scholarly journals ESC 2019 guidelines on chronic coronary syndromes: can calcium scoring improve the risk underestimation associated with the updated pre-test probability risk score?

2021 ◽  
Vol 22 (Supplement_1) ◽  
Author(s):  
S Fyyaz ◽  
H Rasoul ◽  
O Olabintan ◽  
S David ◽  
S Plein ◽  
...  
Keyword(s):  
Chest Pain ◽  
Risk Score ◽  
Calcium Score ◽  
Low Risk ◽  
Risk Scores ◽  
Severe Stenosis ◽  
Mild Stenosis ◽  
Number Of Patients ◽  
Stable Chest Pain ◽  
Test Probability

Abstract Funding Acknowledgements Type of funding sources: None. Introduction The European Society of Cardiology (ESC) published an updated stable chest pain guideline in 2019. It recommends the use of an updated pre-test probability (PTP) risk score (RS) to assess the likelihood of coronary artery disease (CAD), to try and reduce the risk overestimation associated with previous risk scores. We sought to assess the performance of the 2019 PTPRS in a contemporary cohort of patients undergoing CT coronary angiography (CTCA). Furthermore, we focussed on patients with PTPRS <15%, and assessed the utility of CT calcium scores as a discriminator of risk. Methods 652 patients who were investigated with CTCA for stable chest pain between January 2017 and May 2018 were included in a retrospective analysis. CTCA reported CAD degree of stenosis as normal/minimal stenosis, mild (30-50%), moderate (50-70%), or severe (>70%). ESC 2019 pre-test probability risk scores were retrospectively calculated and compared. Results A total of 652 patients underwent CTCA between 01 January 2017 and 31 May 2018, of which 330 were male and 322 were female, with an average age of 55 years ±11 years. Using the ESC 2019 PTPRS there were no patients with PTPRS >85%. 2 patients had PTPRS 50-85%; one patient had moderate stenosis and one mild stenosis on CTCA.  There were 267 patients with PTPRS 15-50%; 23 (9%) patients had severe CTCA stenosis, 37 (14%) a moderate stenosis, and 34 (13%) a mild stenosis. A further 379 patients had PTPRS <15%; 11 (3%) had severe stenosis and 20 (5%) moderate stenosis. A further 27 (7%) patients had mild CTCA stenosis.  A total of 357 of 379 patients with PTPRS <15% based on ESC 2019 had a CT calcium score. 236 patients were found to have a calcium score of zero, and 121 patients had a score greater than zero, with a range between 1 and 930. Of patients with zero calcium score, only 1 (0.4%) patient had severe stenosis, 2 (0.8%) moderate stenoses and 6 (2.5%) mild stenosis. In contrast, in patients with positive calcium scores, 10 (8%) had severe stenosis, 18 (15%) moderate stenosis, and 22 (18%) mild stenosis. Conclusions The ESC 2019 PTPRS classified this as an overall low risk cohort. The downward risk modification of PTPRS has led to a large number of patients being classified as low risk with PTPRS <15%. No or deferred investigation is recommended by the ESC in this cohort. However, the use of CT calcium scores  in patients with PTPRS <15%, detected the majority of patients with any degree of CAD. CT calcium scores are a simple and low cost risk modifier, and may help identify patients who may benefit from primary prevention as per SCOT-Heart. Patients with calcium score greater than zero could be investigated with CTCA.

ESC guidelines on stable chest pain: a comparison of the previous and current risk scores for the assessment of pre-test probability of coronary artery disease

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
S Fyyaz ◽  
O Olabintan ◽  
S David ◽  
S Plein ◽  
K Alfakih
Keyword(s):  
Coronary Artery Disease ◽  
Chest Pain ◽  
Coronary Artery ◽  
Risk Scores ◽  
Severe Stenosis ◽  
Mild Stenosis ◽  
Esc Guidelines ◽  
Artery Disease ◽  
Stable Chest Pain ◽  
Test Probability

Abstract Introduction The European Society of Cardiology (ESC) guidelines on stable chest pain recommend the use of a pre-test probability (PTP) risk score (RS) which predicts the likelihood of coronary artery disease (CAD) to guide investigation and modality. The 2019 guidelines provide an updated PTPRS compared with 2013 guidelines, adjusted for the lower prevalence of coronary artery disease in contemporary populations. We assessed the performance of the two PTPRS in a cohort of patients with stable chest pain who underwent CT coronary angiography (CTCA) as the first line investigation. Methods We retrospectively searched a radiology database from January 2017 to June 2018. CTCA reported CAD degree of stenosis as normal/minimal stenosis, mild (30–50%), moderate (50–70%), or severe (>70%) and retrospectively calculated ESC PTP scores for 2013 and 2019 guidelines. Results In total 652 patients underwent CTCA (mean age 55 yrs; IQR 48–63; 330 male). For ESC 2019 PTPRS there were no patients with PTP >85%. 2 patients had PTP 50–85%; 1 patient had moderate stenosis and 1 mild stenosis on CTCA. 267 patients had PTP 15–50%; 23 (9%) had severe stenosis and 35 (13%) moderate stenosis. Finally, 379 patients had PTP <15%; 11 (3%) had severe stenosis and 18 (5%) moderate CTCA stenosis. In comparison, ESC 2013 PTPRS had 2 patients with PTP >85%; 1 had moderate stenosis and 1 had mild stenosis on CTCA. 149 patients had PTP 50–85%; 17 (11%) had severe stenosis and 23 (15%) moderate stenosis. A further 427 patients had a PTP 15–50%; 17 (4%) had severe stenosis and 32 (8%) had moderate stenosis. Lastly, 70 patients had a PTP <15% and two (3%) were found to have a moderate stenosis on CTCA. Conclusions The updated ESC 2019 PTPRS appears to underestimate the presence of CAD given 11 (3%) patients with severe CTCA stenosis would have been missed. Although the 2013 PTPRS was thought to overestimate the prevalence of CAD, it did not miss anyone found to have severe CTCA stenosis. Furthermore, patients with evidence of mild or moderate CAD on CTCA may not have been investigated due to PTP <15% and therefore may not be commenced on medical therapy, to derive a mortality benefit as demonstrated in SCOT-Heart trial. Funding Acknowledgement Type of funding source: None

scholarly journals ESC 2019 guidelines on chronic coronary syndromes: could calcium scoring improve detection of coronary artery disease in patients with low risk score. Findings from a retrospective cohort of patients in a district general hospital

2021 ◽  
Vol 10 ◽  
pp. 204800402110327
Author(s):  
S Fyyaz ◽  
H Rasoul ◽  
C Miles ◽  
O Olabintan ◽  
S David ◽  
...  
Keyword(s):  
Coronary Artery Disease ◽  
Chest Pain ◽  
Coronary Artery ◽  
Risk Score ◽  
Calcium Score ◽  
District General Hospital ◽  
Artery Disease ◽  
Stable Chest Pain ◽  
Zero Calcium Score ◽  
European Society Of Cardiology

Background The European Society of Cardiology (ESC) published an updated stable chest pain guideline in 2019, recommending the use of an updated pre-test probability (PTP) risk score (RS) to assess the likelihood of coronary artery disease (CAD). We sought to compare the 2019 and 2013 PTPRS in a contemporary cohort of patients. Methods 612 patients who were investigated with computed tomography coronary angiography (CTCA) for stable chest pain were included in a retrospective analysis. Results There were 255 patients with 2019 PTPRS 15–50% with a 9% yield of severe CAD on CTCA, compared with 402 patients and a 4% yield using the 2013 PTPRS (p = 0.01). 355 patients had a 2019 PTPRS of <15%, with 3% found to have severe CAD, compared with 67 patients and none with severe CAD using the 2013 PTPRS (p = 0.14). 336 of patients with 2019 PTPRS of <15% had a calcium score as part of the CTCA. 223 of these had a zero calcium score and only one had severe CAD. In comparison, 113 patients had a positive calcium score, and 10 (9%) had severe CAD (p < 0.001). Discussion The ESC 2019 PTPRS classifies more patients as at lower risk of CAD and hence reduces the risk overestimation associated with the 2013 PTPRS. However, in patients with a 2019 PTPRS of <15%, who would not be investigated, the use of the calcium score detected the majority of patients with significant CAD, who may benefit from secondary prevention and an associated mortality benefit as per the SCOT-Heart trial.

scholarly journals Assessing the clinical utility of genetic risk scores for targeted cancer screening

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Carly A. Conran ◽  
Zhuqing Shi ◽  
William Kyle Resurreccion ◽  
Rong Na ◽  
Brian T. Helfand ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Primary Care ◽  
High Risk ◽  
Risk Score ◽  
Genetic Risk ◽  
Clinical Utility ◽  
Low Risk ◽  
Risk Scores ◽  
Average Risk ◽  
Genetic Risk Scores

Abstract Background Genome-wide association studies have identified thousands of disease-associated single nucleotide polymorphisms (SNPs). A subset of these SNPs may be additively combined to generate genetic risk scores (GRSs) that confer risk for a specific disease. Although the clinical validity of GRSs to predict risk of specific diseases has been well established, there is still a great need to determine their clinical utility by applying GRSs in primary care for cancer risk assessment and targeted intervention. Methods This clinical study involved 281 primary care patients without a personal history of breast, prostate or colorectal cancer who were 40–70 years old. DNA was obtained from a pre-existing biobank at NorthShore University HealthSystem. GRSs for colorectal cancer and breast or prostate cancer were calculated and shared with participants through their primary care provider. Additional data was gathered using questionnaires as well as electronic medical record information. A t-test or Chi-square test was applied for comparison of demographic and key clinical variables among different groups. Results The median age of the 281 participants was 58 years and the majority were female (66.6%). One hundred one (36.9%) participants received 2 low risk scores, 99 (35.2%) received 1 low risk and 1 average risk score, 37 (13.2%) received 1 low risk and 1 high risk score, 23 (8.2%) received 2 average risk scores, 21 (7.5%) received 1 average risk and 1 high risk score, and no one received 2 high risk scores. Before receiving GRSs, younger patients and women reported significantly more worry about risk of developing cancer. After receiving GRSs, those who received at least one high GRS reported significantly more worry about developing cancer. There were no significant differences found between gender, age, or GRS with regards to participants’ reported optimism about their future health neither before nor after receiving GRS results. Conclusions Genetic risk scores that quantify an individual’s risk of developing breast, prostate and colorectal cancers as compared with a race-defined population average risk have potential clinical utility as a tool for risk stratification and to guide cancer screening in a primary care setting.

scholarly journals Identifying individuals with high risk of Alzheimer’s disease using polygenic risk scores

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Ganna Leonenko ◽  
Emily Baker ◽  
Joshua Stevenson-Hoare ◽  
Annerieke Sierksma ◽  
Mark Fiers ◽  
...  
Keyword(s):  
High Risk ◽  
Risk Score ◽  
Genetic Risk ◽  
Prediction Accuracy ◽  
Genetic Risk Score ◽  
Low Risk ◽  
Risk Scores ◽  
Sample Mean ◽  
Polygenic Risk ◽  
Reliable Identification

AbstractPolygenic Risk Scores (PRS) for AD offer unique possibilities for reliable identification of individuals at high and low risk of AD. However, there is little agreement in the field as to what approach should be used for genetic risk score calculations, how to model the effect of APOE, what the optimal p-value threshold (pT) for SNP selection is and how to compare scores between studies and methods. We show that the best prediction accuracy is achieved with a model with two predictors (APOE and PRS excluding APOE region) with pT<0.1 for SNP selection. Prediction accuracy in a sample across different PRS approaches is similar, but individuals’ scores and their associated ranking differ. We show that standardising PRS against the population mean, as opposed to the sample mean, makes the individuals’ scores comparable between studies. Our work highlights the best strategies for polygenic profiling when assessing individuals for AD risk.

scholarly journals Pre-test probability risk scores and their use in contemporary management of patients with chest pain: One year stress echo cohort study

JRSM Open ◽  
2015 ◽  
Vol 6 (11) ◽  
pp. 205427041561129
Author(s):  
Daniela Cassar Demarco ◽  
Alexandros Papachristidis ◽  
Damian Roper ◽  
Ioannis Tsironis ◽  
Jonathan Byrne ◽  
...  
Keyword(s):  
Cohort Study ◽  
Chest Pain ◽  
Risk Scores ◽  
Stress Echo ◽  
Contemporary Management ◽  
One Year ◽  
Test Probability

scholarly journals Pre-test probability of obstructive coronary artery disease in the new guidelines: too much, too little or just enough?

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
P Lopes ◽  
F Albuquerque ◽  
P Freitas ◽  
B Rocha ◽  
G Cunha ◽  
...  
Keyword(s):  
Coronary Artery Disease ◽  
Chest Pain ◽  
Obstructive Coronary Artery Disease ◽  
P Value ◽  
Coronary Syndrome ◽  
Luminal Stenosis ◽  
Artery Disease ◽  
Stable Chest Pain ◽  
New Guidelines ◽  
Test Probability

Abstract Background Previous 2013 ESC guidelines recommended the use of the Modified Diamond-Forrester method to assess the pre-test probability (PTP) of obstructive coronary artery disease (CAD). The 2019 ESC Chronic Coronary Syndrome guidelines updated this recommendation with a major downgrade in PTP. The aim of this study was to compare the performance of these two methods in patients with stable chest pain undergoing coronary computed tomography angiography (CCTA) for suspected CAD. Methods We performed a retrospective analysis on prospectively collected data from a cohort of consecutive patients undergoing CCTA for suspected CAD from October 2016 to 2019. Key exclusion criteria were age &lt;30 years-old, known CAD, suspected acute coronary syndrome or symptoms other than chest pain. Obstructive CAD was defined as any luminal stenosis ≥50% on CCTA. Whenever invasive coronary angiography (ICA) was subsequently performed, patients were reclassified if luminal stenosis was &lt;50%. The two PTP prediction models were assessed for calibration and discrimination. Results A total of 320 patients (median age 63 years [IQR 53–70], 59% women) were included. Chest pain characteristics were: 48% atypical angina, 38% non-anginal chest pain, 14% typical angina. The observed prevalence of obstructive CAD was 16.3% (n=52). Patients with obstructive CAD were more often male, were significantly older and had a higher prevalence of typical angina and cardiovascular risk factors (except for family history of CAD). On average, individual PTP was 22.1% lower in the new guidelines. The 2013 prediction model significantly overestimated the likelihood of obstructive CAD (mean PTP 37.3% vs 16.3%; relative overestimation of 130%, p-value for miscalibration 0.005). The updated 2019 method showed good calibration for predicting the likelihood of obstructive CAD (mean PTP 15.2% vs 16.3%; relative underestimation of 6.5%, p-value for miscalibration 0.712). The two approaches showed similar discriminative power, with a C-statistics of 0.730 and 0.735 for the 2013 and 2019 methods, respectively (p-value for comparison 0.933). Stratification by gender produced similar results. Conclusions In patients with stable chest pain undergoing CCTA, the updated 2019 prediction model allows for a more precise estimation of pre-test probabilities of obstructive CAD than the previous model. Adoption of this new score may improve disease prediction and change the downstream diagnostic pathway in a significant proportion of cases. Graph 1 Funding Acknowledgement Type of funding source: None

scholarly journals TYROBP, TLR4 and ITGAM regulated macrophages polarization and immune checkpoints expression in osteosarcoma

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Tuo Liang ◽  
Jiarui Chen ◽  
GuoYong Xu ◽  
Zide Zhang ◽  
Jiang Xue ◽  
...  
Keyword(s):  
Risk Score ◽  
Immune Cell ◽  
Risk Model ◽  
Low Risk ◽  
Risk Scores ◽  
Immune Checkpoints ◽  
Kegg Pathways ◽  
Gene Sets ◽  
Macrophages Polarization ◽  
Immune Related Genes

AbstractWe established a relationship among the immune-related genes, tumor-infiltrating immune cells (TIICs), and immune checkpoints in patients with osteosarcoma. The gene expression data for osteosarcoma were downloaded from UCSC Xena and GEO database. Immune-related differentially expressed genes (DEGs) were detected to calculate the risk score. “Estimate” was used for immune infiltrating estimation and “xCell” was used to obtain 64 immune cell subtypes. Furthermore, the relationship among the risk scores, immune cell subtypes, and immune checkpoints was evaluated. The three immune-related genes (TYROBP, TLR4, and ITGAM) were selected to establish a risk scoring system based on their integrated prognostic relevance. The GSEA results for the Hallmark and KEGG pathways revealed that the low-risk score group exhibited the most gene sets that were related to immune-related pathways. The risk score significantly correlated with the xCell score of macrophages, M1 macrophages, and M2 macrophages, which significantly affected the prognosis of osteosarcoma. Thus, patients with low-risk scores showed better results with the immune checkpoints inhibitor therapy. A three immune-related, gene-based risk model can regulate macrophage activation and predict the treatment outcomes the survival rate in osteosarcoma.

scholarly journals Development of an ensemble machine learning prognostic model to predict 60-day risk of major adverse cardiac events in adults with chest pain

2021 ◽  
Author(s):  
Chris J. Kennedy ◽  
Dustin G. Mark ◽  
Jie Huang ◽  
Mark J. van der Laan ◽  
Alan E. Hubbard ◽  
...  
Keyword(s):  
Machine Learning ◽  
Logistic Regression ◽  
Chest Pain ◽  
Random Forest ◽  
Decision Trees ◽  
Low Risk ◽  
Major Adverse Cardiac Events ◽  
Risk Scores ◽  
Cardiac Events ◽  
Adverse Cardiac Events

Background: Chest pain is the second leading reason for emergency department (ED) visits and is commonly identified as a leading driver of low-value health care. Accurate identification of patients at low risk of major adverse cardiac events (MACE) is important to improve resource allocation and reduce over-treatment. Objectives: We sought to assess machine learning (ML) methods and electronic health record (EHR) covariate collection for MACE prediction. We aimed to maximize the pool of low-risk patients that are accurately predicted to have less than 0.5% MACE risk and may be eligible for reduced testing. Population Studied: 116,764 adult patients presenting with chest pain in the ED and evaluated for potential acute coronary syndrome (ACS). 60-day MACE rate was 1.9%. Methods: We evaluated ML algorithms (lasso, splines, random forest, extreme gradient boosting, Bayesian additive regression trees) and SuperLearner stacked ensembling. We tuned ML hyperparameters through nested ensembling, and imputed missing values with generalized low-rank models (GLRM). We benchmarked performance to key biomarkers, validated clinical risk scores, decision trees, and logistic regression. We explained the models through variable importance ranking and accumulated local effect visualization. Results: The best discrimination (area under the precision-recall [PR-AUC] and receiver operating characteristic [ROC-AUC] curves) was provided by SuperLearner ensembling (0.148, 0.867), followed by random forest (0.146, 0.862). Logistic regression (0.120, 0.842) and decision trees (0.094, 0.805) exhibited worse discrimination, as did risk scores [HEART (0.064, 0.765), EDACS (0.046, 0.733)] and biomarkers [serum troponin level (0.064, 0.708), electrocardiography (0.047, 0.686)]. The ensemble's risk estimates were miscalibrated by 0.2 percentage points. The ensemble accurately identified 50% of patients to be below a 0.5% 60-day MACE risk threshold. The most important predictors were age, peak troponin, HEART score, EDACS score, and electrocardiogram. GLRM imputation achieved 90% reduction in root mean-squared error compared to median-mode imputation. Conclusion: Use of ML algorithms, combined with broad predictor sets, improved MACE risk prediction compared to simpler alternatives, while providing calibrated predictions and interpretability. Standard risk scores may neglect important health information available in other characteristics and combined in nuanced ways via ML.

scholarly journals An immune-related lncRNA signature as a prognostic immunotherapy target for colon cancer

2020 ◽  
Author(s):  
Bin Wu ◽  
Yi Yao ◽  
Yi Dong ◽  
Si Qi Yang ◽  
Deng Jing Zhou ◽  
...  
Keyword(s):  
Colon Cancer ◽  
High Risk ◽  
Risk Score ◽  
Enrichment Analysis ◽  
Risk Groups ◽  
Low Risk ◽  
Gene Set Enrichment Analysis ◽  
Risk Scores ◽  
Gene Set Enrichment ◽  
Immunotherapy Target

Abstract Background：We aimed to investigate an immune-related long non-coding RNA (lncRNA) signature that may be exploited as a potential immunotherapy target in colon cancer. Materials and methods: Colon cancer samples from The Cancer Genome Atlas (TCGA) containing available clinical information and complete genomic mRNA expression data were used in our study. We then constructed immune-related lncRNA co-expression networks to identify the most promising immune-related lncRNAs. According to the risk score developed from screened immune-related lncRNAs, the high-risk and low-risk groups were separated on the basis of the median risk score, which served as the cutoff value. An overall survival analysis was then performed to confirm that the risk score developed from screened immune-related lncRNAs could predict colon cancer prognosis. The prediction reliability was further evaluated in the independent prognostic analysis and receiver operating characteristic curve (ROC). A principal component analysis (PCA) and gene set enrichment analysis (GSEA) were performed for functional annotation. Results: Information for a total of 514 patients was included in our study. After multiplex analysis, 12 immune-related lncRNAs were confirmed as a signature to evaluate the risk scores for each patient with cancer. Patients in the low-risk group exhibited a longer overall survival (OS) than those in the high-risk group. Additionally, the risk scores were an independent factor, and the Area Under Curve (AUC) of ROC for accuracy prediction was 0.726. Moreover, the low-risk and high-risk groups displayed different immune statuses based on principal components and gene set enrichment analysis.Conclusions: Our study suggested that the signature consisting of 12 immune-related lncRNAs can provide an accessible approach to measuring the prognosis of colon cancer and may serve as a valuable antitumor immunotherapy.

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