Dataset Information

Identifying Subpopulations with Distinct Response to Treatment Using Plasma Biomarkers in Acute Heart Failure: Results from the PROTECT Trial : Differential Response in Acute Heart Failure.

ABSTRACT: Over the last 50 years, clinical trials of novel interventions for acute heart failure (AHF) have, with few exceptions, been neutral or shown harm. We hypothesize that this might be related to a differential response to pharmacological therapy.We studied the magnitude of treatment effect of rolofylline across clinical characteristics and plasma biomarkers in 2033 AHF patients and derived a biomarker-based responder sum score model. Treatment response was survival from all-cause mortality through day 180.In the overall study population, rolofylline had no effect on mortality (HR 1.03, 95% CI 0.82-1.28, p = 0.808). We found no treatment interaction across clinical characteristics, but we found interactions between several biomarkers and rolofylline. The biomarker-based sum score model included TNF-R1?, ST2, WAP four-disulfide core domain protein HE4 (WAP-4C), and total cholesterol, and the score ranged between 0 and 4. In patients with score 4 (those with increased TNF-R1?, ST2, WAP-4C, and low total cholesterol), treatment with rolofylline was beneficial (HR 0.61, 95% CI 0.40-0.92, p = 0.019). In patients with score 0, treatment with rolofylline was harmful (HR 5.52, 95% CI 1.68-18.13, p = 0.005; treatment by score interaction p < 0.001). Internal validation estimated similar hazard ratio estimates (0 points: HR 5.56, 95% CI 5.27-7-5.87; 1 point: HR 1.31, 95% CI 1.25-1.33; 2 points: HR 0.75, 95% CI 0.74-0.76; 3 points: HR 1.13, 95% CI 1.11-1.15; 4 points, HR 0.61, 95% CI 0.61-0.62) compared to the original data.Biomarkers are superior to clinical characteristics to study treatment heterogeneity in acute heart failure.

SUBMITTER: Liu LCY

PROVIDER: S-EPMC5550531 | biostudies-literature | 2017 Jun

REPOSITORIES: biostudies-literature

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Identifying Subpopulations with Distinct Response to Treatment Using Plasma Biomarkers in Acute Heart Failure: Results from the PROTECT Trial : Differential Response in Acute Heart Failure.

Liu Licette C Y LCY Valente Mattia A E MAE Postmus Douwe D O'Connor Christopher M CM Metra Marco M Dittrich Howard C HC Ponikowski Piotr P Teerlink John R JR Cotter Gad G Davison Beth B Cleland John G F JGF Givertz Michael M MM Bloomfield Daniel M DM van Veldhuisen Dirk J DJ Hillege Hans L HL van der Meer Peter P Voors Adriaan A AA

Cardiovascular drugs and therapy 20170601 3

<h4>Background</h4>Over the last 50 years, clinical trials of novel interventions for acute heart failure (AHF) have, with few exceptions, been neutral or shown harm. We hypothesize that this might be related to a differential response to pharmacological therapy.<h4>Methods</h4>We studied the magnitude of treatment effect of rolofylline across clinical characteristics and plasma biomarkers in 2033 AHF patients and derived a biomarker-based responder sum score model. Treatment response was surviv ...[more]

PMID: 28656542

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Project description:Patients with acute heart failure (AHF) are included into clinical trials regardless of differences in baseline clinical characteristics. The aim of this study was to assess patients with AHF according to the presence of central and/or peripheral congestion at hospital admission and evaluate treatment response and outcomes in studied phenotypes. We investigated retrospectively 352 patients (mean age: 68 ± 13 years, 77% men) hospitalized due to AHF with the signs of congestion on admission. Patients were divided according to the type of signs of congestion into three groups: A, isolated pulmonary congestion (n = 52, 15%); B, isolated peripheral congestion (n = 31, 9%); and C, signs of mixed (peripheral and central) congestion (n = 269, 76%). Patients from Group A had lower concentration of urea, bilirubin, and gamma-glutamyl transferase whereas higher level of haematocrit, albumin, and leukocytes on admission. The highest baseline N-terminal pro-B-type natriuretic peptide level (median: 4113 vs. 3634 vs. 6093 pg/mL) and percentage of patients with chronic heart failure (56 vs. 58 vs. 74%; A vs. B. vs. C, respectively, all P < 0.01) were observed in Group C. There were no differences in terms of demographics, co-morbidities, left ventricular ejection fraction, and applied treatment between studied groups. Patients from Group A had the highest systolic blood pressure on admission (145 ± 37 vs. 122 ± 20 vs. 130 ± 29 mmHg) and the biggest decrease in systolic blood pressure [-22 (-45 to -4) vs. -2 (-13 to 2) vs. -10 (-25 to 0) mmHg] and heart rate [-16 (-35 to -1.5) vs. -1 (-10 to 5) vs. -7 (-20 to 0) b.p.m.] with the lowest weight change [-1.0 (-1.0 to 0) vs. -2.9 (-3.8 to -0.9) vs. -2.0 (-3.0 to -1.0) kg; all P < 0.01] after 48 h of hospitalization. There were differences in short-term and long-term outcomes with favourable results in Group A. Group A experienced less frequent in-hospital heart failure worsening during the first 48 h (4 vs. 23 vs. 7%), had shorter length of hospital stay [6 (5-8) vs. 7 (5-11) vs. 7 (6-11) days], and had lower 1 year all-cause mortality (12 vs. 28 vs. 29%; all P < 0.05). Presence of peripheral congestion on admission was independent predictor for all-cause mortality within 1 year [hazard ratio (95% confidence interval): 2.68 (1.06-6.79); P = 0.04]. Patterns of congestion in AHF are associated with differences in clinical characteristics, treatment response, and outcomes. It needs to be considered once planning clinical trials in AHF.

Project description:AimsThe importance of true worsening renal failure (WRF), which is associated with a poor prognosis, had been suggested in patients with acute heart failure (AHF). The aim of the present study was to establish the biomarker strategy for the prediction of true WRF in AHF.Methods and resultsTwo hundred eighty-one patients with AHF were analysed. Their biomarkers were measured within 30 min of admission. Patients were assigned to the non-WRF (n = 168), pseudo-WRF (n = 56), or true-WRF (n = 57) groups using the criteria of both acute kidney injury on admission and increasing serum creatinine value during the first 7 days. A Kaplan-Meier curve showed that the survival and heart failure event rate of the true-WRF group within 1000 days was significantly lower than that of the non-WRF and pseudo-WRF groups (P ≤ 0.001). The multivariate Cox regression model also indicated that true WRF was an independent predictor of 1000 day mortality and heart failure events [hazard ratio: 4.315, 95% confidence interval (CI): 2.466-7.550, P ≤ 0.001, and hazard ratio: 2.834, 95% CI: 1.893-4.243, P ≤ 0.001, respectively]. The serum heart-type fatty acid-binding protein (s-HFABP) levels were significantly higher in the true-WRF group than in the non-WRF and pseudo-WRF groups (P ≤ 0.001). The multivariate logistic regression model indicated that the predictive biomarker for the true-WRF group was the s-HFABP level (odds ratio: 5.472, 95% CI: 2.729-10.972, P ≤ 0.001). The sensitivity and specificity for indicating the presence of true WRF were 73.7% and 76.8% (area under the curve = 0.831) for s-HFABP in whole patients, respectively, and 94.7% and 72.7% (area under the curve = 0.904) in non-chronic kidney disease (CKD) patients, respectively.ConclusionsCardiac biomarkers, especially the s-HFABP, might predict the development of true WRF in AHF patients. Furthermore, the predictive value was higher in AHF patients without CKD than in those with CKD.

Project description:Heart failure (HF) and osteoarthritis (OA) are medical conditions that can significantly impact daily activities. Evidence has shown that HF and OA may share some pathogenic mechanisms. However, the underlying genomic mechanisms remain unclear. This study aimed to explore the underlying molecular mechanism and identify diagnostic biomarkers for HF and OA. With the cutoff criteria of fold change (FC) > 1.3 and P < .05, 920, 1500, 2195, and 2164 differentially expressed genes (DEGs) were identified in GSE57338, GSE116250, GSE114007, and GSE169077, respectively. After making the intersection of DEGs, we obtained 90 upregulated DEGs and 51 downregulated DEGs in HF datasets and 115 upregulated DEGs and 75 downregulated DEGs in OA datasets. Afterward, we conducted genome ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses, protein-protein interaction (PPI) networks, and hub genes screening based on DEGs. Then, 4 common DEGs (fibroblast activation protein alpha [FAP], secreted frizzled-related protein 4 (SFRP4), Thy-1 cell surface antigen (THY1), matrix remodeling associated 5 [MXRA5]) between HF and OA were screened and validated in GSE5406 and GSE113825 datasets, based on which we established the support vector machine (SVM) models. The combined area under the receiver operating characteristic curve (AUC) of THY1, FAP, SFRP4, and MXRA5 in the HF training and test sets reached 0.949 and 0.928. While in the OA training set and test set, the combined AUC of THY1, FAP, SFRP4, and MXRA5 reached 1 and 1, respectively. The analysis of immune cells in HF revealed high levels of dendritic cell (DC), B cells, natural killer T cell (NKT), Type 1 regulatory T cell (Tr1), cytotoxic T cell (Tc), exhausted T cell (Tex), and mucosal-associated invariant T cell (MAIT), while displaying lower levels of monocytes, macrophages, NK, CD4 + T, gamma delta T (γδ T), T helper type 1 (Th1), T helper type 2 (Th2), and effector memory T cell (Tem). Moreover, the 4 common DEGs were positively correlated with DCs and B cells and negatively correlated with γδ T. In OA patients, the abundance of monocyte, macrophage, CD4 + naïve, and natural T regulatory cell (nTreg) was higher, while the infiltration of CD8 + T, γδ T, CD8 + naïve, and MAIT was lower. The expression of THY1 and FAP was significantly correlated with macrophage, CD8 + T, nTreg, and CD8 + naïve. SFRP4 was correlated with monocyte, CD8 + T, γδ T, CD4 + naïve, nTreg, CD8 + naïve and MAIT. MXRA5 was correlated with macrophage, CD8 + T, nTreg and CD8 + naïve. FAP, THY1, MXRA5, and SFRP4 may be diagnostic biomarkers for both HF and OA, and their correlation with immune cell infiltrations suggests shared immune pathogenesis.

Dataset Information

Identifying Subpopulations with Distinct Response to Treatment Using Plasma Biomarkers in Acute Heart Failure: Results from the PROTECT Trial : Differential Response in Acute Heart Failure.

Publications

Identifying Subpopulations with Distinct Response to Treatment Using Plasma Biomarkers in Acute Heart Failure: Results from the PROTECT Trial : Differential Response in Acute Heart Failure.

Similar Datasets

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