Results 71 to 80 of about 388,843 (271)

Impact of dyslipidemia on cardiovascular risk stratification of hypertensive patients and association of lipid profile with other cardiovascular risk factors: results from the ICEBERG study

Integrated Blood Pressure Control, 2008
Giray Kabakci1, Nevres Koylan2, Baris Ilerigelen3, Omer Kozan4, Kemalettin Buyukozturk2 on behalf of the ICEBERG Investigators1Hacettepe University, Hacettepe School of Medicine, Department of Cardiology, Ankara, Turkey; 2Istanbul University, Istanbul ...
Giray Kabakci, Nevres Koylan, Baris Ilerigelen, Omer Kozan, Kemalettin Buyukozturk on behalf of the ICEBERG Investigators   +4 more
doaj  

Preclinical markers of carotid atherosclerosis and cardiovascular risk assessed by the ESH/ESC scale (2003, 2007, 2009)

Кардиоваскулярная терапия и профилактика, 2011
Aim. To assess the degree of cardiovascular (CV) risk adjustment in patients with low and intermediate risk by the SCORE scale, who were further examined in accordance with the European Society of Hypertension/European Society of Cardiology Guidelines ...
S. Sh. Urazalina, A. N. Rogoza, T. V. Balakhonova, R. P. Myasnikov, T. E. Kolmakova, Yu. A. Karpov, V. V. Kukharchuk, S. A. Boytsov   +7 more
doaj   +1 more source

Exploration of heterogeneity and recurrence signatures in hepatocellular carcinoma

Molecular Oncology, EarlyView.
This study leveraged public datasets and integrative bioinformatic analysis to dissect malignant cell heterogeneity between relapsed and primary HCC, focusing on intercellular communication, differentiation status, metabolic activity, and transcriptomic profiles.
Wen‐Jing Wu, Jianchao Wang, Fuqing Chen, Xuefeng Wang, Bin Lan, Ruyi Fu, Hong Wen, Fangfang Chen, Wei Hong, Tian‐Yu Tang, Ying He, Gang Chen, Jianyin Zhou, Hai‐Long Piao, Di Chen, Shu‐Yong Lin   +15 more
wiley   +1 more source

Cardiac risk stratification: Role of the coronary calcium score

Vascular Health and Risk Management, 2010
Rakesh K Sharma1, Rajiv K Sharma1, Donald J Voelker1, Vibhuti N Singh2, Deepak Pahuja3, Teresa Nash1, Hanumanth K Reddy11Medical Center of South Arkansas, University of Arkansas for Medical Sciences, Little Rock, AR, USA; 2Bayfront Medical Center, St ...
Rakesh K Sharma, Rajiv K Sharma, Donald J Voelker, et al   +3 more
doaj  

Comparing self‐reported race and genetic ancestry for identifying potential differentially methylated sites in endometrial cancer: insights from African ancestry proportions using machine learning models

Molecular Oncology, EarlyView.
Integrating ancestry, differential methylation analysis, and machine learning, we identified robust epigenetic signature genes (ESGs) and Core‐ESGs in Black and White women with endometrial cancer. Core‐ESGs (namely APOBEC1 and PLEKHG5) methylation levels were significantly associated with survival, with tumors from high African ancestry (THA) showing ...
Huma Asif, J. Julie Kim
wiley   +1 more source

A large‐scale retrospective study in metastatic breast cancer patients using circulating tumour DNA and machine learning to predict treatment outcome and progression‐free survival

Molecular Oncology, EarlyView.
There is an unmet need in metastatic breast cancer patients to monitor therapy response in real time. In this study, we show how a noninvasive and affordable strategy based on sequencing of plasma samples with longitudinal tracking of tumour fraction paired with a statistical model provides valuable information on treatment response in advance of the ...
Emma J. Beddowes, Mario Ortega Duran, Solon Karapanagiotis, Alistair Martin, Meiling Gao, Riccardo Masina, Ramona Woitek, James Tanner, Fleur Tippin, Justine Kane, Jonathan Lay, Anja Brouwer, Stephen‐John Sammut, Suet‐Feung Chin, Davina Gale, Dana W. Y. Tsui, Sarah‐Jane Dawson, Nitzan Rosenfeld, Maurizio Callari, Oscar M. Rueda, Carlos Caldas   +20 more
wiley   +1 more source

MET and NF2 alterations confer primary and early resistance to first‐line alectinib treatment in ALK‐positive non‐small‐cell lung cancer

Molecular Oncology, EarlyView.
Alectinib resistance in ALK+ NSCLC depends on treatment sequence and EML4‐ALK variants. Variant 1 exhibited off‐target resistance after first‐line treatment, while variant 3 and later lines favored on‐target mutations. Early resistance involved off‐target alterations, like MET and NF2, while on‐target mutations emerged with prolonged therapy.
Jie Hu, Ning Ding, Xiaobo Xu, Yedan Chen, Yong Zhang, Jingwen Liu, Jiebai Zhou, Hairong Bao, Donghui Zhang, Yijun Song, Yang Shao, Yuanlin Song   +11 more
wiley   +1 more source

Clinical risk stratification of children with SIOPEL high-risk hepatoblastoma in Taiwan

Pediatrics and Neonatology, 2020
Backgorund: Hepatoblastoma is the most common primary liver malignancy in young children. Methods: To identify predictors of the clinical outcomes of hepatoblastoma, we retrospectively reviewed the medical records of 45 children with hepatoblastoma in ...
Wei-Yun Hsu, Hsiu-Hao Chang, Meng-Yao Lu, Yung-Li Yang, Shiann-Tarng Jou, Huey-Ling Chen, Yen-Hsuan Ni, Hong-Yuan Hsu, Mei-Hwei Chang, Jia-Feng Wu   +9 more
doaj  

Detecting homologous recombination deficiency for breast cancer through integrative analysis of genomic data

Molecular Oncology, EarlyView.
This study develops a semi‐supervised classifier integrating multi‐genomic data (1404 training/5893 validation samples) to improve homologous recombination deficiency (HRD) detection in breast cancer. Our method demonstrates prognostic value and predicts chemotherapy/PARP inhibitor sensitivity in HRD+ tumours.
Rong Zhu, Katherine Eason, Suet‐Feung Chin, Paul A. W. Edwards, Raquel Manzano Garcia, Richard Moulange, Jia Wern Pan, Soo Hwang Teo, Sach Mukherjee, Maurizio Callari, Carlos Caldas, Stephen‐John Sammut, Oscar M. Rueda   +12 more
wiley   +1 more source

ACDC: $α$-Carving Decision Chain for Risk Stratification [PDF]

arXiv, 2016
In many healthcare settings, intuitive decision rules for risk stratification can help effective hospital resource allocation. This paper introduces a novel variant of decision tree algorithms that produces a chain of decisions, not a general tree. Our algorithm, $\alpha$-Carving Decision Chain (ACDC), sequentially carves out "pure" subsets of the ...
arxiv