scholarly journals Individual patient risk stratification of high-risk neuroblastomas using a two-gene score suited for clinical use

2015 ◽  
Vol 137 (4) ◽  
pp. 868-877 ◽  
Author(s):  
Kristoffer von Stedingk ◽  
Katleen De Preter ◽  
Jo Vandesompele ◽  
Rosa Noguera ◽  
Ingrid Øra ◽  
...  
Keyword(s):  
High Risk ◽  
Risk Stratification ◽  
Clinical Use ◽  
Gene Score ◽  
Patient Risk

Abstract 5585: Understanding Physicians’ Risk Stratification of Acute Coronary Syndromes: Insights from the Canadian ACS II Registry

Circulation ◽  
2008 ◽  
Vol 118 (suppl_18) ◽  
Author(s):  
Andrew T Yan ◽  
Raymond T Yan ◽  
Thao Huynh ◽  
Amparo Casanova ◽  
F. E Raimondo ◽  
...  
Keyword(s):  
Risk Assessment ◽  
High Risk ◽  
Risk Stratification ◽  
Risk Score ◽  
Acute Coronary Syndromes ◽  
Risk Scores ◽  
Risk Category ◽  
Patient Risk ◽  
Treatment Risk ◽  
Coronary Syndromes

An important treatment-risk paradox exists in the management of acute coronary syndromes (ACS). However, the process of risk stratification by physicians and its relationship to patient management have not been well studied. Our objective was to examine patient risk assessment by physician in relation to treatment and objective risk score evaluation, and the underlying patient characteristics that physicians consider to indicate high risk. The prospective Canadian ACS II Registry recruited 1956 patients admitted for non-ST elevation ACS in 36 hospitals in Oct 2002-Dec 2003. Patient risk assessment by the treating physician and management were recorded on standardized case report forms. We calculated the TIMI, PURSUIT and GRACE risk scores for each patient. Of the 1956 ACS patients, 347 (17.8%) patients were classified as low risk, 822 (42%) as intermediate risk, and 787 (40.2%) as high risk by their treating physicians. Patients considered as high risk were more likely to receive aggressive medical therapies and to undergo coronary angiography and revascularization. However, there were only weak correlations (Kendall’s tau-b correlation coefficients ranging from 0.08 to 0.14) between risk assessment by physicians and all 3 validated risk scores. Advanced age was an independent negative predictor. Furthermore, there was no significant association between the high risk category and several established prognosticators, such as history of heart failure, hemodynamic variables, and creatinine. Contemporary risk stratification of ACS appears suboptimal and may perpetuate the treatment-risk paradox. Physicians may not recognize and incorporate the most powerful adverse prognosticators into overall patient risk assessment. Routine use of validated risk score may enhance risk stratification and facilitate more appropriate tailoring of intensive therapies towards high-risk patients.

scholarly journals Risk assessment in precapillary pulmonary hypertension: a comparative analysis

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Thomas Sonnweber ◽  
Eva-Maria Schneider ◽  
Manfred Nairz ◽  
Igor Theurl ◽  
Günter Weiss ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Pulmonary Hypertension ◽  
High Risk ◽  
Risk Stratification ◽  
Risk Prediction ◽  
Mortality Risk ◽  
Assessment Tool ◽  
Risk Models ◽  
Non Invasive

Abstract Background Risk stratification is essential to assess mortality risk and guide treatment in patients with precapillary pulmonary hypertension (PH). We herein compared the accuracy of different currently used PH risk stratification tools and evaluated the significance of particular risk parameters. Methods We conducted a retrospective longitudinal observational cohort study evaluating seven different risk assessment approaches according to the current PH guidelines. A comprehensive assessment including multi-parametric risk stratification was performed at baseline and 4 yearly follow-up time-points. Multi-step Cox hazard analysis was used to analyse and refine risk prediction. Results Various available risk models effectively predicted mortality in patients with precapillary pulmonary hypertension. Right-heart catheter parameters were not essential for risk prediction. Contrary, non-invasive follow-up re-evaluations significantly improved the accuracy of risk estimations. A lack of accuracy of various risk models was found in the intermediate- and high-risk classes. For these patients, an additional evaluation step including assessment of age and right atrium area improved risk prediction significantly. Discussion Currently used abbreviated versions of the ESC/ERS risk assessment tool, as well as the REVEAL 2.0 and REVEAL Lite 2 based risk stratification, lack accuracy to predict mortality in intermediate- and high-risk precapillary pulmonary hypertension patients. An expanded non-invasive evaluation improves mortality risk prediction in these individuals.

scholarly journals The Indices of Cardiovascular Magnetic Resonance Derived Atrial Dynamics May Improve the Contemporary Risk Stratification Algorithms in Children with Hypertrophic Cardiomyopathy

2021 ◽  
Vol 10 (4) ◽  
pp. 650
Author(s):  
Lidia Ziółkowska ◽  
Łukasz Mazurkiewicz ◽  
Joanna Petryka ◽  
Monika Kowalczyk-Domagała ◽  
Agnieszka Boruc ◽  
...  
Keyword(s):  
Hypertrophic Cardiomyopathy ◽  
High Risk ◽  
Risk Stratification ◽  
Heart Association ◽  
The Novel ◽  
Identification Performance ◽  
Strong Trend ◽  
Prognostic Utility ◽  
Conduit Function ◽  
High Risk Children

Introduction: The most efficient risk stratification algorithms are expected to deliver robust and indefectible identification of high-risk children with hypertrophic cardiomyopathy (HCM). Here we compare algorithms for risk stratification in primary prevention in HCM children and investigate whether novel indices of biatrial performance improve these algorithms. Methods and Results: The endpoints were defined as sudden cardiac death, resuscitated cardiac arrest, or appropriate implantable cardioverter-defibrillator discharge. We examined the prognostic utility of classic American College of Cardiology/American Heart Association (ACC/AHA) risk factors, the novel HCM Risk-Kids score and the combination of these with indices of biatrial dynamics. The study consisted of 55 HCM children (mean age 12.5 ± 4.6 years, 69.1% males); seven had endpoints (four deaths, three appropriate ICD discharges). A strong trend (DeLong p = 0.08) was observed towards better endpoint identification performance of the HCM Risk-Kids Model compared to the ACC/AHA strategy. Adding the atrial conduit function component significantly improved the prediction capabilities of the AHA/ACC Model (DeLong p = 0.01) and HCM Risk-Kids algorithm (DeLong p = 0.04). Conclusions: The new HCM Risk-Kids individualised algorithm and score was capable of identifying high-risk children with very good accuracy. The inclusion of one of the atrial dynamic indices improved both risk stratification strategies.

scholarly journals Development of Molecular Magnetic Resonance Imaging Tools for Risk Stratification of Carotid Atherosclerotic Disease Using Dual-Targeted Microparticles of Iron Oxide

2021 ◽  
Author(s):  
Joyce M. S. Chan ◽  
Park Sung Jin ◽  
Michael Ng ◽  
Joanne Garnell ◽  
Chan Wan Ying ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Iron Oxide ◽  
High Risk ◽  
Magnetic Resonance ◽  
Carotid Artery ◽  
Risk Stratification ◽  
Stroke Prevention ◽  
Inflammatory Activity ◽  
Resonance Imaging ◽  
Inflammatory Status

AbstractIdentification of patients with high-risk asymptomatic carotid plaques remains a challenging but crucial step in stroke prevention. Inflammation is the key factor that drives plaque instability. Currently, there is no imaging tool in routine clinical practice to assess the inflammatory status within atherosclerotic plaques. We have developed a molecular magnetic resonance imaging (MRI) tool to quantitatively report the inflammatory activity in atherosclerosis using dual-targeted microparticles of iron oxide (DT-MPIO) against P-selectin and VCAM-1 as a smart MRI probe. A periarterial cuff was used to generate plaques with varying degree of phenotypes, inflammation and risk levels at specific locations along the same single carotid artery in an Apolipoprotein-E-deficient mouse model. Using this platform, we demonstrated that in vivo DT-MPIO-enhanced MRI can (i) target high-risk vulnerable plaques, (ii) differentiate the heterogeneity (i.e. high vs intermediate vs low-risk plaques) within the asymptomatic plaque population and (iii) quantitatively report the inflammatory activity of local plaques in carotid artery. This novel molecular MRI tool may allow characterisation of plaque vulnerability and quantitative reporting of inflammatory status in atherosclerosis. This would permit accurate risk stratification by identifying high-risk asymptomatic individual patients for prophylactic carotid intervention, expediting early stroke prevention and paving the way for personalised management of carotid atherosclerotic disease.

Investigation of a 22-gene genomic classifier (GC) for risk stratification and molecular subtyping in an Asian prostate cancer (PCa) cohort.

2021 ◽  
Vol 39 (6_suppl) ◽  
pp. 249-249
Author(s):  
Wei Loong Sherman Yee ◽  
Wai Yee Woo ◽  
Adelene Sim ◽  
Kar Perng Low ◽  
Alice Meng ◽  
...  
Keyword(s):  
High Risk ◽  
Risk Stratification ◽  
Racial Differences ◽  
White Men ◽  
Risk Groups ◽  
Molecular Subtyping ◽  
Basal Subtype ◽  
Grid Database ◽  
Risk Patients ◽  
Very High

249 Background: A 22-gene GC has been proposed to refine risk stratification of localized PCa by conventional NCCN criteria, and this may potentially influence treatment recommendations. Nonetheless, majority of studies looking at the utility of GC were conducted in White and non-White men from Western cohorts. We therefore investigated the association of GC with NCCN risk groups (RG) in an Asian PCa cohort. Additionally, we examined for inter-racial differences in molecular subtyping between Asian and White/non-White PCa. Methods: GC (Decipher Biosciences Inc., CA) was performed on diagnostic biopsies of men who were treated with radiotherapy +/- hormonal therapy at a single institution (N = 75). ISUP Gleason’s grade (GG) and tumor cellularity were reviewed by an expert GU pathologist. RNA was extracted from 2 x 2.0-mm tumor cores using Qiagen AllPrep DNA/RNA FFPE Kit (Qiagen, Germany) and gene expression was performed on Affymetrix Human Exon 1.0 ST Array (ThermoFischer, CA). PAM50 molecular subtyping was derived using the DecipherGRID database. Results: We profiled 80 tumors from 75 patients, comprising of 18 (24.0%), 9 (12.0%), 21 (28.0%), and 19 (25.3%) NCCN low-/favorable intermediate-, unfavorable intermediate-, high- and very high-RG, respectively; of note, 8 (10.7%) patients had regional/metastatic disease at diagnosis. Using the GC, 27 (33.8%), 14 (17.5%) and 39 (48.8%) were classified as low- (<0.45), intermediate- (0.45-0.6) and high-RG, respectively (>0.6). When stratified using a three-tier clinico-genomic (CG) classification system (Spratt et al. 2017), 6 of 21 (28.6%) NCCN-defined high-risk and 4 of 19 (21.1%) very high-risk patients were downgraded to CG-defined intermediate-/low-risk, while 2 of 27 (7.4%) NCCN low-/intermediate-risk patients were in fact upgraded to CG high-risk. Next, we interrogated the PAM50 basal-luminal signature in our cohort. Interestingly, when matched to White (N = 5762) and non-White (N = 155) for NCCN RG, ISUP GG and age, we observed a high proportion of basal subtype (62.7%) in Asians, which contrasted the prevalence observed in White (16.7%) and non-White (15.9%) North American patients (Chi-sq P <0.001). Conclusions: Here, we demonstrated the utility of the 22-gene GC for refining the NCCN risk stratification in a largest Asian PCa dataset to-date. An unexpectedly high proportion of PAM50 basal-subtype was observed, suggesting race-specific differences of the tumor transcriptome.

Abstract P019: A Single Model For Predicting Major Adverse Cardiovascular Events In Individuals With And Without History Of Atherosclerotic Cardiovascular Disease: The Atherosclerosis Risk In Communities (aric) Study

Circulation ◽  
2021 ◽  
Vol 143 (Suppl_1) ◽  
Author(s):  
Yejin Mok ◽  
Lena Mathews ◽  
Ron C Hoogeveen ◽  
Michael J Blaha ◽  
Christie M Ballantyne ◽  
...  
Keyword(s):  
Myocardial Infarction ◽  
Cardiovascular Disease ◽  
High Risk ◽  
Risk Stratification ◽  
Cardiovascular Events ◽  
Major Adverse Cardiovascular Events ◽  
Atherosclerotic Cardiovascular Disease ◽  
Single Model ◽  
History Of ◽  
Very High

Background: In the 2018 AHA/ACC Cholesterol guideline, risk stratification is an essential element. The use of a Pooled Cohort Equation (PCE) is recommended for individuals without atherosclerotic cardiovascular disease (ASCVD), and the new dichotomous classification of very high-risk vs. high-risk has been introduced for patients with ASCVD. These distinct risk stratification systems mainly rely on traditional risk factors, raising the possibility that a single model can predict major adverse cardiovascular events (MACEs) in persons with and without ASCVD. Methods: We studied 11,335 ARIC participants with (n=885) and without (n=10,450) a history of ASCVD (myocardial infarction, ischemic stroke, and symptomatic peripheral artery disease) at baseline (1996-98). We modeled factors in the PCE and the new classification for ASCVD patients (Figure legend) in a single CVD prediction model. We examined their associations with MACEs (myocardial infarction, stroke, and heart failure) using Cox models and evaluated the discrimination and calibration for a single model including those factors. Results: During a median follow-up of 18.4 years, there were 3,658 MACEs (3,105 in participants without ASCVD). In general, the factors in the PCE and the risk classification system for ASCVD patients were associated similarly with MACEs regardless of baseline ASCVD status, although age and systolic blood pressure showed significant interactions. A single model with these predictors and the relevant interaction terms showed good calibration and discrimination for those with and without ASCVD (c-statistic=0.729 and 0.704, respectively) (Figure). Conclusion: A single CVD prediction model performed well in persons with and without ASCVD. This approach will provide a specific predicted risk to ASCVD patients (instead of dichotomy of very high vs. high risk) and eliminate a practice gap between primary vs. secondary prevention due to different risk prediction tools.

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