scholarly journals Survival and Treatment of Lung Cancer in Taiwan between 2010 and 2016

2021 ◽  
Vol 10 (20) ◽  
pp. 4675
Author(s):  
Yen-Jung Chang ◽  
Jing-Yang Huang ◽  
Ching-Hsiung Lin ◽  
Bing-Yen Wang
Keyword(s):  
Lung Cancer ◽  
Overall Survival ◽  
Multivariate Analysis ◽  
Prognostic Factors ◽  
Cancer Patients ◽  
Randomized Clinical Trials ◽  
Treatment Strategies ◽  
Stage Iv ◽  
Clinical Staging ◽  
Lung Cancer Patients

Background: Lung cancer is the leading cause of cancer-related death, and its incidence is still growing in Taiwan. This study investigated the prognostic factors of overall survival between 2010 and 2016 in Taiwan. Methods: Data from 2010 to 2016 was collected from the Taiwan Cancer Registry (TCR). The characteristics and overall survival of 71,334 lung cancer patients were analyzed according to the tumor, node, metastasis (TNM) 7th staging system. Univariate and multivariate analysis were performed to identify the prognostic factors. Results: The five-year overall survival (n = 71,334) was 25.0%, and the median survival was 25.3 months. The five-year overall survival of patients receiving any kind of treatment (n = 65,436; 91.7%) and surgical resection (n = 20,131; 28.2%) was 27.09% and 69.93%, respectively. The clinical staging distribution was as follows: stage IA (9208, 12.9%), stage IB (4087, 5.7%), stage IIA (1702, 2.4%), stage IIB (1454, 2.0%), stage IIIA (5309, 7.4%), stage IIIB (6316, 8.9%), stage IV (41458, 58.1%). Age, sex, Charlson comorbidity index, cell type, clinical T, clinical N, clinical M, grading and treatment strategy are independent prognostic factors in the multivariate analysis. Conclusion: The outcome for lung cancer patients was still poor. The identification of prognostic factors could facilitate in choosing treatment strategies and designing further randomized clinical trials.

The Relationship between Prognostic Factors and Overall Survival in Small Cell Lung Cancer Patients: a Single Centre Experience

2012 ◽  
Vol 13 (2) ◽  
pp. 60-64
Author(s):  
Bala Basak Oven Ustaalioglu ◽  
Ahmet Bilici ◽  
Mesut Seker ◽  
Taflan Salepci ◽  
Recep Ustaalioglu ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Overall Survival ◽  
Prognostic Factors ◽  
Cancer Patients ◽  
Small Cell ◽  
Small Cell Lung ◽  
Single Centre ◽  
Lung Cancer Patients ◽  
Single Centre Experience ◽  
The Relationship

Using Naïve Bayes Algorithm to Estimate the Response to Drug in Lung Cancer Patients

2019 ◽  
Vol 21 (10) ◽  
pp. 734-748 ◽  
Author(s):  
Baoling Guo ◽  
Qiuxiang Zheng
Keyword(s):  
Lung Cancer ◽  
Side Effects ◽  
Cancer Patients ◽  
Drug Response ◽  
Treatment Options ◽  
Clinical Manifestations ◽  
Treatment Strategies ◽  
Cancer Resistance ◽  
Lung Cancer Patients ◽  
Bayes Algorithm

Aim and Objective: Lung cancer is a highly heterogeneous cancer, due to the significant differences in molecular levels, resulting in different clinical manifestations of lung cancer patients there is a big difference. Including disease characterization, drug response, the risk of recurrence, survival, etc. Method: Clinical patients with lung cancer do not have yet particularly effective treatment options, while patients with lung cancer resistance not only delayed the treatment cycle but also caused strong side effects. Therefore, if we can sum up the abnormalities of functional level from the molecular level, we can scientifically and effectively evaluate the patients' sensitivity to treatment and make the personalized treatment strategies to avoid the side effects caused by over-treatment and improve the prognosis. Result & Conclusion: According to the different sensitivities of lung cancer patients to drug response, this study screened out genes that were significantly associated with drug resistance. The bayes model was used to assess patient resistance.

Sign in / Sign up

Export Citation Format

Share Document