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Background: Concerns exist as to whether the allocation of resources in clinical research is aligned with public health needs. We evaluated the alignment between the effort of clinical research through the conduct of randomized controlled trials (RCTs) and health needs measured as the burden of diseases for all regions and a broad range of diseases., Methods: We grouped countries into seven regions and diseases into 27 groups. We mapped all RCTs initiated between 2006 and 2015 that were registered at the WHO International Clinical Trials Registry Platform to regions and diseases. The burden of diseases in 2005 was mapped as disability-adjusted life years (DALYs), based on the 2010 Global Burden of Diseases study. Within regions, we defined a research gap when the proportion of RCTs concerning a disease in the region was less than half the relative burden of the disease., Results: We mapped 117,180 RCTs planning to enroll 42.6 million patients and 2,220 million DALYs. In high- versus non-high-income countries, 130.9 versus 6.9 RCTs per million DALYs were conducted. We did not identify any research gap in high-income countries. We identified research gaps for all other regions. In particular, for Sub-Saharan Africa, we identified research gaps for common infectious diseases (CID) and neonatal disorders (ND): 5.8% (95% uncertainty interval 4.7-6.9) and 2.0% (0.9-4.5) of RCTs in Sub-Saharan Africa concerned CID and ND, although these diseases represented 22.9% and 11.6% of the burden in the region, respectively. For South Asia, we identified research gaps for the same two groups of diseases., Conclusions: In non-high-income regions, the conduct of RCTs was misaligned with the distribution of major causes of burden, in particular infectious diseases and neonatal disorders in Sub-Saharan Africa and South Asia., (Copyright © 2018 Elsevier Inc. All rights reserved.)

An empiric perspective on what epidemiology has studied over time might inform discussions about future directions for the discipline. We aimed to identify the main areas of epidemiologic inquiry and determine how they evolved over time in 5 high-impact epidemiologic journals. We analyzed the titles and abstracts of 20,895 articles that were published between 1974 and 2013. In 5 time periods that reflected approximately equal numbers of articles, we identified the main topics by clustering terms based on co-occurrence. Infectious disease and cardiovascular disease epidemiology were the prevailing topics over the 5 periods. Cancer epidemiology was a major topic from 1974 to 2001 but disappeared thereafter. Nutritional epidemiology gained relative importance from 1974 to 2013. Environmental epidemiology appeared during 1996-2001 and continued to be important, whereas 2 clusters related to methodology and meta-analysis in genetics appeared during 2008-2013. Several areas of epidemiology, including injury or psychiatric epidemiology, did not make an appearance as major topics at any time. In an ancillary analysis of 6 high-impact general medicine journals, we found patterns of epidemiologic articles that were overall consistent with the findings in epidemiologic journals. This metaknowledge investigation allowed identification of the dominant topics in and conversely those that were absent from 5 major epidemiologic journals. We discuss implications for the field., (© The Author 2015. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Résumé: Les résultats des essais cliniques randomisés sont parfois difficiles à appliquer chez tous les patients parce que l'interprétation des résultats n'est pas univoque. Il peut en effet exister une hétérogénéité dans le résultat, 1) soit parce que l'effet du traitement varie en fonction de caractéristiques des patients (sous-groupes), 2) soit parce que les auteurs ont utilisé un critère de jugement combinant plusieurs composantes individuelles (critère composite) et que l'effet du traitement varie entre composantes. Cette note synthétise les problèmes inhérents aux analyses en sous-groupes (manque de puissance, multiplicité des tests, et défaut de comparabilité des groupes de traitement) et à l'utilisation de critères composites (hétérogénéité qualitative ou quantitative et difficultés d'interprétation en cas d'événements rares). Elle indique aussi les recommandations d'analyse et de présentation des résultats. The interpretation of randomized clinical trials may be challenging and their results are therefore sometimes difficult to generalize. Subgroup analyses and the use of composite outcomes are two common issues in clinical trials. This review addresses how to use, interpret, and report subgroup analyses and composite outcomes, focusing on the main analytic challenges. In subgroup analyses, the main issues are lack of statistical power, confounding effects, and multiplicity of tests. Composite outcomes are subject to qualitative and quantitative heterogeneity that may be difficult to interpret and translate into clinical practice. Higher event rates and larger treatment effects associated with less important components may result in misleading impressions of the impact of treatment. [ABSTRACT FROM AUTHOR]

Background: One of the mechanisms suggested to link physical activity (PA) to favorable brain health is through stimulation of neural growth factors such as brain-derived neurotrophic factor (BDNF). Acute bouts of PA stimulate circulating BDNF levels.Objective: In this investigation, we assessed whether habitual, accelerometer-measured PA levels were related to circulating BDNF levels in a middle-aged cohort.Methods: In the Framingham Heart Study Third Generation cohort, 1,769 participants provided reliable accelerometry data and were not missing BDNF measurement or platelet counts. In a cross-sectional analysis, using multivariable regression, we related PA measures to serum BDNF levels, adjusting for age, sex, smoking status, platelet count, depression status, and accelerometer wear time.Results: Our study participants (mean age 47±9 years, 50.8% women) spent an average of 22.3 mins/day in moderate-to-vigorous (MV)PA. Most PA variables (steps, MVPA, light activity, and sedentary time) were not related to BDNF levels (p > 0.05). We observed a non-linear trend, where 15-50 mins/week vigorous activity was associated with lower BDNF compared to those with 0 min vigorous activity (β= -0.049±0.024, p = 0.05), but with no significant associations at lower or higher vigorous activity levels. In smokers, MVPA was also associated with lower BDNF levels (β= -0.216±0.079, p = 0.01).Conclusion: Our study reveals that circulating BDNF is not chronically elevated in individuals with higher levels of habitual PA in middle-aged adults from the community and may even be chronically suppressed with higher PA in subgroups, including current smokers. These results do not contradict previous studies demonstrating that circulating BDNF rises acutely after PA. [ABSTRACT FROM AUTHOR]

Background: P-wave signal-averaged electrocardiography (P-SAECG) quantifies atrial electrical activity. P-SAECG measures and their clinical correlates and heritability have had limited characterization in community-based cohorts.Objective: The purpose of this study was to (1) establish reference values; (2) identify clinical risk factors associated with P-SAECG; and (3) estimate genetic heritability for P-SAECG traits.Methods: We performed P-SAECG in 2 generations of Framingham Heart Study participants. We performed backward elimination regression models to assess associations of clinical factors with each SAECG trait (P-wave [PW] duration, root mean square voltage in terminal 40 ms [RMS40], terminal 30 ms RMS30, terminal 20 ms RMS20, RMS PW, and PW integral). We estimated the adjusted genetic heritability of P-SAECG measures using the Sequential Oligogenic Linkage Analysis Routines (SOLAR) program.Results: We included 4307 participants (age 55 ± 14 years; 56% female). The reference values were derived from 1752 participants without cardiovascular risk factors. Median (2.5th percentile; 97.5th percentile) total PW duration was 118 ms (93; 146) in women and 128 ms (104; 158) in men in the reference sample, and 121 ms (94; 151) in women and 129 ms (103; 159) in the entire study cohort (broad sample). In the broad sample, after adjusting for age and sex, total PW duration was positively associated with height, weight, prevalent heart failure, history of atrial fibrillation (AF), and atrioventricular node blockers, and negatively associated with smoking, waist circumference, heart rate, and diabetes. The estimated heritability of P-SAECG traits was moderate, ranging from 11.9% for RMS30 to 24.9% for PW integral.Conclusion: P-SAECG traits are associated with multiple AF-related risk factors and are moderately heritable. [ABSTRACT FROM AUTHOR]

Background: Advancing age is a prominent risk factor for atrial fibrillation (AF). Shorter telomere length is a biomarker of biological aging, but the link between shorter telomere length and increased risk of AF remains unclear. We examined the association between shorter leukocyte telomere length (LTL) and incident AF. Methods and Results: We included AF‐free participants from the observational Framingham Heart Study Offspring cohort from 1995 to 1998, who had LTL measurements. We examined the association between baseline LTL and incident AF with multivariable Cox models adjusted for age, sex, current smoking, height, weight, systolic and diastolic blood pressure, use of antihypertensive medication, diabetes mellitus, history of myocardial infarction, and history of heart failure. The study sample comprised 1143 AF‐free participants (52.8% women), with mean age of 60±8 years. The mean LTL at baseline was 6.95±0.57 kb. During 15.1±4.2 years mean follow‐up, 184 participants (64 women) developed AF. Chronological age was associated with increased risk of AF (hazard ratio per 10‐year increase, 2.16; 95% confidence interval, 1.71–2.72). There was no significant association between LTL and incident AF (hazard ratio per 1 SD decrease LTL, 1.01; 95% confidence interval, 0.86–1.19). Our study was observational in nature; hence, we could not exclude residual confounding and we were unable to establish causal pathways. Conclusions: In our moderate‐sized community‐based cohort, we did not find evidence for a significant association between LTL and risk of incident AF.

Context: Older adults are underrepresented in clinical research. To assess therapeutic efficacy in older patients, some randomized controlled trials (RCTs) include older adults only. Objective: To compare treatment effects between RCTs including older adults only (elderly RCTs) and RCTs including all adults (adult RCTs) by a meta-epidemiological approach. Methods: All systematic reviews published in the Cochrane Library (Issue 4, 2011) were screened. Eligible studies were meta-analyses of binary outcomes of pharmacologic treatment including at least one elderly RCT and at least one adult RCT. For each meta-analysis, we compared summary odds ratios for elderly RCTs and adult RCTs by calculating a ratio of odds ratios (ROR). A summary ROR was estimated across all meta-analyses. Results: We selected 55 meta-analyses including 524 RCTs (17% elderly RCTs). The treatment effects differed beyond that expected by chance for 7 (13%) meta-analyses, showing more favourable treatment effects in elderly RCTs in 5 cases and in adult RCTs in 2 cases. The summary ROR was 0.91 (95% CI, 0.77–1.08, p = 0.28), with substantial heterogeneity (I2 = 51% and τ2 = 0.14). Sensitivity and subgroup analyses by type-of-age RCT (elderly RCTs vs RCTs excluding older adults and vs RCTs of mixed-age adults), type of outcome (mortality or other) and type of comparator (placebo or active drug) yielded similar results. Conclusions: The efficacy of pharmacologic treatments did not significantly differ, on average, between RCTs including older adults only and RCTs of all adults. However, clinically important discrepancies may occur and should be considered when generalizing evidence from all adults to older adults. [ABSTRACT FROM AUTHOR]

Background: New electronic cohort (e-Cohort) study designs provide resource-effective methods for collecting participant data. It is unclear if implementing an e-Cohort study without direct, in-person participant contact can achieve successful participation rates. Objective: The objective of this study was to compare 2 distinct enrollment methods for setting up mobile health (mHealth) devices and to assess the ongoing adherence to device use in an e-Cohort pilot study. Methods: We coenrolled participants from the Framingham Heart Study (FHS) into the FHS–Health eHeart (HeH) pilot study, a digital cohort with infrastructure for collecting mHealth data. FHS participants who had an email address and smartphone were randomized to our FHS-HeH pilot study into 1 of 2 study arms: remote versus on-site support. We oversampled older adults (age ≥65 years), with a target of enrolling 20% of our sample as older adults. In the remote arm, participants received an email containing a link to enrollment website and, upon enrollment, were sent 4 smartphone-connectable sensor devices. Participants in the on-site arm were invited to visit an in-person FHS facility and were provided in-person support for enrollment and connecting the devices. Device data were tracked for at least 5 months. Results: Compared with the individuals who declined, individuals who consented to our pilot study (on-site, n=101; remote, n=93) were more likely to be women, highly educated, and younger. In the on-site arm, the connection and initial use of devices was ≥20% higher than the remote arm (mean percent difference was 25% [95% CI 17-35] for activity monitor, 22% [95% CI 12-32] for blood pressure cuff, 20% [95% CI 10-30] for scale, and 43% [95% CI 30-55] for electrocardiogram), with device connection rates in the on-site arm of 99%, 95%, 95%, and 84%. Once connected, continued device use over the 5-month study period was similar between the study arms. Conclusions: Our pilot study demonstrated that the deployment of mobile devices among middle-aged and older adults in the context of an on-site clinic visit was associated with higher initial rates of device use as compared with offering only remote support. Once connected, the device use was similar in both groups. [ABSTRACT FROM AUTHOR]

The article reports a study which investigated whether trial sample size influence treatment effect estimates within meta-analyses. The results revealed that treatment effect estimates differ within meta-analyses based on trial sample size. Small trials rather than large trials report large treatment benefits within one meta-analysis.

Background: There is conflicting evidence regarding the association between atrial fibrillation and the risk of subsequent fractures.Methods: We included participants aged 45 years or older from the Framingham Heart Study Offspring, Third-Generation, New Offspring Spouse, Omni 1, and Omni 2 cohorts. We prespecified analyzing index age 65 years as our primary analysis; we repeated analyses for index ages 45, 55, and 75 years. The primary outcome was any incident bone fracture, except finger, toe, foot, skull, and facial fractures. We assessed the association between time-varying atrial fibrillation and subsequent fractures by an illness-death model that accounted for the competing risk of death. We estimated hazard ratios (HR) adjusted for age, sex, body mass index, smoking, diabetes, alcohol intake, and prior fracture.Results: We included 3403 participants (mean age of 68 years, 53.3% female) in the analysis at index age 65 years and above. In all, 525 (15%) participants suffered incident fractures during follow-up (median 12.5 years). The HR between atrial fibrillation and subsequent fracture was 1.37; 95% confidence interval (CI), 1.06-1.79. There was no evidence of effect modification by sex (HR 1.55; 95% CI, 1.06-2.26 in men; HR 1.22; 95% CI, 0.84-1.77 in women; interaction P value .27). Results were consistent at other index ages.Conclusion: Atrial fibrillation was associated with increased risk of incident fracture in the community-based Framingham Heart Study. [ABSTRACT FROM AUTHOR]

Background: The long-term probability of developing atrial fibrillation (AF) considering genetic predisposition and clinical risk factor burden is unknown.Methods: We estimated the lifetime risk of AF in individuals from the community-based Framingham Heart Study. Polygenic risk for AF was derived using a score of ≈1000 AF-associated single-nucleotide polymorphisms. Clinical risk factor burden was calculated for each individual using a validated risk score for incident AF comprised of height, weight, systolic and diastolic blood pressure, current smoking status, antihypertensive medication use, diabetes mellitus, history of myocardial infarction, and history of heart failure. We estimated the lifetime risk of AF within tertiles of polygenic and clinical risk.Results: Among 4606 participants without AF at 55 years of age, 580 developed incident AF (median follow-up, 9.4 years; 25th-75th percentile, 4.4-14.3 years). The lifetime risk of AF >55 years of age was 37.1% and was substantially influenced by both polygenic and clinical risk factor burden. Among individuals free of AF at 55 years of age, those in low-polygenic and clinical risk tertiles had a lifetime risk of AF of 22.3% (95% confidence interval, 15.4-9.1), whereas those in high-risk tertiles had a risk of 48.2% (95% confidence interval, 41.3-55.1). A lower clinical risk factor burden was associated with later AF onset after adjusting for genetic predisposition (P<0.001).Conclusions: In our community-based cohort, the lifetime risk of AF was 37%. Estimation of polygenic AF risk is feasible and together with clinical risk factor burden explains a substantial gradient in long-term AF risk. [ABSTRACT FROM AUTHOR]

Background: Prior proteomics analyses on the risk of incident AF screened for limited numbers of proteins. We report the use of single-stranded DNA-based aptamers as affinity agents to screen for 1373 proteins and identify novel biomarkers that are associated with risk of incident AF in a prospective cohort study. Methods: We studied the Framingham Heart Study Offspring Cohort participants who attended exam 5 from 1991 to 1995. We ascertained AF or atrial flutter on ECG at routine research visits and from clinical records review. Participants with prevalent AF (n=28) were excluded. Plasma protein levels were measured by the SOMAscan proteomic profiling platform, which uses single-stranded DNA-based aptamers to capture conformational protein epitopes. We used robust inference for the Cox proportional hazards models to relate each protein level with incident AF. In addition, we examined the association between AF-related genetic loci and circulating protein levels. Results: Our study included 1,885 participants (mean age 55±10 years, 54% women) who had proteomic profiles measured. A total of 349 participants developed AF during follow-up (mean follow-up 18.3 years). We found 8 proteins that were significantly associated with incident AF after adjusting for age, sex, and technical covariates and correction for multiple testing (p <0.05/1373=3.64x10-5). After additional adjustments for clinical factors (smoking, height, weight, systolic and diastolic blood pressures, antihypertensive treatment, diabetes mellitus, prevalent myocardial infarction, prevalent heart failure) associated with AF, ADAMTS13 and NT-proBNP (HR, 0.78; 95% CI, 0.70-0.88; and 1.44; 95% CI, 1.22-1.70, respectively; p <3.64x10-5 for both) remained significantly associated with the risk of incident AF. None of the 8 proteins were associated AF-related genetic loci previously identified in recent genome-wide association studies. Conclusions: In our proteomic analysis of longitudinal community-based sample, we identified 8 proteins associated with risk of incident AF after adjustment for age and sex. Future studies are needed to identify whether they are mechanistically related to AF development and whether they are clinically useful for identification of future AF risk. [ABSTRACT FROM AUTHOR]

Background: Recent evidence suggests that dementia appears linked to subclinical vascular changes, which may be attenuated by physical activity. The Physical Activity Guidelines for Americans (PA-Guidelines) are currently set at 150 min of moderate-to-vigorous physical activity (MVPA) per week, as a target for adults to achieve favorable health outcomes, but make no specific recommendations for prevention of dementia. Many Americans fall well below the PA-Guidelines. The aim of this investigation was to determine whether there is a continuum of lower intensities and volumes of physical activity associated with healthy brain aging even in individuals not meeting the PA-Guidelines. Methods: We included Framingham Heart Study (FHS) participants who wore an Actical accelerometer for ≥3 valid days (>10 h wear time per day) on their right hip during the most recent cohort examinations and completed brain magnetic resonance imaging (MRI) an average of 1.7 (±0.9) years later (n=2534): Offspring exam 9, Third Generation exam 2, and corresponding examinations of the Omni cohorts. Participants were excluded from this analysis if they had prevalent stroke or dementia (n=63) or met the 150 min MVPA per week PA-Guidelines (n=1158). Non-wear time (defined as 60 min of zero-counts, with two interruptions allowed) was removed. Sedentary time (<200 counts/min, <1.5 metabolic equivalents [METs]) and light activity (201-1485 counts/min, 1.5-3 METs) were only accumulated during 6 am-10 pm, were represented as proportions of wear time to account for differences in wear time among participants, and standardized to a 16 h day. MVPA (>1486 counts/min, ≥3 METs) and steps were accumulated at any time of day. The relations of physical activity measures to brain MRI measures were assessed using multivariable linear regression. Results: More than 53% of FHS participants did not meet the PA-Guidelines for MVPA during their last exam, and were thus included in this investigation (n=1313, 56 [±14] years old, 60% women). These participants took an average of 6149 [±3079] steps, spent 10.5 [±6.1] min MVPA, 13 h 36 min [±48 min] sedentary and 2 h 14 min [±48 min] in light activities per day. Each additional 40 min of light activity (spent in 1.5-3 METs) or 42 min less time spent sedentary was associated with 0.22% [±0.07%] greater total cerebral brain volume (TCBV), after adjusting for age, sex, body mass index, smoking, diabetes mellitus, and cardiovascular disease (p=0.001), equivalent to approximately 1.1 years less brain aging. Greater light activity and lower sedentary time were also associated with greater hippocampal volume (p<0.005). Conclusions: Our investigation demonstrates, in a community setting, that there may be a negative association of light physical activity with brain aging even among individuals not meeting the PA-Guidelines for MVPA. [ABSTRACT FROM AUTHOR]