publisher’s version ) (Open Access) The Rotterdam Study is an ongoing prospective cohort study that started in 1990 in the city of Rotterdam, The Netherlands. The study aims to unravel etiology, preclinical course, natural history and potential targets for intervention for chronic diseases in mid-life and late-life. The study focuses on cardiovascular, endocrine, hepatic, neurological, ophthalmic, psychiatric, dermatological, otolaryngological, locomotor, and respiratory diseases. As of 2008, 14,926 subjects aged 45 years or over comprise the Rotterdam Study cohort. Since 2016, the cohort is being expanded by persons aged 40 years and over. The findings of the Rotterdam Study have been presented in over 1700 research articles and reports. This article provides an update on the rationale and design of the study. It also presents a summary of the major findings from the preceding 3 years and outlines developments for the coming period.

BACKGROUND: the Covid-19 pandemic has provoked a huge of clinical and epidemiological research initiatives, especially in the most involved countries. However, this very large effort was characterized by several methodological weaknesses, both in the field of discovering effective treatments (with too many small and uncontrolled trials) and in the field of identifying preventable risks and prognostic factors (with too few large, representative and well-designed cohorts orcase-control studies). OBJECTIVES: in response to the fragmented and uncoordinatedresearch production on Covid-19, the italian Association of Epidemiology (AIE) stimulated the formation of a working group (WG) with the aims of identifying the most important gaps in knowledge and to propose a structured research agenda of clinical and epidemiological studies considered at high priority on Covid-19, including recommendations on the preferable methodology. METHODS: the WG was composed by 25 subjects, mainly epidemiologists, statisticians, and other experts in specific fields, who have voluntarily agreed to the proposal. The agreement on a list of main research questions and on the structure of the specific documents to be produced were defined through few meetings and cycles of document exchanges. RESULTS: twelve main research questions on Covid-19 were identified, covering aetiology, prognosis,interventions, follow-up and impact on general and specific populations (children, pregnant women). For each of them, a two-page form was developed, structured in: background, main topics, methods (with recommendations on preferred study design and warnings for bias prevention) and an essential bibliography. CONCLUSIONS: this research agenda represents an initial contribution to direct clinical and epidemiological research efforts on high priority topics with a focus on methodological aspects. Further development and refinements of this agenda by Public Health Authorities are encouraged.

Background A proper application of the Delphi technique is essential for obtaining valid research results. Medical researchers regularly use Delphi studies, but reports often lack detailed information on methodology and controlled feedback: in the medical literature, papers focusing on Delphi methodology issues are rare. Since the introduction of electronic surveys, details on response times remain scarce. We aim to bridge a number of gaps by providing a real world example covering methodological choices and response times in detail. Methods The objective of our e(lectronic)-Delphi study was to determine minimum standards for emergency departments (EDs) in the Netherlands. We opted for a two-part design with explicit decision rules. Part 1 focused on gathering and defining items; Part 2 addressed the main research question using an online survey tool. A two-person consensus rule was applied throughout: even after consensus on specific items was reached, panellists could reopen the discussion as long as at least two panellists argued similarly. Per round, the number of reminders sent and individual response times were noted. We also recorded the methodological considerations and evaluations made by the research team prior to as well as during the study. Results The study was performed in eight rounds and an additional confirmation round. Response rates were 100% in all rounds, resulting in 100% consensus in Part 1 and 96% consensus in Part 2. Our decision rules proved to be stable and easily applicable. Items with negative advice required more rounds before consensus was reached. Response delays were mostly due to late starts, but once panellists started, they nearly always finished the questionnaire on the same day. Reminders often yielded rapid responses. Intra-individual differences in response time were large, but quick responders remained quick. Conclusions We advise those considering Delphi study to follow the CREDES guideline, consider a two-part design, invest in personal commitment of the panellists, set clear decision rules, use a consistent lay-out and send out your reminders early. Adopting this overall approach may assist researchers in future Delphi studies and may help to improve the quality of Delphi designs in terms of improved rigor and higher response rates.

Although the suicide rate in Japan increased during the COVID-19 pandemic, the reasons for suicide have yet to be comprehensively investigated.To assess which reasons for suicide had rates that exceeded the expected number of suicide deaths for that reason during the COVID-19 pandemic.This national, population-based cross-sectional study of data on suicides gathered by the Ministry of Health, Labor, and Welfare from January 2020 to May 2021 used a times-series analysis on the numbers of reason-identified suicides. Data of decedents were recorded by the National Police Agency and compiled by the Ministry of Health, Labor, and Welfare.For category analysis, we compared data from January 2020 to May 2021 with data from December 2014 to June 2020. For subcategory analysis, data from January 2020 to May 2021 were compared with data from January 2019 to June 2020.The main outcome was the monthly excess suicide rate, ie, the difference between the observed number of monthly suicide deaths and the upper bound of the 1-sided 95% CI for the expected number of suicide deaths in that month. Reasons for suicide were categorized into family, health, economy, work, relationships, school, and others, which were further divided into 52 subcategories. A quasi-Poisson regression model was used to estimate the expected number of monthly suicides. Individual regression models were used for each of the 7 categories, 52 subcategories, men, women, and both genders.From the 29 938 suicides (9984 [33.3%] women; 1093 [3.7%] aged20 years; 3147 [10.5%] aged80 years), there were 21 027 reason-identified suicides (7415 [35.3%] women). For both genders, all categories indicated monthly excess suicide rates, except for school in men. October 2020 had the highest excess suicide rates for all cases (observed, 1577; upper bound of 95% CI for expected number of suicides, 1254; 25.8% greater). In men, the highest monthly excess suicide rate was 24.3% for the other category in August 2020 (observed, 87; upper bound of 95% CI for expected number, 70); in women, it was 85.7% for school in August 2020 (observed, 26; upper bound of 95% CI for expected number, 14).In this study, observed suicides corresponding to all 7 categories of reasons exceeded the monthly estimates (based on data from before or during the COVID-19 pandemic), except for school-related reasons in men. This study can be used as a basis for developing intervention programs for suicide prevention.

Observational epidemiological studies involving foods and nutrients often attract great attention from both the press and the public as they involve substances that are part of the daily lives of millions of individuals. In the digital era, findings of this research can be disseminated to very large audiences almost instantaneously, informing health beliefs and potentially triggering lifestyle changes. In this context, communication of results from observational nutritional epidemiology often involves specific issues that may limit the accuracy of the information ultimately being delivered to the public. In this narrative review we discuss some of these issues, with a special attention to the selective reporting of research studies by the media, the presentation of study findings as if they were free of bias, the reporting of inconsistent study results, and the issues related to the real-life uptake of research findings presented in the press. Collaborative efforts by all stakeholders involved in the dissemination process may help ameliorate this situation, and with this purpose we discuss some innovative approaches that may help reduce these issues.

Background Major challenges in clinical trials of ultra-orphan oncology diseases include limited patient availability and paucity of reliable prior data for estimating the treatment effect and, therefore, determining optimal sample size. Angiosarcoma (AS), a particularly aggressive form of soft tissue sarcoma with an incidence of about 2000 cases per year in the United States and Europe is poorly addressed by current systemic therapies. Pazopanib, an inhibitor of vascular endothelial growth factor receptor (VEGFR) is approved for the treatment of AS, with modest benefit. TRC105 (carotuximab) is a monoclonal antibody to endoglin, an essential angiogenic target highly expressed on proliferating endothelium and both tumor vessels and tumor cells in AS, that has the potential to complement VEGFR tyrosine kinase inhibitors. In a phase I/II study of soft tissue sarcoma, TRC105 combined safely with pazopanib and the combination demonstrated durable complete responses and encouraging progression-free survival (PFS). In addition, there was a suggestion of superior benefit in patients with cutaneous lesions versus those with the non-cutaneous lesions. Patients and methods This article describes the design of a recently initiated phase III trial of TRC105 And Pazopanib versus Pazopanib alone in patients with advanced AngioSarcoma (TAPPAS trial). Given the ultra-orphan status of the disease and the paucity of reliable prior data on PFS or overall survival (end points required for regulatory approval as a pivotal trial), an adaptive design incorporating population enrichment and sample size re-estimation was implemented. The design incorporated regulatory input from the Food and Drug Administration (FDA) and European Medicines Agency and proceeded following special protocol assessment designation by the FDA. Conclusions It is shown that the benefit of the adaptive design as compared with a conventional single-look design arises from the learning and subsequent improvements in power that occur after an unblinded analysis of interim data. Registered on Clinicaltrials.gov NCT02979899.

We study the spatial-temporal pattern of the spread of the 2009 H1N1 influenza virus using a metapopulation model linked by commuting flow based on the reported influenza cases during the early stages of the epidemic in the Republic of Korea. The spatial heterogeneities, such as the local reproductive number and peak time, are investigated at province level. Furthermore, we discuss the effect of early intervention strategies, isolation and commuting restrictions, on the reduction of incidence at each province level. A major finding of this study is that early intervention at the source area of infection is more effective than interventions at the commuting-hub areas if the cost is limited.

Background: Nursing homes are among the most common places of death in many countries. Aim: To determine the quality of dying and end-of-life care of nursing home residents in six European countries. Design: Epidemiological survey in a proportionally stratified random sample of nursing homes. We identified all deaths of residents of the preceding 3-month period. Main outcomes: quality of dying in the last week of life (measured using End-of-Life in Dementia Scales – Comfort Assessment while Dying (EOLD-CAD)); quality of end-of-life care in the last month of life (measured using Quality of Dying in Long-Term Care (QoD-LTC) scale). Higher scores indicate better quality. Setting/participants: Three hundred and twenty-two nursing homes in Belgium, Finland, Italy, the Netherlands, Poland and England. Participants were staff (nurses or care assistants) most involved in each resident’s care. Results: Staff returned questionnaires regarding 1384 (81.6%) of 1696 deceased residents. The End-of-Life in Dementia Scales – Comfort Assessment while Dying mean score (95% confidence interval) (theoretical 14–42) ranged from 29.9 (27.6; 32.2) in Italy to 33.9 (31.5; 36.3) in England. The Quality of Dying in Long-Term Care mean score (95% confidence interval) (theoretical 11–55) ranged from 35.0 (31.8; 38.3) in Italy to 44.1 (40.7; 47.4) in England. A higher End-of-Life in Dementia Scales – Comfort Assessment while Dying score was associated with country ( p = 0.027), older age ( p = 0.012), length of stay ⩾1 year ( p = 0.034), higher functional status ( p Conclusion: The quality of dying and quality of end-of-life care in nursing homes in the countries studied are not optimal. This includes countries with high levels of palliative care development in nursing homes such as Belgium, the Netherlands and England.

International audience; Methodologies of population-based studies on neurological diseases in low-and middle-income countries (LMICs) have not been standardized. The objective of this paper is to provide an overview of the numerous challenges occurring in this context and propose a standard framework for population- based studies in LMICs. We relied on our expertise on few diseases, epilepsy and neurodegenerative disorders.The proposed framework is the result of extensive field experience in tropical LMICs. It ensures that important steps are not forgotten when setting up a study plan. It must remain flexible and be adapted to each situation, to the disease studied, in particular its prevalence, but also to the geography of the study area and the availability of survey technologies

Background Data audits are often evaluated soon after completion, even though the identification of systematic issues may lead to additional data quality improvements in the future. In this study, we assess the impact of the entire data audit process on subsequent statistical analyses. Methods We conducted on-site audits of datasets from nine international HIV care sites. Error rates were quantified for key demographic and clinical variables among a subset of records randomly selected for auditing. Based on audit results, some sites were tasked with targeted validation of high-error-rate variables resulting in a post-audit dataset. We estimated the times from antiretroviral therapy initiation until death and first AIDS-defining event using the pre-audit data, the audit data, and the post-audit data. Results The overall discrepancy rate between pre-audit and audit data (n = 250) across all audited variables was 17.1%. The estimated probability of mortality and an AIDS-defining event over time was higher in the audited data relative to the pre-audit data. Among patients represented in both the post-audit and pre-audit cohorts (n = 18,999), AIDS and mortality estimates also were higher in the post-audit data. Conclusion Though some changes may have occurred independently, our findings suggest that improved data quality following the audit may impact epidemiological inferences.

Objectives To evaluate the postsurgery gingival healing as well as plaque, gingival inflammation and staining levels following the use of a 0.2% chlorhexidine (CHX) solution with or without antidiscoloration system (ADS) and 0.2% hyaluronic acid (HA). Methods Patients undergoing flap surgery at sites with an intact or reduced but healthy periodontium participated in a parallel-arm RCT. After surgery, patients used the assigned mouthrinse (CHX + HA + ADS or CHX) for 21 days. At days 7 and 21, the healing process was evaluated at experimental teeth using a composite index, namely the Gingival Healing Index (GHI). GHI score was obtained as the sum of the scores related to the severity of wound dehiscence (score 1-3) and the profile of the buccal and oral aspects of the papilla (score 1-3). Therefore, GHI ranged from 2 (worst quality of healing) to 6 (optimal quality of healing). Plaque Index (PlI), Gingival Index (GI), angulated bleeding score (AngBS), and tooth and tongue staining were also assessed. Results In both groups, GHI assumed values of 5 or 6 at both days 7 and 21 in ≥50% of patients, and low median values of PlI, GI, AngBS and staining were observed during the 21-day period. Except for a significantly lower GI in CHX group at day 7, no other significant intergroup differences were found. Conclusions Postsurgery plaque control based on either CHX or CHX + HA + ADS mouthrinses results in optimal plaque control and quality of early gingival healing along with limited tooth and tongue staining.

The directed acyclic graph (DAG) is a powerful tool to model the interactions of high-dimensional variables. While estimating edge directions in a DAG often requires interventional data, one can estimate the skeleton of a DAG (i.e., an undirected graph formed by removing the direction of each edge in a DAG) using observational data. In real data analyses, the samples of the high-dimensional variables may be collected from a mixture of multiple populations. Each population has its own DAG while the DAGs across populations may have significant overlap. In this article, we propose a two-step approach to jointly estimate the DAG skeletons of multiple populations while the population origin of each sample may or may not be labeled. In particular, our method allows a probabilistic soft label for each sample, which can be easily computed and often leads to more accurate skeleton estimation than hard labels. Compared with separate estimation of skeletons for each population, our method is more accurate and robust to labeling errors. We study the estimation consistency for our method, and demonstrate its performance using simulation studies in different settings. Finally, we apply our method to analyze gene expression data from breast cancer patients of multiple cancer subtypes.

Background Establishing mechanisms of disease causation in neurodegenerative diseases has long seemed to be beyond the pale of traditional epidemiological tools. Establishing a plausible mechanism for initiation of amyotrophic lateral sclerosis (ALS) has appeared a particularly elusive goal. This review shows that a likely mechanism for ALS initiation may be inferred by applying classical methods of epidemiological inference. Key points Advances in characterizing the biology of ALS suggest that most cases of ALS are cortically-generated, part of the ALS-FTD spectrum, with focal onset and spread by contiguity within the motor super-network. Evidence-based methods identified the most credible exogenous risk factor – smoking. AB Hill's nine viewpoints to inferring causation from association were invoked. The most likely mechanism consistent with smoking being a risk factor for ALS was inferred: cumulative DNA damage, akin to cumulative somatic mutations in carcinogenesis. Focal onset supports the concept that these changes, occurring in a single cell, may trigger the cascade leading to clinical ALS. The plausibility of this mechanism was affirmed by its coherence/consistency with other observations in sporadic, familial and western Pacific ALS. Conclusion Application of traditional epidemiological reasoning suggests that cumulative DNA damage may contribute to disease onset in ALS.

Risk difference is a relevant effect measure in epidemiologic research. Although it is well known that when there are few events per confounder, logistic regression is not suitable for confounding control, it is not clear how many events per confounder are required for valid estimation of risk difference using linear binomial models. Because the maximum likelihood method has a convergence problem, we investigated the number of events per confounder necessary to validly estimate risk difference using modified least-squares regression in a simulation. We simulated 864 scenarios, according to the number of confounders (2-20), the number of events per confounder (2-12), marginal risk (0.5%-40%), exposure proportion (20% and 40%), and 3 sizes of risk difference. Our simulation showed that modified least-squares regression provided unbiased risk difference-regardless of the number of events per confounder-and reliable confidence intervals when more than 5 events were expected in the exposed and in the unexposed, irrespective of the number of events per confounder. We illustrated the modified least-squares regression analysis using perinatal epidemiologic data. Modified least-squares regression is considered to be a useful analytical tool for rare binary outcomes relative to the number of confounders.

Background HIV risk remains unacceptably high among adolescent girls and young women (AGYW) in southern and eastern Africa, reflecting structural and social inequities that drive new infections. In 2015, PEPFAR (the United States President’s Emergency Plan for AIDS Relief) with private-sector partners launched the DREAMS Partnership, an ambitious package of interventions in 10 sub-Saharan African countries. DREAMS aims to reduce HIV incidence by 40% among AGYW over two years by addressing multiple causes of AGYW vulnerability. This protocol outlines an impact evaluation of DREAMS in four settings. Methods To achieve an impact evaluation that is credible and timely, we describe a mix of methods that build on longitudinal data available in existing surveillance sites prior to DREAMS roll-out. In three long-running surveillance sites (in rural and urban Kenya and rural South Africa), the evaluation will measure: (1) population-level changes over time in HIV incidence and socio-economic, behavioural and health outcomes among AGYW and young men (before, during, after DREAMS); and (2) causal pathways linking uptake of DREAMS interventions to ‘mediators’ of change such as empowerment, through to behavioural and health outcomes, using nested cohort studies with samples of ~ 1000–1500 AGYW selected randomly from the general population and followed for two years. In Zimbabwe, where DREAMS includes an offer of pre-exposure HIV prophylaxis (PrEP), cohorts of young women who sell sex will be followed for two years to measure the impact of ‘DREAMS+PrEP’ on HIV incidence among young women at highest risk of HIV. In all four settings, process evaluation and qualitative studies will monitor the delivery and context of DREAMS implementation. The primary evaluation outcome is HIV incidence, and secondary outcomes include indicators of sexual behavior change, and social and biological protection. Discussion DREAMS is, to date, the most ambitious effort to scale-up combinations or ‘packages’ of multi-sectoral interventions for HIV prevention. Evidence of its effectiveness in reducing HIV incidence among AGYW, and demonstrating which aspects of the lives of AGYW were changed, will offer valuable lessons for replication. Electronic supplementary material The online version of this article (10.1186/s12889-018-5789-7) contains supplementary material, which is available to authorized users.

Substantial progress has recently been made in optimizing the management of cancer patients, resulting in major gains in survival and quality of life. Much of this progress has resulted from the serial testing of promising treatment strategies, typically using prospective randomized controlled trials to compare outcomes achieved with the new approach versus the current standard(s) of care. However, there is an ever-expanding list of important questions that are difficult to investigate, particularly with respect to determining the optimal sequencing and combination of proven active agents. With the rapidly growing list of clinical, pathologic and molecular characteristics that promise to predict treatment benefit and/or risk for defined patient subsets, many new questions regarding how best to personalize our approach to treatment selection are emerging. These questions can be investigated in the context of registry-based randomized clinical trials. Recently, the potential of registry-based randomized clinical trials was demonstrated in cardiology, highlighting the ability to rapidly recruit large numbers of patients to a trial addressing an important clinical question, with minimal cost and high external validity. In this review, we discuss the challenges and limitations of conventional clinical trials in multidisciplinary cancer care, describe the potential advantages of registry-based randomized trials, and highlight several registry-based oncology studies that are already underway to demonstrate the feasibility of this approach.

BACKGROUND Androgen Deficiency in Aging Male (ADAM) questionnaire is increasingly popular for the evaluation of testosterone deficiency (TD) in Sub-Saharan African men with type 2 diabetes mellitus (T2DM). However, its reliability in this population is unknown. OBJECTIVE To evaluate the reliability of the ADAM questionnaire for the clinical detection of testosterone deficiency in Sub-Saharan African men with T2DM. METHODS Total testosterone < 8nmol/L was used as gold standard for diagnosis of TD in a crosssectional survey of 200 males with T2DM aged 30-69 years. Participants also completed the Saint Louis University ADAM questionnaire whereby TD was diagnosed by a "yes" answer to question 1 (reduced libido) or 7 (erectile dysfunction) or any other three questions. The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and overall accuracy of the ADAM tool were computed. RESULTS The mean age of the participants was 58.0 ± 8.8 years. 142 subjects (71.0%) had TD based on the ADAM questionnaire. However, TD was biochemically confirmed in 59 subjects (29.5%). ADAM questionnaire rendered sensitivity of 88.1%, specificity of 44.7%, PPV of 50.0%, NPV of 85.7% and accuracy of 61.4%. Low libido alone had better specificity (75.5%) and accuracy (73.2%) than the entire questionnaire. CONCLUSION Despite an impressive sensitivity, the low specificity and overall accuracy of the ADAM questionnaire makes it unreliable for the detection of AD in Sub-Saharan African men with type 2 DM. However, presence of a sustained low libido appears to be a reliable pointer to underlying testosterone deficiency requiring biochemical confirmation.

Measures of causal effects play a central role in epidemiology. A wide range of measures exist, which are designed to give relevant answers to substantive epidemiological research questions. However, due to mathematical convenience and software limitations most studies only report odds ratios for binary outcomes and hazard ratios for time-to-event outcomes. In this paper we show how logistic regression models and Cox proportional hazards regression models can be used to estimate a wide range of causal effect measures, with the R-package stdReg. For illustration we focus on the attributable fraction, the number needed to treat and the relative excess risk due to interaction. We use two publicly available data sets, so that the reader can easily replicate and elaborate on the analyses. The first dataset includes information on 487 births among 188 women, and the second dataset includes information on 2982 women diagnosed with primary breast cancer.

International audience; Background - In occupational epidemiology, a male-centered perspective often predominates. We aimed to describe current research practices in terms of gender consideration at different stages of epidemiological studies. Methods - A systematic review of occupational lung cancer publications indexed in PubMed was conducted over the period 2003-2014. Articles were described according to the sex composition of their study sample. Results - In 243 studies, 7 (3%) were women-only, 101 (41%) were mixed, with a disproportionate men-to-women ratio (P50 = 3.5; P75 = 12.4). A shift was observed from mixed and unspecified source populations to men-only final samples. Our results also suggest implicit generalization of results from men-only studies, a lack of tests of interaction and often unjustified sex-adjustment for mixed studies. Conclusions - The lower proportion of women in studies cannot be fully explained by their under-representation in the target populations, since there were large numbers of women among both potentially exposed workers and patients diagnosed with lung cancer.

INTRODUCTION: Although infrequently recorded in electronic health records (EHR), measures of SES are essential to describe health inequalities and account for confounding in epidemiologic research. Medical Assistance (i.e., Medicaid) is often used as a surrogate for SES, but correspondence between conventional SES and Medical Assistance has been insufficiently studied. METHODS: Geisinger Clinic EHR data from 2001 to 2014 and a 2014 questionnaire were used to create six SES measures: EHR-derived Medical Assistance and proportion of time under observation on Medical Assistance; educational attainment, income, and marital status; and area-level poverty. Analyzed in 2016–2017, associations of SES measures with obesity, hypertension, type 2 diabetes, chronic rhinosinusitus, fatigue, and migraine headache were assessed using weighted age- and sex-adjusted logistic regression. RESULTS: Among 5,550 participants (interquartile range, 39.6–57.5 years, 65.9% female), 83% never used Medical Assistance. All SES measures were correlated (Spearman’s p≤0.4). MA was significantly associated with all six health outcomes in adjusted models. For example, the OR for prevalent type 2 diabetes associated with Medical Assistance was 1.7 (95% CI=1.3, 2.2); the OR for high school versus college graduates was 1.7 (95% CI=1.2, 2.5). Medical Assistance was an imperfect proxy for SES: associations between conventional SES measures and health were attenuated

The self-controlled tree-temporal scan statistic—a new signal-detection method—can evaluate whether any of a wide variety of health outcomes are temporally associated with receipt of a specific vaccine, while adjusting for multiple testing. Neither health outcomes nor postvaccination potential periods of increased risk need be prespecified. Using US medical claims data in the Food and Drug Administration’s Sentinel system, we employed the method to evaluate adverse events occurring after receipt of quadrivalent human papillomavirus vaccine (4vHPV). Incident outcomes recorded in emergency department or inpatient settings within 56 days after first doses of 4vHPV received by 9- through 26.9-year-olds in 2006–2014 were identified using International Classification of Diseases, Ninth Revision, diagnosis codes and analyzed by pairing the new method with a standard hierarchical classification of diagnoses. On scanning diagnoses of 1.9 million 4vHPV recipients, 2 statistically significant categories of adverse events were found: cellulitis on days 2–3 after vaccination and “other complications of surgical and medical procedures” on days 1–3 after vaccination. Cellulitis is a known adverse event. Clinically informed investigation of electronic claims records of the patients with “other complications” did not suggest any previously unknown vaccine safety problem. Considering that thousands of potential short-term adverse events and hundreds of potential risk intervals were evaluated, these findings add significantly to the growing safety record of 4vHPV.

Despite recent successes in understanding the genetics of Parkinson's disease (PD), the causes of late-onset sporadic PD remain elusive. Many of the epidemiologic findings on PD etiology have been challenged by alternative explanations such as reverse causation. This is mainly because PD often takes decades to develop before it can be diagnosed late in life. Convincing evidence shows that this prodromal stage of PD is characterized by various prodromal symptoms such as olfactory impairment and rapid-eye-movement sleep behavior disorder (RBD). As they likely reflect PD pathogenesis years, if not decades, before nigrostriatal involvement, research on these symptoms may represent an unprecedented opportunity to dissect the etiology of PD. Using PD prodromal symptoms as intermediate phenotypes, we may be able to identify factors that contribute to the development of these symptoms and factors that modify their progression to clinical PD. Further, this line of research will also enable examinations of novel etiological hypotheses of PD development such as the microbiome and prion hypotheses. In this article, the author used olfactory impairment and RBD as examples to illustrate the promises and challenges of epidemiologic research on prodromal symptoms to understand PD etiology.

Collaborative study designs (CSDs) that combine individual-level data from multiple independent contributing studies (ICSs) are becoming much more common due to their many advantages: increased statistical power through large sample sizes; increased ability to investigate effect heterogeneity due to diversity of participants; cost-efficiency through capitalizing on existing data; and ability to foster cooperative research and training of junior investigators. CSDs also present surmountable political, logistical and methodological challenges. Data harmonization may result in a reduced set of common data elements, but opportunities exist to leverage heterogeneous data across ICSs to investigate measurement error and residual confounding. Combining data from different study designs is an art, which motivates methods development. Diverse study samples, both across and within ICSs, prompt questions about the generalizability of results from CSDs. However, CSDs present unique opportunities to describe population health across person, place and time in a consistent fashion, and to explicitly generalize results to target populations of public health interest. Additional analytic challenges exist when analysing CSD data, because mechanisms by which systematic biases (e.g. information bias, confounding bias) arise may vary across ICSs, but multidisciplinary research teams are ready to tackle these challenges. CSDs are a powerful tool that, when properly harnessed, permits research that was not previously possible.

Brazil is experiencing among the world’s fastest demographic aging worldwide. This demographic transition is occurring in a context of few resources and great social inequalities. The Brazilian Longitudinal Study of Aging (ELSI-Brazil) is a nationally representative study of 9,412 people aged 50 years or older, residing in 70 municipalities across the 5 Brazilian regions. ELSI-Brazil allows investigations of the aging process, its health, psychosocial and economic determinants, and societal consequences. The baseline examination (2015–2016) included detailed household and individual interviews and physical measurements (blood pressure, anthropometry, grip strength, and timed walk and balance tests). Blood tests and sample storage were performed in a subsample of study participants. Subsequent waves are planned for every 3 years. The study adopts a conceptual framework common to other large-scale longitudinal studies of aging in the world, such as the Health and Retirement Study, allowing cross-national comparisons. The goal of ELSI-Brazil is not only to build an understanding of aging in a large, Western, middle-income country in a rapid demographic transition but also to provide scientific data to support and study policy changes that may affect older adults. We describe the methodology of the study and some descriptive results of the baseline survey.

In this MiniReview, we provide general considerations for the planning and conduct of pharmacoepidemiological studies of associations between drug use and cancer development. We address data sources, study design, assessment of drug exposure, ascertainment of cancer outcomes, confounder adjustment and future perspectives. Aspects of data sources include assessment of complete history of drug use and data on dose and duration of drug use, allowing estimates of cumulative exposure. Outcome data from formal cancer registries are preferable, but cancer data from other sources, for example, patient or pathology registries, medical records or claims are also suitable. The two principal designs for observational studies evaluating drug-cancer associations are the cohort and case-control designs. A key challenge in studies of drug-cancer associations is the exposure assessment due to the typically long period of cancer development. We present methods to examine early and late effects of drug use on cancer development and discuss the need for employing 'lag-time' in order to avoid reverse causation. We emphasize that a new-user study design should always be considered. We also underline the need for 'dose-response' analyses, as drug-cancer associations are likely to be dose-dependent. Generally, studies of drug-cancer associations should explore risk of site-specific cancer, rather than cancer overall. Additional differentiation may also be crucial for organ-specific cancer with various distinct histological subtypes (e.g., lung or ovary cancer). We also highlight the influence of confounding factors and discuss various methods to address confounding, while emphasizing that the choices of methods depend on the design and specific objectives of the individual study. In some studies, use of active comparator(s) may be preferable. Pharmacoepidemiological studies of drug-cancer associations are expected to evolve considerably in the coming years, due to the increasing availability of long-term data on drug exposures and cancer outcomes, the increasing conduct of multinational studies, allowing studies of rare cancers and subtypes of cancer, and methodological improvements specifically addressing cancer and other long-term outcomes.

The Kelly West Award for Outstanding Achievement in Epidemiology is presented in honor of the memory of Kelly M. West, widely regarded as the “father of diabetes epidemiology.” Harry Keen described West as characterized by “generosity of spirit, deeply human and humorous, deliberate of address, modest, conciliatory and untiringly persevering. Few people have done so much to change the landscape of diabetes” (1). The award and lecture recognize a leading epidemiologist in the field of diabetes. Dana Dabelea, MD, PhD, received this award at the American Diabetes Association’s 77th Scientific Sessions, 9–13 June 2017, in San Diego, CA. She presented the Kelly West Award Lecture, “Diabetes in Youth—Looking Backwards to Inform the Future,” on Sunday, 11 June 2017.

Occupational epidemiology studies in the 1980s and 1990s demonstrated a beneficial effect of physically active employment on risks of premature death,1 with HR of ~1.50 for sedentary employees (see the online supplement for a detailed discussion). However, that accepted wisdom was disputed in a recent meta-analysis which claimed that male employees faced ‘detrimental health consequences associated with high-level occupational activity, even after adjusting for relevant factors’.2 Such a view challenges existing physical activity guidelines and poses the intriguing problem why occupational activity might be bad for men but not women. Here the author scrutinises the choice of articles for this meta-analysis, the characteristics of apparently hazardous activity and potential confounding by covariates, focusing on the male data. Possible reasons why women do not show an occupational paradox are discussed in the online supplemental material. ### Supplementary file [bjsports-2018-100344supp001.docx] Articles for the meta-analysis were drawn from 13 countries, but 5 of 16 were written by the study authors, leading to some similarities in the determination of active individuals and choice of co-variates. Moreover, participants in 5 of 16 studies lived around Copenhagen, with a potential for subject overlap; the author does not believe that this was evaluated. Studies provided ~30 to 5668 male …

This study examined the associations between asymmetric handgrip strength (HGS) and multimorbidity in American adults. Secondary analyses of data from persons aged at least 40 years from the 2011–2012 and 2013–2014 waves of the National Health and Nutrition Examination Survey were conducted. A handheld dynamometer collected HGS on each hand and persons with a strength imbalance >10% between hands were classified as having asymmetric HGS. Adults with the presence of ≥2 of the following conditions had multimorbidity: cardiovascular disease, chronic obstructive pulmonary disease, chronic kidney disease, asthma, arthritis, cancer, obesity, stroke, hypertension, high cholesterol, and diabetes. Of the n = 3483 participants included, n = 2700 (77.5%) had multimorbidity. A greater proportion of adults with multimorbidity had HGS asymmetry (n = 1234 (45.7%)), compared to persons living without multimorbidity (n = 314 (40.1%); p < 0.05). Relative to individuals without asymmetry, adults with asymmetric HGS had 1.31 (95% confidence interval (CI): 1.03–1.67) greater odds for multimorbidity. Moreover, persons with HGS asymmetry had 1.22 (CI: 1.04–1.44) greater odds for accumulating morbidities. Asymmetric strength, as another indicator of diminished muscle function, is linked to chronic morbidity status. Healthcare providers should recommend healthy behaviors for reducing asymmetries to improve muscle function and mitigate morbidity risk after completing asymmetry screenings.

Studies often combine several events, for example, death or myocardial infarction or stroke, into a single study outcome. This is called a composite endpoint. Composite endpoints make doing trials easier by reducing the sample size or follow-up period required to demonstrate the effectiveness of an intervention. However, interpreting the results of composite endpoints can be confusing. To avoid misleading conclusions about the effectiveness of an intervention, it is important for readers of studies reporting a composite endpoint to ascertain that the clinical importance, the frequency of events, and the effect of the intervention on each component of the composite endpoint are similar.