120 Disparity in cardiovascular risk stratification between a novel non-invasive arterial stiffness method and three conventional risk scores in a high risk population

Heart ◽  
2010 ◽  
Vol 96 (Suppl 1) ◽  
pp. A69.3-A70
Author(s):  
D Dutton ◽  
J Fullerton ◽  
A Gunarathne ◽  
W Dimitri ◽  
P Banerjee ◽  
...  
BMC Medicine ◽  
2022 ◽  
Vol 20 (1) ◽  
Author(s):  
Biyuan Luo ◽  
Fang Ma ◽  
Hao Liu ◽  
Jixiong Hu ◽  
Le Rao ◽  
...  

Abstract Background Aberrant DNA methylation may offer opportunities in revolutionizing cancer screening and diagnosis. We sought to identify a non-invasive DNA methylation-based screening approach using cell-free DNA (cfDNA) for early detection of hepatocellular carcinoma (HCC). Methods Differentially, DNA methylation blocks were determined by comparing methylation profiles of biopsy-proven HCC, liver cirrhosis, and normal tissue samples with high throughput DNA bisulfite sequencing. A multi-layer HCC screening model was subsequently constructed based on tissue-derived differentially methylated blocks (DMBs). This model was tested in a cohort consisting of 120 HCC, 92 liver cirrhotic, and 290 healthy plasma samples including 65 hepatitis B surface antigen-seropositive (HBsAg+) samples, independently validated in a cohort consisting of 67 HCC, 111 liver cirrhotic, and 242 healthy plasma samples including 56 HBsAg+ samples. Results Based on methylation profiling of tissue samples, 2321 DMBs were identified, which were subsequently used to construct a cfDNA-based HCC screening model, achieved a sensitivity of 86% and specificity of 98% in the training cohort and a sensitivity of 84% and specificity of 96% in the independent validation cohort. This model obtained a sensitivity of 76% in 37 early-stage HCC (Barcelona clinical liver cancer [BCLC] stage 0-A) patients. The screening model can effectively discriminate HCC patients from non-HCC controls, including liver cirrhotic patients, asymptomatic HBsAg+ and healthy individuals, achieving an AUC of 0.957(95% CI 0.939–0.975), whereas serum α-fetoprotein (AFP) only achieved an AUC of 0.803 (95% CI 0.758–0.847). Besides detecting patients with early-stage HCC from non-HCC controls, this model showed high capacity for distinguishing early-stage HCC from a high risk population (AUC=0.934; 95% CI 0.905–0.963), also significantly outperforming AFP. Furthermore, our model also showed superior performance in distinguishing HCC with normal AFP (< 20ng ml−1) from high risk population (AUC=0.93; 95% CI 0.892–0.969). Conclusions We have developed a sensitive blood-based non-invasive HCC screening model which can effectively distinguish early-stage HCC patients from high risk population and demonstrated its performance through an independent validation cohort. Trial registration The study was approved by the ethic committee of The Second Xiangya Hospital of Central South University (KYLL2018072) and Chongqing University Cancer Hospital (2019167). The study is registered at ClinicalTrials.gov(#NCT04383353).


2019 ◽  
Vol 156 (3) ◽  
pp. S73-S74
Author(s):  
Elizabeth A. Spencer ◽  
Kyle Gettler ◽  
Drew Helmus ◽  
Shannon Telesco ◽  
Amy Hart ◽  
...  

2014 ◽  
Vol 73 (Suppl 2) ◽  
pp. 411.2-411
Author(s):  
M. Robustillo-Villarino ◽  
J.J. Alegre-Sancho ◽  
F. Gil-Latorre ◽  
E. Rodilla-Sala ◽  
À. Martínez-Ferrer ◽  
...  

Diabetes ◽  
2019 ◽  
Vol 68 (Supplement 1) ◽  
pp. 903-P
Author(s):  
JENNIFER L. SHEARER ◽  
KIRANBIR JOSAN ◽  
ABHA KHANDELWAL ◽  
SHRIRAM NALLAMSHETTY ◽  
FAHIM ABBASI ◽  
...  

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