scholarly journals Current Advances in Computational biology of Lung Cancer

2022 ◽  
Vol 05 (01) ◽  
Author(s):  
Purbasha Pati ◽  
Keyword(s):  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Small Cell ◽  
Small Cell Lung ◽  
Cad Systems ◽  
Cad System ◽  
Lung Cancer Diagnosis ◽  
Total Cancer ◽  
Dynamics Simulations

Lung cancer is the main basis of cancer death amongst men and women, making up almost 25% of the world’s total cancer deaths. Lung cancer described for nearly 1.6 million deaths in 2012 and 1.80 million deaths in 2020. Small cell lung cancer and non-small-cell lung cancer are the two key categories of Lung cancer. The signs of lung cancer include hemoptysis, weight loss, shortness of breath and chest pain. Lung cancer treated by chemotherapy, surgery and CT scan. In this review paper, one of the most crucial zones aiming lung cancer diagnosis has been discussed. Computer-aided diagnosis (CAD) systems adapted for lung cancer can increase the patients’ survival chances. A typical CAD system for lung cancer functions in the fields of lung segmentation, detecting lung nodules and the diagnosis of the nodules as benign or malignant. CAD systems for lung cancer are examined in a huge number of research case studies. CAD system steps and outlining of inhibitor genes at molecular level is being discussed. An insight into multi-omics and molecular dynamics simulations is also given in this paper.

scholarly journals Prognostic factors in patients with skeletal-related events at non-small-cell lung cancer diagnosis

2017 ◽  
Vol 7 (5) ◽  
pp. 897-902 ◽  
Author(s):  
Hiroyuki Tominaga ◽  
Takao Setoguchi ◽  
Hirofumi Shimada ◽  
Satoshi Nagano ◽  
Hiromi Sasaki ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Prognostic Factors ◽  
Small Cell Lung Cancer ◽  
Cancer Diagnosis ◽  
Cell Lung Cancer ◽  
Small Cell ◽  
Small Cell Lung ◽  
Lung Cancer Diagnosis ◽  
Skeletal Related Events

scholarly journals Relationship Between Deficits in Overall Quality of Life and Non–Small-Cell Lung Cancer Survival

2012 ◽  
Vol 30 (13) ◽  
pp. 1498-1504 ◽  
Author(s):  
Jeff A. Sloan ◽  
Xinghua Zhao ◽  
Paul J. Novotny ◽  
Jason Wampfler ◽  
Yolanda Garces ◽  
...  
Keyword(s):  
Quality Of Life ◽  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
Cancer Diagnosis ◽  
Cell Lung Cancer ◽  
Small Cell ◽  
Small Cell Lung ◽  
Single Item ◽  
Lung Cancer Diagnosis

Purpose Evidence has suggested a clinically meaningful relationship between self-reported quality of life (QOL) of a patient with cancer at the time of receiving a cancer diagnosis and overall survival (OS). This study evaluated the prognostic value of QOL assessments with regard to OS in a large cohort of patients with lung cancer. Patients and Methods A total of 2,442 patients with non–small-cell lung cancer were observed between 1997 and 2007 and completed a single-item measure of overall QOL within the first 6 months of receiving a lung cancer diagnosis; these were dichotomized using an a priori definition of a clinically deficient score (CDS; ≤ 50 v > 50). Kaplan-Meier estimates and Cox models were used to evaluate the prognostic importance of QOL on OS alone and in the presence of covariates. Logistic regression modeling was used to identify which clinical and patient characteristics were related to a clinically meaningful deficit in QOL. Results QOL deficits at time of lung cancer diagnosis were significantly associated with OS (hazard ratio [HR], 1.55; P < .001), as were performance status, older age, smoking history, male sex, treatment factors, and stage of disease. The median survival for patients with CDS QOL was 1.6 years versus 5.6 years for patients with non-CDS QOL. After controlling for all these covariates, the indication of a clinically deficient baseline QOL still contributed significantly to the prediction of patient survival (HR, 0.67; P < .001). Conclusion Overall QOL measured by a simple single item at the time of lung cancer diagnosis is a significant and independent prognostic factor for survival in patients with lung cancer.

scholarly journals miRNA Detection for non-small cell lung cancer diagnosis

2021 ◽  
Author(s):  
Carla Cruz ◽  
André Rico ◽  
Fani Sousa ◽  
Bernardo Teixeira ◽  
Daniela Alexandre
Keyword(s):  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
Cancer Diagnosis ◽  
Cell Lung Cancer ◽  
Small Cell ◽  
Small Cell Lung ◽  
Lung Cancer Diagnosis ◽  
Mirna Detection
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