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Objective The purpose of this systematic review was to identify and appraise externally validated prognostic models to predict a patient's health outcomes relevant to physical rehabilitation of musculoskeletal (MSK) conditions. Methods We systematically reviewed 8 databases and reported our findings according to Preferred Reporting Items for Systematic Reviews and Meta-Analysis 2020. An information specialist designed a search strategy to identify externally validated prognostic models for MSK conditions. Paired reviewers independently screened the title, abstract, and full text and conducted data extraction. We extracted characteristics of included studies (eg, country and study design), prognostic models (eg, performance measures and type of model) and predicted clinical outcomes (eg, pain and disability). We assessed the risk of bias and concerns of applicability using the prediction model risk of bias assessment tool. We proposed and used a 5-step method to determine which prognostic models were clinically valuable. Results We found 4896 citations, read 300 full-text articles, and included 46 papers (37 distinct models). Prognostic models were externally validated for the spine, upper limb, lower limb conditions, and MSK trauma, injuries, and pain. All studies presented a high risk of bias. Half of the models showed low concerns for applicability. Reporting of calibration and discrimination performance measures was often lacking. We found 6 externally validated models with adequate measures, which could be deemed clinically valuable [ie, (1) STart Back Screening Tool, (2) Wallis Occupational Rehabilitation RisK model, (3) Da Silva model, (4) PICKUP model, (5) Schellingerhout rule, and (6) Keene model]. Despite having a high risk of bias, which is mostly explained by the very conservative properties of the PROBAST tool, the 6 models remain clinically relevant. Conclusion We found 6 externally validated prognostic models developed to predict patients' health outcomes that were clinically relevant to the physical rehabilitation of MSK conditions. Impact Our results provide clinicians with externally validated prognostic models to help them better predict patients' clinical outcomes and facilitate personalized treatment plans. Incorporating clinically valuable prognostic models could inherently improve the value of care provided by physical therapists. [ABSTRACT FROM AUTHOR]

Background: Klemera-Doubal's method (KDM) is an advanced and widely applied algorithm for estimating biological age (BA), but it has no uniform paradigm for biomarker processing. This article proposed all subsets of biomarkers for estimating BAs and assessed their association with mortality to determine the most predictive subset and BA.Methods: Clinical biomarkers, including those from physical examinations and blood assays, were assessed in the China Health and Nutrition Survey (CHNS) 2009 wave. Those correlated with chronological age (CA) were combined to produce complete subsets, and BA was estimated by KDM from each subset of biomarkers. A Cox proportional hazards regression model was used to examine and compare each BA's effect size and predictive capacity for all-cause mortality. Validation analysis was performed in the Chinese Longitudinal Healthy Longevity Survey (CLHLS) and National Health and Nutrition Examination Survey (NHANES). KD-BA and Levine's BA were compared in all cohorts.Results: A total of 130 918 panels of BAs were estimated from complete subsets comprising 3-17 biomarkers, whose Pearson coefficients with CA varied from 0.39 to 1. The most predictive subset consisted of 5 biomarkers, whose estimated KD-BA had the most predictive accuracy for all-cause mortality. Compared with Levine's BA, the accuracy of the best-fitting KD-BA in predicting death varied among specific populations.Conclusion: All-subset analysis could effectively reduce the number of redundant biomarkers and significantly improve the accuracy of KD-BA in predicting all-cause mortality. [ABSTRACT FROM AUTHOR]

Aims: The aim of this study is to evaluate whether the MADIT-ICD benefit score can predict who benefits most from the addition of implantable cardioverter-defibrillator (ICD) to cardiac resynchronization therapy (CRT) in real-world patients with heart failure with reduced ejection fraction (HFrEF) and to compare this with selection according to a multidisciplinary expert centre approach.Methods and Results: Consecutive HFrEF patients who received a CRT for a guideline indication at a tertiary care hospital (Ziekenhuis Oost-Limburg, Genk, Belgium) between October 2008 and September 2016, were retrospectively evaluated. The MADIT-ICD benefit groups (low, intermediate, and high) were compared with the current multidisciplinary expert centre approach. Endpoints were (i) sustained ventricular tachycardia (VT) or ventricular fibrillation (VF) and (ii) non-arrhythmic mortality. Of the 475 included patients, 165 (34.7%) were in the lowest, 220 (46.3%) in the intermediate, and 90 (19.0%) in the highest benefit group. After a median follow-up of 34 months, VT/VF occurred in 3 (1.8%) patients in the lowest, 9 (4.1%) in the intermediate, and 13 (14.4%) in the highest benefit group (P < 0.001). Vice versa, non-arrhythmic death occurred in 32 (19.4%) in the lowest, 32 (14.6%) in the intermediate, and 3 (3.3%) in the highest benefit group (P = 0.002). The predictive power for ICD benefit was comparable between expert multidisciplinary judgement and the MADIT-ICD benefit score: Uno's C-statistic 0.69 vs. 0.69 (P = 0.936) for VT/VF and 0.62 vs. 0.60 (P = 0.790) for non-arrhythmic mortality.Conclusion: The MADIT-ICD benefit score can identify who benefits most from CRT-D and is comparable with multidisciplinary judgement in a CRT expert centre. [ABSTRACT FROM AUTHOR]

Background: External validation of prognostic models is necessary to assess the accuracy and generalizability of the model to new patients. If models are validated in a setting in which competing events occur, these competing risks should be accounted for when comparing predicted risks to observed outcomes.Methods: We discuss existing measures of calibration and discrimination that incorporate competing events for time-to-event models. These methods are illustrated using a clinical-data example concerning the prediction of kidney failure in a population with advanced chronic kidney disease (CKD), using the guideline-recommended Kidney Failure Risk Equation (KFRE). The KFRE was developed using Cox regression in a diverse population of CKD patients and has been proposed for use in patients with advanced CKD in whom death is a frequent competing event.Results: When validating the 5-year KFRE with methods that account for competing events, it becomes apparent that the 5-year KFRE considerably overestimates the real-world risk of kidney failure. The absolute overestimation was 10%age points on average and 29%age points in older high-risk patients.Conclusions: It is crucial that competing events are accounted for during external validation to provide a more reliable assessment the performance of a model in clinical settings in which competing risks occur. [ABSTRACT FROM AUTHOR]

Background: Financial toxicity is a growing problem in oncology, but no prior studies have prospectively measured the financial impact of cancer treatment in a diverse national cohort of newly diagnosed cancer patients. S1417CD was the first cooperative group-led multicenter prospective cohort study to evaluate financial hardship in metastatic colorectal cancer (mCRC) patients.Methods: Patients aged 18 years or older within 120 days of mCRC diagnosis completed quarterly questionnaires for 12 months. We estimated the cumulative incidence of major financial hardship (MFH), defined as 1 or more of increased debt, new loans from family and/or friends, selling or refinancing home, or 20% or more income decline. We evaluated the association between patient characteristics and MFH using multivariate cox regression and the association between MFH and quality of life using linear regression.Results: A total of 380 patients (median age = 59.9 years) were enrolled; 77.7% were White, 98.0% insured, and 56.5% had annual income of $50 000 or less. Cumulative incidence of MFH at 12 months was 71.3% (95% confidence interval = 65.7% to 76.1%). Age, race, marital status, and income (split at $50 000 per year) were not statistically significantly associated with MFH. However, income less than $100 000 and total assets less than $100 000 were both associated with greater MFH. MFH at 3 months was associated with decreased social functioning and quality of life at 6 months.Conclusions: Nearly 3 out of 4 mCRC patients experienced MFH despite access to health insurance. These findings underscore the need for clinic and policy solutions that protect cancer patients from financial harm. [ABSTRACT FROM AUTHOR]

Background: Tumor-based classification of human glioma portends patient prognosis, but considerable unexplained survival variability remains. Host factors (eg, age) also strongly influence survival times, partly reflecting a compromised immune system. How blood epigenetic measures of immune characteristics and age augment molecular classifications in glioma survival has not been investigated. We assess the prognostic impact of immune cell fractions and epigenetic age in archived blood across glioma molecular subtypes for the first time.Methods: We evaluated immune cell fractions and epigenetic age in archived blood from the University of California San Francisco Adult Glioma Study, which included a training set of 197 patients with IDH-wild type, 1p19q intact, TERT wild type (IDH/1p19q/TERT-WT) glioma, an evaluation set of 350 patients with other subtypes of glioma, and 454 patients without glioma.Results: IDH/1p19q/TERT-WT patients had lower lymphocyte fractions (CD4+ T, CD8+ T, natural killer, and B cells) and higher neutrophil fractions than people without glioma. Recursive partitioning analysis delineated 4 statistically significantly different survival groups for patients with IDH/1p19q/TERT-WT based on an interaction between chronological age and 2 blood immune factors, CD4+ T cells, and neutrophils. Median overall survival ranged from 0.76 years (95% confidence interval = 0.55-0.99) for the worst survival group (n = 28) to 9.72 years (95% confidence interval = 6.18 to not available) for the best (n = 33). The recursive partitioning analysis also statistically significantly delineated 4 risk groups in patients with other glioma subtypes.Conclusions: The delineation of different survival groups in the training and evaluation sets based on an interaction between chronological age and blood immune characteristics suggests that common host immune factors among different glioma types may affect survival. The ability of DNA methylation-based markers of immune status to capture diverse, clinically relevant information may facilitate noninvasive, personalized patient evaluation in the neuro-oncology clinic. [ABSTRACT FROM AUTHOR]

Background: Immune cell transcriptome signatures have been widely used to study the lung tumor microenvironment (TME). However, it is unclear to what extent the immune cell composition in the lung TME varies across histological and molecular subtypes (intertumor heterogeneity [inter-TH]) and within tumors (intratumor heterogeneity [ITH]) and whether ITH has any prognostic relevance.Methods: Using RNA sequencing in 269 tumor samples from 160 lung cancer patients, we quantified the inter-TH of immune gene expression and immune cell abundance and evaluated the association of median immune cell abundance with clinical and pathological features and overall survival. In 39 tumors with 132 multiregion samples, we also analyzed the ITH of immune cell abundance in relation to overall survival using a variance-weighted multivariate Cox model not biased by the number of samples per tumor.Results: Substantial inter-TH of 14 immune cell types was observed even within the same histological and molecular subtypes, but early stage tumors had higher lymphocyte infiltration across all tumor types. In multiregion samples, an unbiased estimate of low ITH of overall immune cell composition (hazard ratio [HR] = 0.40, 95% confidence interval [CI] = 0.21 to 0.78; P = .007), dendritic cells (HR = 0.24, 95% CI = 0.096 to 0.58; P = .002), and macrophages (HR = 0.50, 95% CI = 0.30 to 0.84; P = .009) was strongly associated with poor survival. The ITH of 3 markers, including CD163 and CD68 (macrophages) and CCL13 (dendritic cells), was enough to characterize the ITH of the corresponding immune cell abundances and its association with overall survival.Conclusion: This study suggests that lack of immune cell diversity may facilitate tumor evasion and progression. ITH inferred from CCL13, CD163, and CD68 could be used as a prognostic tool in clinical practice. [ABSTRACT FROM AUTHOR]

We develop methods for assessing the predictive accuracy of a given event time model when the validation sample is comprised of case $K$ interval-censored data. An imputation-based, an inverse probability weighted (IPW), and an augmented inverse probability weighted (AIPW) estimator are developed and evaluated for the mean prediction error and the area under the receiver operating characteristic curve when the goal is to predict event status at a landmark time. The weights used for the IPW and AIPW estimators are obtained by fitting a multistate model which jointly considers the event process, the recurrent assessment process, and loss to follow-up. We empirically investigate the performance of the proposed methods and illustrate their application in the context of a motivating rheumatology study in which human leukocyte antigen markers are used to predict disease progression status in patients with psoriatic arthritis. [ABSTRACT FROM AUTHOR]

Background: Despite early antiretroviral therapy (ART), ART-suppressed people with human immunodeficiency virus (HIV) (PWH) remain at higher risk for infections and infection-related cancers than the general population. The immunologic pathways that remain abnormal in this setting, potentially contributing to these complications, are unclear.Methods: ART-suppressed PWH and HIV-negative controls, all cytomegalovirus seropositive and enriched for HIV risk factors, were sampled from an influenza vaccine responsiveness study. PWH were stratified by timing of ART initiation (within 6 months of infection [early ART] vs later) and nadir CD4+ T-cell count among later initiators. Between-group differences in kynurenine-tryptophan (KT) ratio, interferon-inducible protein 10, soluble CD14 and CD163, soluble tumor necrosis factor receptor 2, interleukin 6, and soluble urokinase plasminogen activator receptor were assessed after confounder adjustment.Results: Most participants (92%) were male, reflecting the demographics of early-ART initiators in San Francisco. Most biomarkers were higher among later-ART initiators. Participants in the early-ART group achieved near-normal soluble tumor necrosis factor receptor 2, interleukin 6, and soluble urokinase plasminogen activator receptor levels, but substantially higher KT ratio than those without HIV after confounder adjustment (P = .008). Soluble CD14, soluble CD163, and interferon-inducible protein 10 trended similarly.Conclusions: While early-ART initiators restore near-normal levels of many inflammatory markers, the kynurenine pathway of tryptophan catabolism remains abnormally high. Because this pathway confers adaptive immune defects and predicts tuberculosis and cancer progression, this it may contribute to persistent risks of these complications in this setting. [ABSTRACT FROM AUTHOR]

In randomized controlled trials (RCTs) with time-to-event outcomes, the difference in restricted mean survival times (RMSTD) offers an absolute measure of the treatment effect on the time scale. Computation of the RMSTD relies on the choice of a time horizon, $\tau$. In a meta-analysis, varying follow-up durations may lead to the exclusion of RCTs with follow-up shorter than $\tau$. We introduce an individual patient data multivariate meta-analysis model for RMSTD estimated at multiple time horizons. We derived the within-trial covariance for the RMSTD enabling the synthesis of all data by borrowing strength from multiple time points. In a simulation study covering 60 scenarios, we compared the statistical performance of the proposed method to that of two univariate meta-analysis models, based on available data at each time point and based on predictions from flexible parametric models. Our multivariate model yields smaller mean squared error over univariate methods at all time points. We illustrate the method with a meta-analysis of five RCTs comparing transcatheter aortic valve replacement (TAVR) with surgical replacement in patients with aortic stenosis. Over 12, 24, and 36 months of follow-up, those treated by TAVR live 0.28 [95% confidence interval (CI) 0.01 to 0.56], 0.46 (95% CI $-$0.08 to 1.01), and 0.79 (95% CI $-$0.43 to 2.02) months longer on average compared to those treated by surgery, respectively. [ABSTRACT FROM AUTHOR]

Acquiring real-world evidence is crucial to support health policy, but observational studies are prone to serious biases. An approach was recently proposed to overcome confounding and immortal-time biases within the emulated trial framework. This tutorial provides a step-by-step description of the design and analysis of emulated trials, as well as R and Stata code, to facilitate its use in practice. The steps consist in: (i) specifying the target trial and inclusion criteria; (ii) cloning patients; (iii) defining censoring and survival times; (iv) estimating the weights to account for informative censoring introduced by design; and (v) analysing these data. These steps are illustrated with observational data to assess the benefit of surgery among 70-89-year-old patients diagnosed with early-stage lung cancer. Because of the severe unbalance of the patient characteristics between treatment arms (surgery yes/no), a naïve Kaplan-Meier survival analysis of the initial cohort severely overestimated the benefit of surgery on 1-year survival (22% difference), as did a survival analysis of the cloned dataset when informative censoring was ignored (17% difference). By contrast, the estimated weights adequately removed the covariate imbalance. The weighted analysis still showed evidence of a benefit, though smaller (11% difference), of surgery among older lung cancer patients on 1-year survival. Complementing the CERBOT tool, this tutorial explains how to proceed to conduct emulated trials using observational data in the presence of immortal-time bias. The strength of this approach is its transparency and its principles that are easily understandable by non-specialists. [ABSTRACT FROM AUTHOR]

Cross-study validation (CSV) of prediction models is an alternative to traditional cross-validation (CV) in domains where multiple comparable datasets are available. Although many studies have noted potential sources of heterogeneity in genomic studies, to our knowledge none have systematically investigated their intertwined impacts on prediction accuracy across studies. We employ a hybrid parametric/non-parametric bootstrap method to realistically simulate publicly available compendia of microarray, RNA-seq, and whole metagenome shotgun microbiome studies of health outcomes. Three types of heterogeneity between studies are manipulated and studied: (i) imbalances in the prevalence of clinical and pathological covariates, (ii) differences in gene covariance that could be caused by batch, platform, or tumor purity effects, and (iii) differences in the "true" model that associates gene expression and clinical factors to outcome. We assess model accuracy, while altering these factors. Lower accuracy is seen in CSV than in CV. Surprisingly, heterogeneity in known clinical covariates and differences in gene covariance structure have very limited contributions in the loss of accuracy when validating in new studies. However, forcing identical generative models greatly reduces the within/across study difference. These results, observed consistently for multiple disease outcomes and omics platforms, suggest that the most easily identifiable sources of study heterogeneity are not necessarily the primary ones that undermine the ability to accurately replicate the accuracy of omics prediction models in new studies. Unidentified heterogeneity, such as could arise from unmeasured confounding, may be more important. [ABSTRACT FROM AUTHOR]

Background: A 'mortality risk score' (MS) based on ten prominent mortality-related cytosine-phosphate-guanine (CpG) sites was previously associated with all-cause mortality, but has not been verified externally. We aimed to validate the association of MS with mortality and to compare MS with three aging biomarkers: telomere length (TL), DNA methylation age (DNAmAge) and phenotypic age (DNAmPhenoAge) to explore whether MS can serve as a reliable measure of biological aging and mortality.Methods: Among 534 males aged 55-85 years from the US Normative Aging Study, the MS, DNAmAge and DNAmPhenoAge were derived from blood DNA methylation profiles from the Illumina HumanMethylation450 BeadChip, and TL was measured by quantitative real-time polymerase chain reaction (qRT-PCR).Results: A total of 147 participants died during a median follow-up of 9.4 years. The MS showed strong associations with all-cause, cardiovascular disease (CVD) and cancer mortality. After controlling for all potential covariates, participants with high MS (>5 CpG sites with aberrant methylation) had almost 4-fold all-cause mortality (hazard ratio: 3.84, 95% confidence interval: 1.92-7.67) compared with participants with a low MS (0-1 CpG site with aberrant methylation). Similar patterns were observed with respect to CVD and cancer mortality. MS was associated with TL and DNAmPhenoAge acceleration but not with DNAmAge acceleration. Although the MS and DNAmPhenoAge acceleration were independently associated with all-cause mortality, the former exhibited a higher predictive accuracy of mortality than the latter.Conclusions: MS has the potential to be a prominent predictor of mortality that could enhance survival prediction in clinical settings. [ABSTRACT FROM AUTHOR]

Many populations of early-stage cancer patients have non-negligible latent cure fractions that can be modeled using transformation cure models. However, there is a lack of statistical metrics to evaluate prognostic utility of biomarkers in this context due to the challenges associated with unknown cure status and heavy censorship. In this article, we develop general concordance measures as evaluation metrics for the discriminatory accuracy of transformation cure models including the so-called promotion time cure models and mixture cure models. We introduce explicit formulas for the consistent estimates of the concordance measures, and show that their asymptotically normal distributions do not depend on the unknown censoring distribution. The estimates work for both parametric and semiparametric transformation models as well as transformation cure models. Numerical feasibility of the estimates and their robustness to the censoring distributions are illustrated via simulation studies and demonstrated using a melanoma data set. [ABSTRACT FROM AUTHOR]

Aims: Diabetes mellitus (DM) is associated with the development of cardiovascular disease (CVD). Morphological changes in the left atrium (LA) may appear before symptoms. We aimed to investigate the association between cardiac magnetic resonance imaging (CMR) measured LA structure and function and incident CVD in asymptomatic individuals with DM. Methods and results: Tissue tracking CMR was used to measure LA size and phasic function (emptying fractions and strain) on all 536 Multi-Ethnic Study of Atherosclerosis (MESA) participants with DM and available CMR at baseline in 2000-2002. At the time of enrolment, all participants were free of clinically recognized CVD, which was defined as MI, resuscitated cardiac arrest, angina, stroke, heart failure, and atrial fibrillation. Cox regression was used to assess the association of LA parameters with incident CVD adjusted for traditional cardiovascular risk factors, LV mass, NT Pro-BNP and maximum LA volume. Kaplan-Meier curves, adjusted for traditional risk factors, were generated for each LA measurement for the 25% of participants with the most abnormal values versus the remaining 75%. After a mean follow up of 11.4 ± 3.4 years, 141 individuals developed CVD. Individuals with incident CVD (mean age 66 years, 66% male vs. mean age 64 years, 50% male) had larger maximum and minimum LA volume index (LAVI) (32.1 vs. 26.8 mm³/m² 19.4 vs. 14.2 mm³/m² respectively, P < 0.001 for both), and lower total, passive, and active EF than those without CVD (P < 0.01 for all). In the fully adjusted model, there was a significant association of minimum LAVI, LA total EF, LA passive EF and LA active EF with incident CVD (HR 1.12 per mm³/m², P < 0.001; HR 0.95 per %, P < 0.001; HR 0.97 per %, P = 0.021; HR 0.98 per %, P < 0.027, respectively). Conclusions: CMR measured LA minimum volume and LA function as measured by emptying fraction are predictive of CVD in a diabetic multi-ethnic population free of any clinically recognized CVD at baseline. [ABSTRACT FROM AUTHOR]

Background:  Cognitive impairment persists despite suppression of plasma human immunodeficiency virus (HIV) RNA. Monocyte-related immune activation is a likely mechanism. We examined immune activation and cognition in a cohort of HIV-infected and uninfected women from the Women's Interagency HIV Study (WIHS).Methods:  Blood levels of activation markers, soluble CD163 (sCD163), soluble CD14 (sCD14), CRP, IL-6, and a gut microbial translocation marker (intestinal fatty acid binding protein (I-FABP)) were measured in 253 women (73% HIV-infected). Markers were compared to concurrent (within ± one semiannual visit) neuropsychological testing performance.Results:  Higher sCD163 levels were associated with worse overall performance and worse verbal learning, verbal memory, executive function, psychomotor speed, and fine motor skills (P < .05 for all comparisons). Higher sCD14 levels were associated with worse verbal learning, verbal memory, executive function, and psychomotor speed (P < .05 for all comparisons). Among women with virological suppression, sCD163 remained associated with overall performance, verbal memory, psychomotor speed, and fine motor skills, and sCD164 remained associated with executive function (P < .05 for all comparisons). CRP, IL-6, and I-FABP were not associated with worse cognitive performance.Conclusions:  Monocyte activation was associated with worse cognitive performance, and associations persisted despite viral suppression. Persistent inflammatory mechanisms related to monocytes correlate to clinically pertinent brain outcomes. [ABSTRACT FROM AUTHOR]

Despite marked improvements in the modern treatment era, human immunodeficiency virus (HIV)-infected individuals, particularly those who initiated antiretroviral therapy (ART) at advanced disease stages, continue to have increased age-related morbidity and mortality, compared with the general population. Immune activation and inflammation persist despite suppressive ART and predict many of these morbidities. The goal of this review is to examine the evidence suggesting a link between the persistent inflammatory state and morbidity and mortality in this setting, to describe the impact of early ART initiation on these factors, and to highlight important unanswered questions for the field. We also advance a hypothesis to explain why some morbidities-and their root inflammatory drivers-may be prevented more than others by early ART initiation. [ABSTRACT FROM AUTHOR]

Background: The manipulation of pregnancy diets in animals can lead to changes in DNA methylation with phenotypic consequences in the offspring. Human studies have concentrated on the effects of nutrition during early gestation. Lacking in humans is an epigenome-wide association study of DNA methylation in relation to perturbations in nutrition across all gestation periods.Methods: We used the quasi-experimental setting of the Dutch famine of 1944-45 to evaluate the impact of famine exposure during specific 10-week gestation periods, or during any time in gestation, on genome-wide DNA methylation levels at age ∼ 59 years. In addition, we evaluated the impact of exposure during a shorter pre- and post-conception period. DNA methylation was assessed using the Illumina 450k array in whole blood among 422 individuals with prenatal famine exposure and 463 time- or sibling-controls without prenatal famine exposure.Results: Famine exposure during gestation weeks 1-10, but not weeks 11-20, 21-30 or 31-delivery, was associated with an increase in DNA methylation of CpG dinucleotides cg20823026 (FAM150B), cg10354880 (SLC38A2) and cg27370573 (PPAP2C) and a decrease of cg11496778 (OSBPL5/MRGPRG) (P < 5.9 × 10(-7), PFDR < 0.031). There was an increase in methylation of TACC1 and ZNF385A after exposure during any time in gestation (P < 2.0 × 10(-7), PFDR = 0.034) and a decrease of cg23989336 (TMEM105) after exposure around conception. These changes represent a shift of 0.3-0.6 standard deviations and are linked to genes involved in growth, development and metabolism.Conclusion: Early gestation, and not mid or late gestation, is identified as a critical time-period for adult DNA methylation changes in whole blood after prenatal exposure to famine. [ABSTRACT FROM AUTHOR]

Background Public health leaders have been criticized for their policy stances, relationships with governments and failure to train the next generation. New approaches to the identification and training of public health leaders may be required. To inform these, lessons can be drawn from public health ‘superheroes’; public health leaders perceived to be the most admired and effective by their peers. Methods Members and Fellows of the UK Faculty of Public Health were contacted via e-newsletter and magazine and asked to nominate their ‘Public Health Superhero’. Twenty-six responses were received, nominating 40 different people. Twelve semi-structured interviews were conducted. Thematic analysis, based on ‘grounded theory’, was conducted. Results Five leadership ‘talents’ for public health were identified: mentoring-nurturing, shaping-organizing, networking-connecting, knowing-interpreting and advocating-impacting. Conclusions Talent-based approaches have been effective for leadership development in other sectors. These talents are the first specific to the practice of public health and align with some aspects of existing frameworks. An increased focus on identifying and developing talents during public health training, as opposed to ‘competency’-based approaches, may be effective in strengthening public health leadership. Further research to understand the combination and intensity of talents across a larger sample of public health leaders is required. [ABSTRACT FROM AUTHOR]

The aim of this study was to investigate the associations between loss of a life partner and the development of dementia and decline in cognitive function in later life. We used an Icelandic cohort of 4,370 participants in the Age, Gene/Environment Susceptibility-Reykjavik Study who were living as married in 1978 (born in 1907–1935) and were either still married (unexposed cohort) or widowed (exposed cohort) at follow-up (in 2002–2006). We ascertained history of marital status and spouse's death by record linkage to the Registry of the Total Population, Statistics Iceland. The outcome measures were as follows: 1) dementia and mild cognitive impairment; and 2) memory, speed of processing, and executive function. During the observation period, 3,007 individuals remained married and 1,363 lost a spouse through death. We did not find any significant associations between loss of a spouse and our outcome variables, except that widowed women had poorer executive function (mean = −0.08) during the first 2 years after their husbands’ deaths compared with still-married women (mean = 0.09). Our findings do not support the notion that the risk of dementia is increased following the loss of a spouse, yet women demonstrate a seemingly temporary decline in executive function following the death of a partner. [ABSTRACT FROM PUBLISHER]

Individual participant time-to-event data from multiple prospective epidemiologic studies enable detailed investigation into the predictive ability of risk models. Here we address the challenges in appropriately combining such information across studies. Methods are exemplified by analyses of log C-reactive protein and conventional risk factors for coronary heart disease in the Emerging Risk Factors Collaboration, a collation of individual data from multiple prospective studies with an average follow-up duration of 9.8 years (dates varied). We derive risk prediction models using Cox proportional hazards regression analysis stratified by study and obtain estimates of risk discrimination, Harrell's concordance index, and Royston's discrimination measure within each study; we then combine the estimates across studies using a weighted meta-analysis. Various weighting approaches are compared and lead us to recommend using the number of events in each study. We also discuss the calculation of measures of reclassification for multiple studies. We further show that comparison of differences in predictive ability across subgroups should be based only on within-study information and that combining measures of risk discrimination from case-control studies and prospective studies is problematic. The concordance index and discrimination measure gave qualitatively similar results throughout. While the concordance index was very heterogeneous between studies, principally because of differing age ranges, the increments in the concordance index from adding log C-reactive protein to conventional risk factors were more homogeneous. [ABSTRACT FROM PUBLISHER]

Aims The left atrium (LA) transfers blood to the left ventricle in a complex manner. LA function is characterized by passive emptying (LA passive fraction), active emptying (LA ejection fraction), and total emptying (LA fractional change). Despite this complexity, the clinical relevance of the LA is based almost exclusively on LA maximal volume (LAmax), which may not glean the full prognostic potential. Cardiovascular magnetic resonance (CMR) is considered the most accurate method for studying LA function and size. The aim of the present study was to evaluate the prognostic importance of LA function in patients following ST elevation myocardial infarction (STEMI). Methods and results In 199 patients, a CMR scan was performed within 1–3 days after STEMI to measure LAmax and minimal volume (LAmin) and LA function. The incidence of death, re-infarction, stroke, and admission for heart failure [major adverse cardiac event (MACE)] were registered during the follow-up period [2.3 years (inter-quartile range: 2.0–2.5)]. A total of 40 patients (20%) met the clinical endpoint of MACE during follow-up. In a Cox regression analysis adjusting for known risk factors, LA fractional change remained independently associated with MACE [adjusted hazard ratio: 0.66 (95% confidence interval: 0.46–0.95)]. LAmax, LAmin, or LA passive fraction was not independently associated with MACE. Furthermore, LA fractional change provided incremental prognostic value to LAmax and other known predictors (Wald χ2 31.0 vs. 39.9, P= 0.016). Conclusion In STEMI patients, impaired LA fractional change is independently associated with outcome and provide incremental prognostic information to established predictors including LAmax. [ABSTRACT FROM PUBLISHER]

Aims To investigate the influence of left ventricular (LV) lead position on LV dyssynchrony in cardiac resynchronization therapy (CRT). Methods and results The LV lead was prospectively targeted to the latest activated LV segment (concordant) evaluated by two-dimensional speckle tracking radial strain (ST-RS) echocardiography in 103 CRT recipients (67 ± 12 years). Mechanical dyssynchrony was assessed by anteroseptal-to-posterior (AS-P) delay and interventricular mechanical delay (IVMD). Concordant LV leads were obtained in 72 (70%) patients. Superior LV reverse remodelling (LV-RR; ≥15% LV end-systolic volume reduction at 6-month follow-up) was observed in the concordant LV leads compared with the discordant LV leads [51 (76%) vs. 13 (45%); P = 0.003]. Mechanical resynchronization responders (≥50% AS-P delay reduction at 6-month follow-up) obtained in the concordant LV leads [44 (66%)] was greater than in the discordant LV leads [10 (34%); P = 0.005]. The discordant LV leads located adjacent to the concordant LV leads (+1 segment; n = 22) and 2 segments apart (+2 segments; n = 9) were evaluated in a subgroup analysis. Mechanical resynchronization responders 6 months after CRT were as follows: in +1 segment [n = 10 (48%)] and in +2 segments (n = 0; P = 0.001). The concordant LV lead was the only independent predictor of LV-RR at 6-month follow-up (odds ratio, 4.177; P = 0.004). Independent predictors of mechanical resynchronization responders were AS-P delay (odds ratio, 1.007; P = 0.032), IVMD (odds ratio, 1.024; P = 0.038), and concordant LV lead (odds ratio, 4.691; P = 0.004). Conclusion Concordant LV leads in CRT provided more responders according to both LV reverse remodelling and mechanical resynchronization. [ABSTRACT FROM AUTHOR]

Background: The intestinal microflora provide a strong defence against intestinal pathogens, and may be altered in inflammatory conditions that impact the gut, such as endometriosis. Therefore, intestinal bacteria shed from rhesus monkeys with endometriosis were compared with age-matched healthy controls. A second study assessed the prevalence of intestinal inflammation in female monkeys to determine whether endometriosis is associated with an increased likelihood of intestinal inflammation.Methods: Differential and selective agars were used to enumerate total and Gram-negative aerobic and facultatively anaerobic bacteria, as well as Lactobacilli, from female monkeys with or without endometriosis. In addition, the prevalence of intestinal inflammation in monkeys with or without endometriosis was determined in a retrospective analysis of necropsy reports.Results: Monkeys with endometriosis had a significantly different profile of shed microflora. Endometriosis was associated with lower Lactobacilli concentrations and higher Gram-negative bacteria concentrations. Moreover, there was a higher prevalence of intestinal inflammation in monkeys with endometriosis in comparison to healthy controls.Conclusions: Endometriosis is associated with an altered profile of intestinal microflora in rhesus monkeys. Although the exact mechanisms linking endometriosis and the microflora are unknown, it is possible that the microflora were affected by endometriosis-associated intestinal inflammation. [ABSTRACT FROM AUTHOR]