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  • 1
    In: PLoS Medicine, 2018, Vol.15(5)
    Description: [This corrects the article DOI: 10.1371/journal.pmed.1002541.].
    Keywords: Correction
    ISSN: 1549-1277
    E-ISSN: 1549-1676
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  • 2
    In: Journal of Proteomics & Bioinformatics, 2015, Vol.08(01)
    Description: Alternative splicing of messenger RNAs provides cells with the opportunity to create protein isoforms of a multitude of functions from a single gene by excluding or including exons during post-transcriptional processing. Reconstructing the contribution of these splice variants on the total amount of gene expression remains difficult. The authors have introduced a probabilistic formulation of the alternative splicing reconstruction problem using a finite mixture model, and provide a solution based on the maximum likelihood principle. Their model is based on the assumption that the expected expression level of exons in a particular splice variant is the same for all exons in that variant but allows for measurement error. In this algorithm the expression in a patient can be written as a weighted sum of the number of splice variant mixture multivariate Gaussian densities. The authors have applied the models to three genes, with 25, 29 and 265 possible splice variants, associated with Marfan's syndrome in gene/exon expression data of 63 patients with Marfan's syndrome.
    Keywords: Gene Expression ; Marfan'S Syndrome ; Data Processing ; Exons ; Algorithms ; Proteomics ; Bioinformatics ; Post-Transcription ; Connective Tissue Diseases ; Mrna ; Alternative Splicing ; Bioinformatics & Computer Applications ; Alternative Splicing ; Marfan Syndrome ; Gene Expression;
    ISSN: Journal of Proteomics & Bioinformatics
    E-ISSN: 0974276X
    Source: CrossRef
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  • 3
    Language: English
    In: JACC: Heart Failure, October 2014, Vol.2(5), pp.429-436
    Description: The present paper systematically reviews and compares existing prediction models in order to establish the strongest variables, models, and model characteristics in patients with heart failure predicting outcome. To improve decision making accurately predicting mortality and heart-failure hospitalization in patients with heart failure can be important for selecting patients with a poorer prognosis or nonresponders to current therapy, to improve decision making. MEDLINE/PubMed was searched for papers dealing with heart failure prediction models. To identify similar models on the basis of their variables hierarchical cluster analysis was performed. Meta-analysis was used to estimate the mean predictive value of the variables and models; meta-regression was used to find characteristics that explain variation in discriminating values between models. We identified 117 models in 55 papers. These models used 249 different variables. The strongest predictors were blood urea nitrogen and sodium. Four subgroups of models were identified. Mortality was most accurately predicted by prospective registry-type studies using a large number of clinical predictor variables. Mean C-statistic of all models was 0.66 ± 0.0005, with 0.71 ± 0.001, 0.68 ± 0.001 and 0.63 ± 0.001 for models predicting mortality, heart failure hospitalization, or both, respectively. There was no significant difference in discriminating value of models between patients with chronic and acute heart failure. Prediction of mortality and in particular heart failure hospitalization in patients with heart failure remains only moderately successful. The strongest predictors were blood urea nitrogen and sodium. The highest C-statistic values were achieved in a clinical setting, predicting short-term mortality with the use of models derived from prospective cohort/registry studies with a large number of predictor variables.
    Keywords: Heart Failure ; Outcome ; Prognosis ; Risk Factor ; Risk Prediction ; Medicine
    ISSN: 2213-1779
    E-ISSN: 2213-1787
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  • 4
    Language: English
    In: Journal of the American College of Cardiology, 04 September 2018, Vol.72(10), pp.1081-1090
    Description: Information on the pathophysiological differences between heart failure with reduced ejection fraction (HFrEF) versus heart failure with preserved ejection fraction (HFpEF) is needed The purpose of this study was to establish biological pathways specifically related to HFrEF and HFpEF. The authors performed a network analysis to identify unique biomarker correlations in HFrEF and HFpEF using 92 biomarkers from different pathophysiological domains in a cohort of 1,544 heart failure (HF) patients. Data were independently validated in 804 patients with HF. Networks were enriched with existing knowledge on protein–protein interactions and translated into biological pathways uniquely related to HFrEF, HF with a midrange ejection fraction, and HFpEF. In the index cohort (mean age 74 years; 34% female), 718 (47%) patients had HFrEF (left ventricular ejection fraction [LVEF] 〈40%) and 431 (27%) patients had HFpEF (LVEF ≥50%). A total of 8 (12%) correlations were unique for HFrEF and 6 (9%) were unique to HFpEF. Central proteins in HFrEF were N-terminal B-type natriuretic peptide, growth differentiation factor-15, interleukin-1 receptor type 1, and activating transcription factor 2, while central proteins in HFpEF were integrin subunit beta-2 and catenin beta-1. Biological pathways in HFrEF were related to DNA binding transcription factor activity, cellular protein metabolism, and regulation of nitric oxide biosynthesis. Unique pathways in patients with HFpEF were related to cytokine response, extracellular matrix organization, and inflammation. Biological pathways of patients with HF with a midrange ejection fraction were in between HFrEF and HFpEF. Network analysis showed that biomarker profiles specific for HFrEF are related to cellular proliferation and metabolism, whereas biomarker profiles specific for HFpEF are related to inflammation and extracellular matrix reorganization. (The BIOlogy Study to TAilored Treatment in Chronic Heart Failure [BIOSTAT-CHF]; EudraCT 2010-020808-29)
    Keywords: Biomarkers ; Hfpef ; Hfref ; Network Analysis ; Pathophysiology ; Medicine
    ISSN: 0735-1097
    E-ISSN: 1558-3597
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  • 5
    Language: English
    In: Journal of the American College of Cardiology, 30 January 2018, Vol.71(4), pp.386-398
    Description: Heart failure guidelines recommend up-titration of angiotensin-converting enzyme (ACE) inhibitor/angiotensin receptor blockers (ARBs), beta-blockers, and mineralocorticoid receptor antagonists (MRAs) to doses used in randomized clinical trials, but these recommended doses are often not reached. Up-titration may, however, not be necessary in all patients. This study sought to establish the role of blood biomarkers to determine which patients should or should not be up-titrated. Clinical outcomes of 2,516 patients with worsening heart failure from the BIOSTAT-CHF (BIOlogy Study to Tailored Treatment in Chronic Heart Failure) were compared between 3 theoretical treatment scenarios: scenario A, in which all patients are up-titrated to 〉50% of recommended doses; scenario B, in which patients are up-titrated according to a biomarker-based treatment selection model; and scenario C, in which no patient is up-titrated to 〉50% of recommended doses. The study conducted multivariable Cox regression using 161 biomarkers and their interaction with treatment, weighted for treatment-indication bias to estimate the expected number of deaths or heart failure hospitalizations at 24 months for all 3 scenarios. Estimated death or hospitalization rates in 1,802 patients with available (bio)markers were 16%, 16%, and 26%, respectively, in the ACE inhibitor/ARB up-titration scenarios A, B, and C. Similar rates for beta-blocker and MRA up-titration scenarios A, B, and C were 23%, 19%, and 24%, and 12%, 11%, and 24%, respectively. If up-titration was successful in all patients, an estimated 9.8, 1.3, and 12.3 events per 100 treated patients could be prevented at 24 months by ACE inhibitor/ARB, beta-blocker, and MRA therapy, respectively. Similar numbers were 9.9, 4.7, and 13.1 if up-titration treatment decision was based on a biomarker-based treatment selection model. Up-titrating patients with heart failure based on biomarker values might have resulted in fewer deaths or hospitalizations compared with a hypothetical scenario in which all patients were successfully up-titrated.
    Keywords: ACE Inhibitor/Arb ; Beta-Blocker ; Biomarkers ; Mra ; Treatment Decision ; Medicine
    ISSN: 0735-1097
    E-ISSN: 1558-3597
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  • 6
    Language: English
    In: International Journal of Cardiology, 15 February 2018, Vol.253, pp.84-90
    Description: Fibroblast growth factor (FGF) 23 is a hormone that increases urinary phosphate excretion and regulates renal sodium reabsorption and plasma volume. We studied the role of plasma FGF23 in therapy optimization and outcomes in patients with new-onset and worsening heart failure (HF). We measured plasma C-terminal FGF23 levels at baseline in 2399 of the 2516 patients included in the BIOlogy Study to Tailored Treatment in Chronic HF (BIOSTAT-CHF) trial. The association between FGF23 and outcome was evaluated by Cox regression analysis adjusted for potential confounders. Median FGF23 was 218.0 [IQR: 117.1–579.3] RU/ml; patients with higher FGF23 levels had a worse NYHA class, more signs of congestion, and were less likely to use an ACE-inhibitor (ACEi) or angiotensin receptor blocker (ARBs) at baseline (all 〈 0.01). Higher FGF23 levels were independently associated with higher BNP, lower eGFR, the presence of oedema and atrial fibrillation (all 0.001). In addition, higher FGF23 was independently associated with impaired uptitration of ACEi/ARBs after 3 months, but not of beta-blockers. In multivariable Cox regression analysis, FGF23 was independently associated with all-cause mortality (hazard ratio: 1.17 (1.09–1.26) per log increase, 〈 0.001), and the combined endpoint of all-cause mortality and HF hospitalization (1.15 (1.08–1.22) per log increase, 〈 0.001). In patients with new-onset and worsening HF, higher plasma FGF23 levels were independently associated with volume overload, less successful uptitration of ACEi/ARBs and an increased risk of all-cause mortality and HF hospitalization.
    Keywords: Heart Failure ; Fgf23 ; Volume Overload ; Prognosis ; Medicine
    ISSN: 0167-5273
    E-ISSN: 1874-1754
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  • 7
    Language: English
    In: Journal of rheumatology, 2011, Vol.38(9), pp.1884-1890
    Description: Objective. To evaluate the influence of inclusion criteria used in rheumatoid arthritis (RA) trials with adalimumab on clinical outcome and response. Methods. The different inclusion criteria of published trials of adalimumab in RA were separately applied to a large prospective cohort of patients with RA treated with adalimumab (AdRA cohort), thereby mimicking patient selection for a clinical trial. Clinical response and outcome in the resulting 11 projection groups were compared using the 28-joint Disease Activity Score (DAS28) and time-averaged DAS28 as outcome measures of efficacy. Results. Thirteen trials (n = 54-799) with 11 different sets of entry criteria were identified, resulting in 11 projection groups (n = 22-168). The DA528 at baseline was similar in the original trial and each projection group based on this trial (5.1-6.4, total AdRA cohort 5.1). After 28 weeks, the efficacy varied substantially among the 11 projected groups (change from baseline DAS28: -1.65 to -2.65, time-averaged DAS28 3.67-4.53). Expressed as outcome (DA528 at 28 weeks), the efficacy was much more similar for almost all projection groups (3.5-4.0) and thus appeared to be mostly independent of disease activity at baseline. Conclusion. We observed that different inclusion criteria for clinical trials can have a marked effect on the expected response, i.e., improvement from baseline. A novel finding is that final disease activity appeared much less dependent on initial disease activity. Our study suggests that for daily practice, one can assume that adalimumab treatment will on average result in a DAS28 between 3.5 and 4.0 after 28 weeks of treatment, regardless of baseline disease activity. (First Release June 15 2011; J Rheumatol 2011;38:1884-90; doi:10.3899/jrheum.101283)
    Keywords: Patient Selection ; Antibodies, Monoclonal, Humanized -- Therapeutic Use ; Antirheumatic Agents -- Therapeutic Use ; Arthritis, Rheumatoid -- Immunology ; Clinical Trials As Topic -- Methods;
    ISSN: 0315-162x
    ISSN: 0315162X
    E-ISSN: 14992752
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  • 8
    Language: English
    In: International journal of cardiology, 2018, Vol.253, pp.84-90
    Description: Background: Fibroblast growth factor (FGF) 23 is a hormone that increases urinary phosphate excretion and regulates renal sodium reabsorption and plasma volume. We studied the role of plasma FGF23 in therapy optimization and outcomes in patients with new-onset and worsening heart failure (HF). Methods: We measured plasma C-terminal FGF23 levels at baseline in 2399 of the 2516 patients included in the BIOlogy Study to Tailored Treatment in Chronic HF (BIOSTAT-CHF) trial. The association between FGF23 and outcome was evaluated by Cox regression analysis adjusted for potential confounders. Results: Median FGF23 was 218.0 [IQR: 117.1-579.3] RU/ml; patients with higher FGF23 levels had a worse NYHA class, more signs of congestion, and were less likely to use an ACE-inhibitor (ACEi) or angiotensin receptor blocker (ARBs) at baseline (all P 〈0.01). Higher FGF23 levels were independently associated with higher BNP, lower eGFR, the presence of oedema and atrial fibrillation (allP 〈0.001). In addition, higher FGF23 was independently associated with impaired uptitration of ACEi/ARBs after 3 months, but not of beta-blockers. In multivariable Cox regression analysis, FGF23 was independently associated with all-cause mortality (hazard ratio: 1.17 (1.09-1.26) per log increase, P 〈0.001), and the combined endpoint of all-cause mortality and HF hospitalization (1.15 (1.08-1.22) per log increase,P 〈0.001). Conclusions: In patients with new-onset and worsening HF, higher plasma FGF23 levels were independently associated with volume overload, less successful uptitration of ACEi/ARBs and an increased risk of all-cause mortality and HF hospitalization. (c) 2017 Elsevier B.V. All rights reserved
    ISSN: 0167-5273
    ISSN: 1874-1754
    Source: NARCIS (National Academic Research and Collaborations Information System)
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  • 9
    Language: English
    In: PLOS MEDICINE, 2018, Vol.15(3), pp.urn:issn:1549-1676
    Description: Background Comorbidities are common in patients with heart failure (HF) and complicate treatment and outcomes. We identified patterns of multimorbidity in Asian patients with HF and their association with patients' quality of life (QoL) and health outcomes. Methods and findings We used data on 6,480...
    Keywords: Preserved Ejection Fraction ; City Cardiomyopathy Questionnaire ; Quality-Of-Life ; Clinical Characteristics ; Noncardiac Comorbidities ; Renal-Function ; Association ; Classification ; Heterogeneity ; Performance
    ISSN: 1549-1676
    ISSN: 15491277
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  • 10
    Language: English
    In: Pharmaceutisch Weekblad, 2018, Vol.153(4), pp.8-9
    ISSN: 0031-6911
    Source: NARCIS (National Academic Research and Collaborations Information System)
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