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Abstract Aims This study aims to provide insight into sex‐specific cardiovascular protein profiles and their associations with adverse outcomes, which may contribute to a better understanding of heart failure (HF) pathophysiology and the optimal use of circulating proteins for prognostication in women and men. Methods and results In 250 stable patients with HF with reduced ejection fraction (HFrEF), we performed trimonthly blood sampling (median follow‐up: 26 [17–30] months). We selected all baseline samples and two samples closest to the primary endpoint (PEP; composite of cardiovascular death, heart transplantation, left ventricular assist device implantation, and HF hospitalization) or one sample closest to censoring and applied the Olink Cardiovascular III panel. We used linear regression to study sex‐based differences in baseline levels and joint models to study differences in the prognostic value of serially measured proteins. In 66 women and 184 men (mean age of 66 and 67 years, respectively), 21% and 28% reached the PEP, respectively. Mean baseline levels of fatty acid‐binding protein 4, secretoglobin family 3A member 2, paraoxonase 3, and trefoil factor 3 were higher in women (Pinteraction: 0.001, 0.007, 0.018, and 0.049, respectively), while matrix metalloproteinase‐3, interleukin 1 receptor‐like 1, and myoglobin were higher in men (Pinteraction:

Abstract Background Active surveillance (AS), where treatment is deferred until cancer progression is detected by a biopsy, is acknowledged as a way to reduce overtreatment in prostate cancer. However, a consensus on the frequency of taking biopsies while in AS is lacking. In former studies to optimize biopsy schedules, the delay in progression detection was taken as an evaluation indicator and believed to be associated with the long‐term outcome, prostate cancer mortality. Nevertheless, this relation was never investigated in empirical data. Here, we use simulated data from a microsimulation model to fill this knowledge gap. Methods In this study, the established MIcrosimulation SCreening Analysis model was extended with functionality to simulate the AS procedures. The biopsy sensitivity in the model was calibrated on the Canary Prostate Cancer Active Surveillance Study (PASS) data, and four (tri‐yearly, bi‐yearly, PASS, and yearly) AS programs were simulated. The relation between detection delay and prostate cancer mortality was investigated by Cox models. Results The biopsy sensitivity of progression detection was found to be 50%. The Cox models show a positive relation between a longer detection delay and a higher risk of prostate cancer death. A 2‐year delay resulted in a prostate cancer death risk of 2.46%–2.69% 5 years after progression detection and a 10‐year risk of 5.75%–5.91%. A 4‐year delay led to an approximately 8% greater 5‐year risk and an approximately 25% greater 10‐year risk. Conclusion The detection delay is confirmed as a surrogate for prostate cancer mortality. A cut‐off for a “safe” detection delay could not be identified.

ABSTRACT: Background: Aortic wall shear stress (WSS) is a known predictor of ascending aortic growth in patients with a bicuspid aortic valve (BAV). The aim of this study was to study regional WSS and changes over time in BAV patients. Methods: BAV patients and age-matched healthy controls underwent four-dimensional (4D) flow cardiovascular magnetic resonance (CMR). Regional, peak systolic ascending aortic WSS, aortic valve function, aortic stiffness measures, and aortic dimensions were assessed. In BAV patients, 4D flow CMR was repeated after 3 years of follow-up and both at baseline and follow-up computed tomography angiography (CTA) were acquired. Aortic growth (volume increase of ≥5%) was measured on CTA. Regional WSS differences within patients’ aorta and WSS changes over time were analyzed using linear mixed-effect models and were associated with clinical parameters. Results: Thirty BAV patients (aged 34 years [interquartile range (IQR) 25–41]) were included in the follow-up analysis. Additionally, another 16 BAV patients and 32 healthy controls (aged 33 years [IQR 28–48]) were included for other regional analyses. Magnitude, axial, and circumferential WSS increased over time (all p 95th percentile of healthy controls increased from 21% (baseline 506/2400 regions) to 31% (follow-up 734/2400 regions) (p

Abstract Background Studies focusing on sex differences in circulating proteins in patients with heart failure with reduced ejection fraction (HFrEF) are scarce. Insight into sex-specific cardiovascular protein profiles and their associations with the risk of adverse outcomes may contribute to a better understanding of the pathophysiological processes involved in HFrEF. Moreover, it could provide a basis for the use of circulating protein measurements for prognostication in women and men, wherein the most relevant protein measurements are applied in each of the sexes. Methods In 382 patients with HFrEF, we performed tri-monthly blood sampling (median follow-up: 25 [13–31] months). We selected all baseline samples and two samples closest to the primary endpoint (PEP: composite of cardiovascular death, heart transplantation, left ventricular assist device implantation, and HF hospitalization) or censoring. We then applied an aptamer-based multiplex proteomic assay identifying 1105 proteins previously associated with cardiovascular disease. We used linear regression models and gene-enrichment analysis to study sex-based differences in baseline levels. We used time-dependent Cox models to study differences in the prognostic value of serially measured proteins. All models were adjusted for the MAGGIC HF mortality risk score and p-values for multiple testing. Results In 104 women and 278 men (mean age 62 and 64 years, respectively) cumulative PEP incidence at 30 months was 25% and 35%, respectively. At baseline, 55 (5%) out of the 1105 proteins were significantly different between women and men. The female protein profile was most strongly associated with extracellular matrix organization, while the male profile was dominated by regulation of cell death. The association of endothelin-1 (Pinteraction

Abstract Background The association structure linking the longitudinal and survival sub-models is of fundamental importance in the joint modeling framework and the choice of this structure should be made based on the clinical background of the study. However, this information may not always be accessible and rationale for selecting this association structure has received relatively little attention in the literature. To this end, we aim to explore four alternative functional forms of the association structure between the CD4 count and the risk of death and provide rationale for selecting the optimal association structure for our data. We also aim to compare the results obtained from the joint model to those obtained from the time-varying Cox model. Methods We used data from the Centre for the AIDS Programme of Research in South Africa (CAPRISA) AIDS Treatment programme, the Starting Antiretroviral Therapy at Three Points in Tuberculosis (SAPiT) study, an open-label, three armed randomised, controlled trial between June 2005 and July 2010 (N=642). In our analysis, we combined the early and late integrated arms and compared results to the sequential arm. We utilized the Deviance Information Criterion (DIC) to select the final model with the best structure, with smaller values indicating better model adjustments to the data. Results Patient characteristics were similar across the study arms. Combined integrated therapy arms had a reduction of 55% in mortality (HR:0.45, 95% CI:0.28-0.72) compared to the sequential therapy arm. The joint model with a cumulative effects functional form was chosen as the best association structure. In particular, our joint model found that the area under the longitudinal profile of CD4 count was strongly associated with a 21% reduction in mortality (HR:0.79, 95% CI:0.72-0.86). Where as results from the time-varying Cox model showed a 19% reduction in mortality (HR:0.81, 95% CI:0.77-0.84). Conclusions In this paper we have shown that the “current value” association structure is not always the best structure that expresses the correct relationship between the outcomes in all settings, which is why it is crucial to explore alternative clinically meaningful association structures that links the longitudinal and survival processes.

Summary: Background: HFrEF is a heterogenous condition with high mortality. We used serial assessments of 4210 circulating proteins to identify distinct novel protein-based HFrEF subphenotypes and to investigate underlying dynamic biological mechanisms. Herewith we aimed to gain pathophysiological insights and fuel opportunities for personalised treatment. Methods: In 382 patients, we performed trimonthly blood sampling during a median follow-up of 2.1 [IQR:1.1–2.6] years. We selected all baseline samples and two samples closest to the primary endpoint (PEP; composite of cardiovascular mortality, HF hospitalization, LVAD implantation, and heart transplantation) or censoring, and applied an aptamer-based multiplex proteomic approach. Using unsupervised machine learning methods, we derived clusters from 4210 repeatedly measured proteomic biomarkers. Sets of proteins that drove cluster allocation were analysed via an enrichment analysis. Differences in clinical characteristics and PEP occurrence were evaluated. Findings: We identified four subphenotypes with different protein profiles, prognosis and clinical characteristics, including age (median [IQR] for subphenotypes 1–4, respectively:70 [64, 76], 68 [60, 79], 57 [47, 65], 59 [56, 66]years), EF (30 [26, 36], 26 [20, 38], 26 [22, 32], 33 [28, 37]%), and chronic renal failure (45%, 65%, 36%, 37%). Subphenotype allocation was driven by subsets of proteins associated with various biological functions, such as oxidative stress, inflammation and extracellular matrix organisation. Clinical characteristics of the subphenotypes were aligned with these associations. Subphenotypes 2 and 3 had the worst prognosis compared to subphenotype 1 (adjHR (95%CI):3.43 (1.76–6.69), and 2.88 (1.37–6.03), respectively). Interpretation: Four circulating-protein based subphenotypes are present in HFrEF, which are driven by varying combinations of protein subsets, and have different clinical characteristics and prognosis. Clinical Trial Registration: ClinicalTrials.gov Identifier: NCT01851538 https://clinicaltrials.gov/ct2/show/NCT01851538. Funding: EU/EFPIA IMI2JU BigData@Heart grant n°116074, Jaap Schouten Foundation and Noordwest Academie.

Abstract The aim of our observational study was to derive a small set out of 92 repeatedly measured biomarkers with optimal predictive capacity for adverse clinical events in heart failure, which could be used for dynamic, individual risk assessment in clinical practice. In 250 chronic HFrEF (CHF) patients, we collected trimonthly blood samples during a median of 2.2 years. We selected 537 samples for repeated measurement of 92 biomarkers with the Cardiovascular Panel III (Olink Proteomics AB). We applied Least Absolute Shrinkage and Selection Operator (LASSO) penalization to select the optimal set of predictors of the primary endpoint (PE). The association between repeatedly measured levels of selected biomarkers and the PE was evaluated by multivariable joint models (mvJM) with stratified fivefold cross validation of the area under the curve (cvAUC). The PE occurred in 66(27%) patients. The optimal set of biomarkers selected by LASSO included 9 proteins: NT-proBNP, ST2, vWF, FABP4, IGFBP-1, PAI-1, PON-3, transferrin receptor protein-1, and chitotriosidase-1, that yielded a cvAUC of 0.88, outperforming the discriminative ability of models consisting of standard biomarkers (NT-proBNP, hs-TnT, eGFR clinically adjusted) − 0.82 and performing equally well as an extended literature-based set of acknowledged biomarkers (NT-proBNP, hs-TnT, hs-CRP, GDF-15, ST2, PAI-1, Galectin 3) − 0.88. Nine out of 92 serially measured circulating proteins provided a multivariable model for adverse clinical events in CHF patients with high discriminative ability. These proteins reflect wall stress, remodelling, endothelial dysfunction, iron deficiency, haemostasis/fibrinolysis and innate immunity activation. A panel containing these proteins could contribute to dynamic, personalized risk assessment. Clinical Trial Registration: 10/05/2013 https://clinicaltrials.gov/ct2/show/NCT01851538?term=nCT01851538&draw=2&rank=1 .

Abstract Background HRV has mostly shown associations with systolic dysfunction and more recently, with diastolic dysfunction in Heart failure (HF) patients. But the role of sympathetic nervous system in changes of left ventricular (LV) systolic and diastolic function and new-onset HF has not been extensively studied. Methods Among 3157 men and 4405 women free of HF and atrial fibrillation retrospectively included from the population-based Rotterdam Study, we used linear mixed models to examine associations of RR-interval differences and standard deviation of RR-intervals corrected for heart rate (RMSSDc and SDNNc) with longitudinal changes of LV ejection fraction (LVEF), E/A ratio, left atrial (LA) diameter, E/e’ ratio. Afterwards, using cox regressions, we examined their association with new-onset HF. Results Mean (SD) age was 65 (9.95) in men and 65.7 (10.2) in women. Every unit increase in log RMSSDc was accompanied by 0.75% (95%CI:-1.11%;-0.39%) and 0.31% (− 0.60%;-0.01%) lower LVEF among men and women each year, respectively. Higher log RMSSDc was linked to 0.03 (− 0.04;-0.01) and 0.02 (− 0.03;-0.003) lower E/A and also − 1.76 (− 2.77;− 0.75) and − 1.18 (− 1.99;-0.38) lower LVM index in both sexes and 0.72 mm (95% CI: − 1.20;-0.25) smaller LA diameters in women. The associations with LVEF in women diminished after excluding HF cases during the first 3 years of follow-up. During a median follow-up of 8.7 years, hazard ratios (95%CI) for incident HF were 1.34 (1.08;1.65) for log RMSSDc in men and 1.15 (0.93;1.42) in women. SDNNc showed similar associations. Conclusions Indices of HRV were associated with worse systolic function in men but mainly with improvement in LA size in women. Higher HRV was associated with higher risk of new-onset HF in men. Our findings highlight potential sex differences in autonomic function underlying cardiac dysfunction and heart failure in the general population.

Missing data occur in many types of studies and typically complicate the analysis. Multiple imputation, either using joint modeling or the more flexible fully conditional specification approach, are popular and work well in standard settings. In settings involving nonlinear associations or interactions, however, incompatibility of the imputation model with the analysis model is an issue often resulting in bias. Similarly, complex outcomes such as longitudinal or survival outcomes cannot be adequately handled by standard implementations. In this paper, we introduce the R package JointAI, which utilizes the Bayesian framework to perform simultaneous analysis and imputation in regression models with incomplete covariates. Using a fully Bayesian joint modeling approach it overcomes the issue of uncongeniality while retaining the attractive flexibility of fully conditional specification multiple imputation by specifying the joint distribution of analysis and imputation models as a sequence of univariate models that can be adapted to the type of variable. JointAI provides functions for Bayesian inference with generalized linear and generalized linear mixed models and extensions thereof as well as survival models and joint models for longitudinal and survival data, that take arguments analogous to the corresponding well known functions for the analysis of complete data from base R and other packages. Usage and features of JointAI are described and illustrated using various examples and the theoretical background is outlined.

A digital twin (DT), originally defined as a virtual representation of a physical asset, system, or process, is a new concept in health care. A DT in health care is not a single technology but a domain-adapted multimodal modeling approach incorporating the acquisition, management, analysis, prediction, and interpretation of data, aiming to improve medical decision-making. However, there are many challenges and barriers that must be overcome before a DT can be used in health care. In this viewpoint paper, we build on the current literature, address these challenges, and describe a dynamic DT in health care for optimizing individual patient health care journeys, specifically for women at risk for cardiovascular complications in the preconception and pregnancy periods and across the life course. We describe how we can commit multiple domains to developing this DT. With our cross-domain definition of the DT, we aim to define future goals, trade-offs, and methods that will guide the development of the dynamic DT and implementation strategies in health care.

Introduction: Predicting disease severity is important for treatment decisions in patients with COVID-19 in the intensive care unit (ICU). Different biomarkers have been investigated in COVID-19 as predictor of mortality, including C-reactive protein (CRP), procalcitonin (PCT), interleukin-6 (IL-6), and soluble urokinase-type plasminogen activator receptor (suPAR). Using repeated measurements in a prediction model may result in a more accurate risk prediction than the use of single point measurements. The goal of this study is to investigate the predictive value of trends in repeated measurements of CRP, PCT, IL-6, and suPAR on mortality in patients admitted to the ICU with COVID-19. Methods: This was a retrospective single center cohort study. Patients were included if they tested positive for SARS-CoV-2 by PCR test and if IL-6, PCT, suPAR was measured during any of the ICU admission days. There were no exclusion criteria for this study. We used joint models to predict ICU-mortality. This analysis was done using the framework of joint models for longitudinal and survival data. The reported hazard ratios express the relative change in the risk of death resulting from a doubling or 20% increase of the biomarker’s value in a day compared to no change in the same period. Results: A total of 107 patients were included, of which 26 died during ICU admission. Adjusted for sex and age, a doubling in the next day in either levels of PCT, IL-6, and suPAR were significantly predictive of in-hospital mortality with HRs of 1.523 (1.012-6.540), 75.25 (1.116-6247), and 24.45 (1.696-1057) respectively. With a 20% increase in biomarker value in a subsequent day, the HR of PCT, IL-6, and suPAR were 1.117 (1.03-1.639), 3.116 (1.029-9.963), and 2.319 (1.149-6.243) respectively. Conclusion: Joint models for the analysis of repeated measurements of PCT, suPAR, and IL-6 are a useful method for predicting mortality in COVID-19 patients in the ICU. Patients with an increasing trend of biomarker levels in consecutive days are at increased risk for mortality.

Abstract Background Missing data can complicate the interpretability of a clinical trial, especially if the proportion is substantial and if there are different, potentially outcome-dependent causes. Methods We aimed to obtain unbiased estimates, in the presence of a high level of missing data, for the intervention effects in a prodromal Alzheimer’s disease trial: the LipiDiDiet study. We used a competing risk joint model that can simultaneously model each patient’s longitudinal outcome trajectory in combination with the timing and type of missingness. Results Using the competing risk joint model, we were able to provide unbiased estimates of the intervention effects in the presence of the different types of missingness. For the LipiDiDiet study, the intervention effects remained statistically significant after this correction for the timing and type of missingness. Conclusion Missing data is a common problem in (Alzheimer) clinical trials. It is important to realize that statistical techniques make specific assumptions about the missing data mechanisms. When there are different missing data sources, a competing risk joint model is a powerful method because it can explicitly model the association between the longitudinal data and each type of missingness. Trial registration Dutch Trial Register, NTR1705 . Registered on 9 March 2009

Abstract Background Pompe disease is a rare, progressive metabolic myopathy. The aim of this study is to investigate the associations of physical outcomes with patient-reported outcome measures (PROMs) in late-onset Pompe disease. Methods We included 121 Dutch adult patients with Pompe disease. Physical outcomes comprised muscle strength (manual muscle testing using Medical Research Council [MRC] grading, hand-held dynamometry [HHD]), walking ability (6-min walk test [6MWT]), and pulmonary function (forced vital capacity [FVC] in upright and supine positions). PROMs comprised quality of life (Short Form 36 health survey [SF-36]), participation (Rotterdam Handicap Scale [RHS]) and daily-life activities (Rasch-Built Pompe-Specific Activity [R-PAct] Scale). Analyses were cross-sectional: the time-point before, and closest to, start of Enzyme Replacement Therapy was chosen. Associations between PROMs and physical outcomes were investigated using linear regression models. Results RHS and R-PAct scores were better in patients with higher FVC supine and upright, HHD, MRC and 6MWT scores, accounting for the effect of sex, disease duration, use of wheelchair and ventilator support. While the SF-36 Physical Component Summary (PCS) was correlated positively with FVC upright, HHD, MRC and 6MWT scores, there was no significant relationship between the SF-36 Mental Component Summary (MCS) and any of the physical outcomes. Conclusions Participation, daily-life activities, and the physical component of quality of life of adult Pompe patients are positively correlated to physical outcomes. This work serves as a first step towards assessing how changes over time in physical outcomes are related to changes in PROMs, and to define the minimal change in physical outcomes required to make an important difference for the patient.

Background Glioblastomas are mostly resected under general anesthesia under the supervision of a general anesthesiologist. Currently, it is largely unkown if clinical outcomes of GBM patients can be improved by appointing a neuro-anesthesiologist for their cases. We aimed to evaluate whether the assignment of dedicated neuro-anesthesiologists improves the outcomes of these patients. We also investigated the value of dedicated neuro-oncological surgical teams as an independent variable in both groups. Methods A cohort consisting of 401 GBM patients who had undergone resection was retrospectively investigated. Primary outcomes were postoperative neurological complications, fluid balance, length-of-stay and overall survival. Secondary outcomes were blood loss, anesthesia modality, extent of resection, total admission costs, and duration of surgery. Results 320 versus 81 patients were operated under the anesthesiological supervision of a general anesthesiologist and a dedicated neuro-anesthesiologist, respectively. Dedicated neuro-anesthesiologists yielded significant superior outcomes in 1) postoperative neurological complications (early: p = 0.002, OR = 2.54; late: p = 0.003, OR = 2.24); 2) fluid balance (pConclusion GBM resections with anesthesiological supervision of a dedicated neuro-anesthesiologists are associated with improved patient outcomes. Prospective evidence is needed to further investigate the usefulness of the dedicated neuro-anesthesiologist in different settings.

ObjectivesThe current surveillance strategy in Barrett's esophagus (BE) uses only histological findings of the last endoscopy to assess neoplastic progression risk. As predictor values vary across endoscopies, single measurements may not be an accurate reflection. Our aim was to explore the value of using longitudinal evolutions (i.e. successive measurements) of histological findings (low-grade dysplasia (LGD)) and immunohistochemical biomarkers (p53 and SOX2) by investigating the association with Barrett's progression.MethodsIn this proof-of-principle study of a longitudinal dynamic risk estimation model with a multicenter cohort design, 631 BE patients from 15 Dutch hospitals who were under surveillance were included. Longitudinal dynamic values of LGD, p53, and SOX2 were included in a multivariate joint model to estimate the risk of high-grade dysplasia (HGD)/esophageal adenocarcinoma (EAC).ResultsLongitudinal evolutions of aberrant expression of p53 (HR 1.26, pConclusionsThis study provides solid ground to further explore a paradigm shift from currently recommended fixed intervals towards personalized surveillance, in which tailored risk estimations and corresponding surveillance intervals can be updated at every FU endoscopy for individual BE patients.

Abstract Background Many prodromal Alzheimer’s disease trials collect two types of data: the time until clinical diagnosis of dementia and longitudinal patient information. These data are often analysed separately, although they are strongly associated. By combining the longitudinal and survival data into a single statistical model, joint models can account for the dependencies between the two types of data. Methods We illustrate the major steps in a joint modelling approach, motivated by data from a prodromal Alzheimer’s disease study: the LipiDiDiet trial. Results By using joint models we are able to disentangle baseline confounding from the intervention effect and moreover, to investigate the association between longitudinal patient information and the time until clinical dementia diagnosis. Conclusions Joint models provide a valuable tool in the statistical analysis of clinical studies with longitudinal and survival data, such as in prodromal Alzheimer’s disease trials, and have several added values compared to separate analyses.

Abstract Background Immunity has been suggested to be important in the pathogenesis of dementia. However, the contribution of innate versus adaptive immunity in the development of dementia is not clear. In this study, we aimed to investigate (1) the association between components of innate immunity (granulocytes and platelets) and adaptive immunity (lymphocytes) with risk of dementia and (2) the association between their derived ratios (granulocyte-to-lymphocyte ratio [GLR], platelet-to-lymphocyte ratio [PLR], and systemic immune-inflammation index [SII]), reflecting the balance between innate and adaptive immunity, with risk of dementia. Methods Blood cell counts were measured repeatedly between 2002 and 2015 in dementia-free participants of the prospective population-based Rotterdam Study. Participants were followed-up for dementia until 1 January 2016. Joint models were used to determine the association between granulocyte, platelets, and lymphocyte counts, and their derived ratios with risk of dementia. Results Of the 8313 participants (mean [standard deviation] age 61.1 [7.4] years, 56.9% women), 664 (8.0%) developed dementia during a median follow-up of 8.6 years. Doubling of granulocyte and platelet counts tended to be associated with an increased risk of dementia (HR [95%CI] 1.22 [0.89–1.67] and 1.45 [1.07–1.95], respectively). Doubling of the derived ratios GLR, PLR, and SII were all associated with an increased dementia risk (HR [95%CI] 1.26 [1.03–1.53], 1.27 [1.05–1.53], and 1.15 [0.98–1.34], respectively). Conclusions GLR, PLR, and SII are associated with an increased risk of dementia in the general population. This supports the role of an imbalance in the immune system towards innate immunity in the pathogenesis of dementia.

BackgroundAtherosclerotic cardiovascular disease (ASCVD) is driven by multifaceted contributions of the immune system. However, the dysregulation of immune cells that leads to ASCVD is poorly understood. We determined the association of components of innate and adaptive immunity longitudinally with ASCVD, and assessed whether arterial calcifications play a role in this association.Methods and findingsGranulocyte (innate immunity) and lymphocyte (adaptive immunity) counts were determined 3 times (2002-2008, mean age 65.2 years; 2009-2013, mean age 69.0 years; and 2014-2015, mean age 78.5 years) in participants of the population-based Rotterdam Study without ASCVD at baseline. Participants were followed-up for ASCVD or death until 1 January 2015. A random sample of 2,366 underwent computed tomography at baseline to quantify arterial calcification volume in 4 vessel beds. We studied the association between immunity components with risk of ASCVD and assessed whether immunity components were related to arterial calcifications at baseline. Of 7,730 participants (59.4% women), 801 developed ASCVD during a median follow-up of 8.1 years. Having an increased granulocyte count increased ASCVD risk (adjusted hazard ratio for doubled granulocyte count [95% CI] = 1.78 [1.34-2.37], P < 0.001). Higher granulocyte counts were related to larger calcification volumes in all vessels, most prominently in the coronary arteries (mean difference in calcium volume [mm3] per SD increase in granulocyte count [95% CI] = 32.3 [9.9-54.7], P < 0.001). Respectively, the association between granulocyte count and incident coronary heart disease and stroke was partly mediated by coronary artery calcification (overall proportion mediated [95% CI] = 19.0% [-10% to 32.3%], P = 0.08) and intracranial artery calcification (14.9% [-10.9% to 19.1%], P = 0.05). A limitation of our study is that studying the etiology of ASCVD remains difficult within an epidemiological setting due to the limited availability of surrogates for innate and especially adaptive immunity.ConclusionsIn this study, we found that an increased granulocyte count was associated with a higher risk of ASCVD in the general population. Moreover, higher levels of granulocytes were associated with larger volumes of arterial calcification. Arterial calcifications may explain a proportion of the link between granulocytes and ASCVD.

Abstract Background Pompe disease is a rare metabolic myopathy. In adult patients, progressive weakness of limb-girdle and respiratory muscles often leads to wheelchair and respirator dependency. Clinical studies have shown enzyme replacement therapy (ERT) to positively affect motor and respiratory outcomes. Here we investigate whether ERT reduces patients’ risk of needing a wheelchair or respirator. Methods Data were collected as part of a prospective international survey, the IPA/Erasmus MC Pompe survey, which was conducted annually between 2002 and 2016. We excluded patients who were already using a wheelchair or respirator, those under 18 at survey entry, and those who had missing information. Time-dependent Cox proportional hazard models were used. Results The inclusion criteria for analyzing the risk of wheelchair use were met by 189 patients (median age 47 years; range 18–75). During follow-up, 126 (67%) started ERT. Over 1120 person-years of follow-up (median 5 years), 46 became wheelchair dependent, 16 of whom used ERT. After adjustment for disease duration, sex and country, ERT reduced the risk for wheelchair use (HR 0.36; 95% CI 0.17–0.75). For analyses of respirator use, 177 patients met the inclusion criteria (median age 46 years; range 18–73). Over 1190 person-years of follow-up (median 6 years), 125 patients (71%) were treated and 48 started respiratory support, 28 of whom received ERT. We found no association between ERT and the risk for respirator use (HR 1.23; 95% CI 0.61–2.47). Conclusions Our study found that ERT reduced the risk for wheelchair dependency. We could not demonstrate an effect on respiratory support.

In clinical research subjects are usually observed during a period of time. Primary and secondary endpoints are often either responses measured longitudinally over time or the time at which an event of interest occurs. Joint modeling is increasingly being used for multiple purposes such as to adjust the analysis of the longitudinal response for informative dropout mechanisms. In this paper we present %JM, a SAS macro that fits jointly generalized mixed models for longitudinal data and proportional hazards models for time-to-event responses. The macro fits normal, binary, binomial and Poisson longitudinal responses and allows choosing among a range of options to fit the trajectories of the longitudinal response over time: a linear function, splines, natural cubic splines and B-splines. For the time-to-event response, that might be right-censored, the macro fits parametric, stratified or not, proportional hazards models with the following baseline risk functions: exponential, Weibull, piecewise exponential and the generalizations of the Weibull and the Gompertz models based on splines. %JM offers several options to connect the longitudinal model and the time-to-event model: current-value-dependent and slope-dependent shared parameters, lagging effects, cumulative effects, random effects coefficients as shared parameters and interaction effects.

Abstract Background Pompe disease is a rare, progressive, metabolic disease, and the first treatable inheritable muscle disorder. Enzyme replacement therapy (ERT) with alglucosidase alfa is disease specific and the only medicinal product authorized for the treatment of Pompe disease. Costs of ERT are very high as for most orphan drugs. This study investigates the cost-effectiveness of ERT compared to supportive treatment in adult patients with Pompe disease. Methods Survival probabilities were estimated from an international observational dataset (n = 283) using a time-dependent Cox model. Quality of life was estimated on a Dutch observational dataset using a previously developed conceptual model which links clinical factors to quality of life. Costs included costs of ERT, costs of drug administration and other healthcare costs. Cost-effectiveness was estimated using a patient-level simulation model (n = 90), synthesising the information from underlying models for survival, quality of life and costs. The cost-effectiveness model estimated the (difference in) lifetime effects and costs for both treatments. Two scenarios were modelled: (1) a worse case scenario with no extrapolation of the survival gain due to ERT beyond the observed period (i.e. from 10 years onwards); and (2) a best case scenario with lifetime extrapolation of the survival gain due to ERT. Effects were expressed in (quality adjusted) life years (QALYs). Costs were discounted at 4.0% and effects at 1.5%. Results Substantial increases in survival were estimated – discounted incremental life years of ERT ranged from 1.9 years to 5.4 years in the scenarios without and with extrapolation of survival gains beyond the observed period. Quality of life was also significantly better for patients receiving ERT. Incremental costs were considerable and primarily consisted of the costs of ERT. Incremental costs per QALY were €3.2 million for scenario 1 and €1.8 million for scenario 2. Conclusions The availability of extended, prospectively collected, longitudinal observational data on the most important input parameters required to construct a cost-effectiveness model is quite exceptional for orphan diseases. The cost-effectiveness model showed substantial survival gains from ERT. Despite these substantial gains, ERT was not cost-effective in the treatment of adult Pompe disease because of the high cost of treatment.

Background Remodeling biomarkers carry high potential for predicting adverse events in chronic heart failure (CHF) patients. However, temporal patterns during the course of CHF, and especially the trajectory before an adverse event, are unknown. We studied the prognostic value of temporal patterns of 14 cardiac remodeling biomarker candidates in stable patients with CHF from the Bio‐SHiFT (Serial Biomarker Measurements and New Echocardiographic Techniques in Chronic Heart Failure Patients Result in Tailored Prediction of Prognosis) study. Methods and Results In 263 CHF patients, we performed trimonthly blood sampling during a median follow‐up of 2.2 years. For the analysis, we selected all baseline samples, the 2 samples closest to the primary end point (PE), or the last sample available for end point–free patients. Thus, in 567 samples, we measured suppression of tumorigenicity‐2, galectin‐3, galectin‐4, growth differentiation factor‐15, matrix metalloproteinase‐2, 3, and 9, tissue inhibitor metalloproteinase‐4, perlecan, aminopeptidase‐N, caspase‐3, cathepsin‐D, cathepsin‐Z, and cystatin‐B. The PE was a composite of cardiovascular mortality, heart transplantation, left ventricular assist device implantation, and HF hospitalization. Associations between repeatedly measured biomarker candidates and the PE were investigated by joint modeling. Median age was 68 (interquartile range: 59–76) years with 72% men; 70 patients reached the PE. Repeatedly measured suppression of tumorigenicity‐2, galectin‐3, galectin‐4, growth differentiation factor‐15, matrix metalloproteinase‐2 and 9, tissue inhibitor metalloproteinase‐4, perlecan, cathepsin‐D, and cystatin‐B levels were significantly associated with the PE, and increased as the PE approached. The slopes of biomarker trajectories were also predictors of clinical outcome, independent of their absolute level. Associations persisted after adjustment for clinical characteristics and pharmacological treatment. Suppression of tumorigenicity‐2 was the strongest predictor (hazard ratio: 7.55 per SD difference, 95% CI: 5.53–10.30), followed by growth differentiation factor‐15 (4.06, 2.98–5.54) and matrix metalloproteinase‐2 (3.59, 2.55–5.05). Conclusions Temporal patterns of remodeling biomarker candidates predict adverse clinical outcomes in CHF. Clinical Trial Registration URL: http://www.clinicaltrials.gov. Unique identifier: NCT01851538.

Joint models for longitudinal and time-to-event data constitute an attractive modeling framework that has received a lot of interest in the recent years. This paper presents the capabilities of the R package JMbayes for fitting these models under a Bayesian approach using Markov chain Monte Carlo algorithms. JMbayes can fit a wide range of joint models, including among others joint models for continuous and categorical longitudinal responses, and provides several options for modeling the association structure between the two outcomes. In addition, this package can be used to derive dynamic predictions for both outcomes, and offers several tools to validate these predictions in terms of discrimination and calibration. All these features are illustrated using a real data example on patients with primary biliary cirrhosis.

The majority of children and adults with Pompe disease in the population of European descent carry the leaky splicing GAA variant c.-32-13T>G (IVS1) in combination with a fully deleterious GAA variant on the second allele. The phenotypic spectrum of this patient group is exceptionally broad, with symptom onset ranging from early infancy to late adulthood. In addition, the response to enzyme replacement therapy (ERT) varies between patients. The insertion/deletion (I/D) polymorphism of the angiotensin I-converting enzyme (ACE) has been suggested to be a modifier of disease onset and/or response to ERT. Here, we have investigated the effect of the ACE I/D polymorphism in a relatively large cohort of 131 children and adults with Pompe disease, of whom 112 were followed during treatment with ERT for 5 years. We assessed the use of wheelchair and mechanical ventilation, muscle strength assessed via manual muscle testing and hand-held dynamometry (HHD), distance walked on the six-minute walk test (6MWT), forced vital capacity (FVC) in sitting and supine position and daily-life activities assessed by R-PAct. Cross sectional analysis at first visit showed no differences between the genotypes with respect to age at first symptoms, diagnosis, wheelchair use, or ventilator use. Also response to ERT over 5 years assessed by linear mixed model analyses showed no significant differences between ACE groups for any of the outcome measures. The patient cohort contained 24 families with 54 siblings. Differences in ACE genotype could neither explain inter nor intra familial differences. We conclude that the ACE I/D polymorphism does not explain the large variation in disease severity and response to ERT observed among Pompe patients with the same c.-32-13T>G GAA variant.

[This corrects the article DOI: 10.1371/journal.pone.0196382.].

BACKGROUND:Anti-RhD immunised donors provide anti-RhD immunoglobulins used for the prevention of rhesus disease. These donors are periodically hyper-immunised (boostered) to retain a high titer level of anti-RhD. STUDY DESIGN AND METHODS:We analysed anti-RhD donor records from 1998 to 2016, consisting of 30,116 anti-RhD titers from 755 donors, encompassing 3,372 booster events. Various models were fit to these data to allow describing the anti-RhD titers over time. RESULTS:A random effects model with a log-linear anti-RhD titer decline over time and a saturating titer response to boostering is shown to fit the data well. This model contains two general model parameters, relating timing and maximum of the booster effect, as well as two parameters characterizing the individual donor, namely how fast the booster effect saturates with current titer and the anti-RhD decline rate. The average individual log2 decline is 0.55 per year, i.e. a 32% decline in absolute titer, with half of the donors declining between 13% and 41% per year. Their anti-RhD titer peaks around 26 days following a booster event. Boostering response reduces with higher titers at boostering; at median titer (log2 11) the mean increase per booster is log2 0.38, that is from an absolute titer of 2048 to 2665 (+30%), with half of all donors increasing between 16% and 65% in their titer. CONCLUSION:The model describes anti-RhD titer change per individual with only four parameters, two of which are donor specific. This information can be used to enhance the blood bank's immunisation programme, by deriving individualized immunization policies in which boostering is adjusted to the anticipated anti-RhD decline, effectiveness of boostering and titer levels required.

There is increasing evidence that mindfulness can reduce stress, and thereby affect other psychological and physiological outcomes as well. Earlier, we reported the direct 3-month results of an online modified mindfulness-based stress reduction training in patients with heart disease, and now we evaluate the effect at 12-month follow-up. 324 patients (mean age 43.2 years, 53.7% male) were randomized in a 2:1 ratio to additional 3-month online mindfulness training or to usual care alone. The primary outcome was exercise capacity measured with the 6 minute walk test (6MWT). Secondary outcomes were blood pressure, heart rate, respiratory rate, NT-proBNP, cortisol levels (scalp hair sample), mental and physical functioning (SF-36), anxiety and depression (HADS), perceived stress (PSS), and social support (PSSS12). Differences between groups on the repeated outcome measures were analyzed with linear mixed models. At 12-months follow-up, participants showed a trend significant improvement exercise capacity (6MWT: 17.9 meters, p = 0.055) compared to UC. Cohen's D showed significant but small improvement on exercise capacity (d = 0.22; 95%CI 0.05 to 0.39), systolic blood pressure (d = 0.19; 95%CI 0.03 to 0.36), mental functioning (d = 0.22; 95%CI 0.05 to 0.38) and depressive symptomatology (d = 0.18; 95%CI 0.02 to 0.35). All other outcome measures did not change statistically significantly. In the as-treated analysis, systolic blood pressure decreased significantly with 5.5 mmHg (p = 0.045; d = 0.23 (95%CI 0.05-0.41)). Online mindfulness training shows favorable albeit small long-term effects on exercise capacity, systolic blood pressure, mental functioning, and depressive symptomatology in patients with heart disease and might therefore be a beneficial addition to current clinical care. TRIAL REGISTRATION:www.trialregister.nl NTR3453.

OBJECTIVES:To compare electroencephalography (EEG) findings during pregnancy and postpartum in women with normotensive pregnancies and pregnancies complicated by hypertensive disorders. Also the health related quality of life postpartum was related to these EEG findings. MATERIALS AND METHODS:An observational case-control study in a university hospital in the Netherlands. Twenty-nine normotensive and 58 hypertensive pregnant women were included. EEG's were recorded on several occasions during pregnancy and 6-8 weeks postpartum. Postpartum, the women filled out health related quality of life questionnaires. Main outcome measures were qualitative and quantitative assessments on EEG, multidimensional fatigue inventory, Short Form (36) Health Survey and EuroQoL visual analogue scale. RESULTS:In women with severe preeclampsia significantly lower alpha peak frequency, more delta and theta activity bilaterally and a higher EEG Sum Score were seen. Postpartum, these women showed impaired mental health, mental fatigue and social functioning, which could not be related to the EEG findings. CONCLUSIONS:Severe preeclamptic patients show more EEG abnormalities and have impaired mental wellbeing postpartum, but these findings are not correlated.

Evidence is accumulating that mindfulness training has favorable effects on psychological outcomes, but studies on physiological outcomes are limited. Patients with heart disease have a high incidence of physiological and psychological problems and may benefit from mindfulness training. Our aim was to determine the beneficial physiological and psychological effects of online mindfulness training in patients with heart disease.The study was a pragmatic randomized controlled single-blind trial. Between June 2012 and April 2014 we randomized 324 patients (mean age 43.2 years, 53.7% male) with heart disease in a 2:1 ratio (n = 215 versus n = 109) to a 12-week online mindfulness training in addition to usual care (UC) compared to UC alone. The primary outcome was exercise capacity measured with the 6 minute walk test (6MWT). Secondary outcomes were other physiological parameters (heart rate, blood pressure, respiratory rate, and NT-proBNP), subjective health status (SF-36), perceived stress (PSS), psychological well-being (HADS), social support (PSSS12) and a composite endpoint (all-cause mortality, heart failure, symptomatic arrhythmia, cardiac surgery, and percutaneous cardiac intervention). Linear mixed models were used to evaluate differences between groups on the repeated outcome measures.Compared to UC, mindfulness showed a borderline significant improved 6MWT (effect size, meters: 13.2, 95%CI: -0.02; 26.4, p = 0.050). There was also a significant lower heart rate in favor of the mindfulness group (effect size, beats per minute: -2.8, 95%CI: -5.4;-0.2, p = 0.033). No significant differences were seen on other outcomes.Mindfulness training showed positive effects on the physiological parameters exercise capacity and heart rate and it might therefore be a useful adjunct to current clinical therapy in patients with heart disease.Dutch Trial Register 3453.

The R package ltm has been developed for the analysis of multivariate dichotomous and polytomous data using latent variable models, under the Item Response Theory approach. For dichotomous data the Rasch, the Two-Parameter Logistic, and Birnbaum's Three-Parameter models have been implemented, whereas for polytomous data Semejima's Graded Response model is available. Parameter estimates are obtained under marginal maximum likelihood using the Gauss-Hermite quadrature rule. The capabilities and features of the package are illustrated using two real data examples.

In transplantation studies, often longitudinal measurements are collected for important markers prior to the actual transplantation. Using only the last available measurement as a baseline covariate in a survival model for the time to graft failure discards the whole longitudinal evolution. We propose a two-stage approach to handle this type of data sets using all available information. At the first stage, we summarize the longitudinal information with nonlinear mixed-effects model, and at the second stage, we include the Empirical Bayes estimates of the subject-specific parameters as predictors in the Cox model for the time to allograft failure. To take into account that the estimated subject-specific parameters are included in the model, we use a Monte Carlo approach and sample from the posterior distribution of the random effects given the observed data. Our proposal is exemplified on a study of the impact of renal resistance evolution on the graft survival.

In longitudinal studies measurements are often collected on different types of outcomes for each subject. These may include several longitudinally measured responses (such as blood values relevant to the medical condition under study) and the time at which an event of particular interest occurs (e.g., death, development of a disease or dropout from the study). These outcomes are often separately analyzed; however, in many instances, a joint modeling approach is either required or may produce a better insight into the mechanisms that underlie the phenomenon under study. In this paper we present the R package JM that fits joint models for longitudinal and time-to-event data.