Protective effect of metformin in lung cancer patients

2009 ◽  
Vol 27 (15_suppl) ◽  
pp. e22063-e22063
Author(s):  
B. Gagnon ◽  
M. Roseman ◽  
G. Kasymjanova ◽  
N. MacDonald ◽  
H. Kreisman ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Cancer Patients ◽  
Cox Regression ◽  
Human Cell Lines ◽  
Community Based ◽  
Cox Regression Analysis ◽  
Lung Cancer Patients ◽  
The Past ◽  
Jewish General Hospital

e22063 Background: Over the past decade, dozens of studies have shown that metformin not only decreases mortality in diabetics, it also significantly reduces CRP and reduces the risks of cancer in rodent and human cell lines. We report on the survival of lung cancer patients concomitantly exposed to metformin in our community-based program. Methods: 850 patients undergoing treatment from a prospectively collected pulmonary oncology database of the SMBD-Jewish General Hospital over an 8-year period were analyzed. Pilot observational study of survival was performed using Cox regression model. The factors that were included in the model were age, gender, stage, histology and metformin use. Results: 850 patients (F: M=375:475; mean age of 66) were diagnosed since 2000 and followed in pulmonary oncology outpatient clinic for NSCLC. 523 (62%) of those patients were diagnosed with adenocarcinoma; 488 (57%) were stage IIIB with pleural effusion/IV. 79(9%) patients were receiving treatment with metformin for their comorbid type 2 diabetes. The Cox regression analysis demonstrated that age, gender, stage and use of metformin were significant prognostic factors for survival. The use of metformin is associated with a 37% (HR 1.37; CI 1.01–1.84) (p=0.039) increase in survival. Conclusions: Thus, the result obtained from our model suggests that use of metformin may be associated with better survival of lung cancer patients. As this is a pilot study, we will consider alternative explanations. No significant financial relationships to disclose.

A nomogram to predict outcomes of lung cancer patients after pneumonectomy based on 47 indicators.

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. e20014-e20014
Author(s):  
Bo Cheng ◽  
Cong Wang ◽  
Xue Meng
Keyword(s):  
Lung Cancer ◽  
Cancer Patients ◽  
Cox Regression ◽  
Clinical Care ◽  
External Validation ◽  
Categorical Variables ◽  
Rank Test ◽  
Survival Prediction ◽  
Cox Regression Analysis ◽  
Lung Cancer Patients

e20014 Background: Nomograms are commonly used tools to estimate prognosis in oncology and medicine.We aimed to establish a nomogram with patients’ characteristics and all available hematological biomarkers for lung cancer patients. Methods: All indexes were cataloged according to clinical significance. Principle component analysis (PCA) was used to reduce the dimensions. Each component was transformed into categorical variables based on recognized cut-off values from receiver operating characteristic (ROC) curve. Kaplan-Meier analysis with log-rank test was used to evaluate the prognostic value of each component. Multivariate analysis was used to determine the promising prognostic biomarkers. Five components were entered into a predictive nomogram. The model was subjected to bootstrap internal validation and to external validation with a separate cohort from Shandong Cancer Hospital. The predictive accuracy and discriminative ability were measured by concordance index (C index) and risk group stratification. Results: Two hundred thirty-six patients were retrospectively analyzed in this study, with 134 in the Discovery Group and 102 in the Validation Group. Forty-seven indexes were sorted into 8 subgroups, and 20 principle components were extracted for further survival analysis. Via cox regression analysis, five components were significant and entered into predictive nomograms. The calibration curves for probability of 3-, and 5-year overall survival (OS) showed optimal agreement between nomogram prediction and actual observation. The new scoring system according to nomogram allowed significant distinction between survival curves within respective tumor-node-metastasis (TNM) subgroups. Conclusions: A nomogram based on the clinical indexes was established for survival prediction of lung cancer patients, which can be used for treatment therapy selection and clinical care option. PCA makes big data analysis feasible.

scholarly journals Synchronous bone metastasis in lung cancer: retrospective study of a single center of 15,716 patients from Tianjin, China

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Xu Guo ◽  
Wenjuan Ma ◽  
Haixiao Wu ◽  
Yao Xu ◽  
Dezheng Wang ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Bone Metastasis ◽  
Cancer Patients ◽  
Clinical Characteristics ◽  
Cox Regression ◽  
Histological Type ◽  
Cytokeratin 19 ◽  
Cox Regression Analysis ◽  
Lung Cancer Patients ◽  
History Of

Abstract Background This study aimed to describe the incidence, clinical characteristics, and prognosis of lung cancer patients with synchronous bone metastasis (SBM) and to analyze the prognostic factors of the lung cancer patients with SBM. Methods A total of 15,716 lung cancer patients who were diagnosed between 2009 to 2018 in the Tianjin Medical University Cancer Institute and Hospital were retrospectively reviewed. Among them, patients with SBM were checked. Both the demographic and clinical characteristics were included as follows: age, gender, marital status, history of smoking, alcohol consumption, family history of tumor, Karnofsky score, lymph node metastasis, histological type. Besides, laboratory data such as alkaline phosphatase, lactate dehydrogenase, carcinoembryonic antigen, squamous cell carcinoma antigen, cytokeratin-19 fragment, and neuron specific enolase were also included. The log-rank test and multivariate Cox regression analysis were employed to reveal the potential prognostic predictors. A further analysis using the Kaplan–Meier was employed to demonstrate the difference on the prognosis of LC patients between adenocarcinoma and non-adenocarcinoma. Results Among the included patients, 2738 patients (17.42%) were diagnosed with SBM. A total of 938 patients (34.3%) with SBM were successfully followed and the median survival was 11.53 months (95%CI: 10.57–12.49 months), and the 1-, 2-, and 5-year overall survival rate was 51, 17, and 8%, respectively. Multivariable Cox regression results showed history of smoking and high level of NSE were associated with the poor prognosis, while adenocarcinoma histological type was associated with better survival. Conclusion The prevalence of SBM in lung cancer is relatively high with poor survival. The lung cancer patients with SBM showed diverse prognosis. Among all the pathological types, the division of adenocarcinoma suggested different prognosis of the lung cancer patients with SBM. The present study emphasized the importance of pathological diagnosis on prognostic determinants in lung cancer patients with SBM.

scholarly journals Metformin Prolongs Survival in Type 2 Diabetes Lung Cancer Patients With EGFR-TKIs

2019 ◽  
Vol 18 ◽  
pp. 153473541986949 ◽  
Author(s):  
Ming-Szu Hung ◽  
Min-Chun Chuang ◽  
Yi-Chuan Chen ◽  
Chuan-Pin Lee ◽  
Tsung-Ming Yang ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Cancer Patients ◽  
Kinase Inhibitor ◽  
Progression Free Survival ◽  
Research Database ◽  
Lung Cancer Patients ◽  
Risk Of Death ◽  
Type 2 Dm ◽  
Egfr Tki

Background: Metformin use reportedly reduces cancer risk and improves survival in lung cancer patients. This study aimed to investigate the effect of metformin use in patients with diabetes mellitus (DM) and lung cancer receiving epidermal growth factor receptor-tyrosine kinase inhibitor (EGFR-TKI) therapy. Methods: A nationwide, population-based cohort study was conducted using the Taiwan National Health Insurance Research Database. From January 1, 2004, to December 31, 2012, a total of 373 metformin and 1260 non-metformin lung cancer cohorts with type 2 DM and EGFR-TKI treatment were studied. Results: Metformin use was significantly associated with a reduced risk of death (hazard ratio: 0.73, 95% confidence interval [CI]: 0.62-0.85, P < .001), as well as a significantly longer median progression-free survival (9.2 months, 95% CI: 8.6-11.7, vs 6.4 months, 95% CI: 5.9-7.2 months, P < .001) and median overall survival (33.4 months, 95% CI: 29.4-40.2, vs 25.4 months, 95% CI: 23.7-27.2 months, P < 0.001). Conclusions: In conclusion, metformin may potentially enhance the therapeutic effect and increase survival in type 2 DM patients with lung cancer receiving EGFR-TKI therapy.

scholarly journals Advancing Personalized Cancer Medicine in Lung Cancer

2012 ◽  
Vol 136 (10) ◽  
pp. 1210-1216 ◽  
Author(s):  
Laura E. MacConaill
Keyword(s):  
Lung Cancer ◽  
Cancer Therapy ◽  
Cancer Patients ◽  
Lung Cancer Patients ◽  
The Past ◽  
Genomic Technologies ◽  
Personalized Cancer Medicine ◽  
Cancer Medicine ◽  
Personalized Cancer Therapy ◽  
Personalized Cancer

Although improvements in genomic technologies during the past decade have greatly advanced our understanding of the genomic alterations that contribute to lung cancer, and the disease has (to a degree) become a paradigm for individualized cancer treatment in solid tumors, additional challenges must be addressed before the goal of personalized cancer therapy can become a reality for lung cancer patients.

scholarly journals CD4/CD8 Ratio of Pleural Effusion Is A Prognostic Predictor for Non-Small Cell Lung Cancer Patients Under Immune Checkpoint Inhibitor Treatments

2021 ◽  
Author(s):  
Po-Hsin Lee ◽  
Tsung-Ying Yang ◽  
Kun-Chieh Chen ◽  
Yen-Hsiang Huang ◽  
Jeng-Sen Tseng ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Pleural Effusion ◽  
Cancer Patients ◽  
Immune Checkpoint ◽  
Checkpoint Inhibitors ◽  
Lung Cancer Patients ◽  
Predicting Factor ◽  
Type 3

Abstract Pleural effusion is a rare immune-related adverse event for lung cancer patients receiving immune checkpoint inhibitors (ICIs). We enrolled 281 lung cancer patients treated with ICIs and 17 were analyzed. We categorized the formation of pleural effusion into 3 patterns: type 1, rapid and massive; type 2, slow and indolent and type 3, with disease progression. CD4/CD8 ratio of 1.93 was selected as the cutoff threshold to predict survival. Most patients of types 1 and 2 effusions possessed pleural effusion with CD4/CD8 ratios > = 1.93. The median OS time in type 1, 2, and 3 patients were not reached, 24.8, and 2.6 months. The median PFS time in type 1, 2, and 3 patients were 35.5, 30.2, and 1.4 months. The median OS for the group with pleural effusion CD4/CD8 > = 1.93 and < 1.93 were not reached and 2.6 months. The median PFS of those with pleural effusion CD4/CD8 > = 1.93 and < 1.93 were 18.4 and 1.2 months. In conclusion, patients with type 1 and 2 effusion patterns had better survival than those with type 3. Type 1 might be interpreted as pseudoprogression of malignant pleural effusion. CD4/CD8 ratio > = 1.93 in pleural effusion is a good predicting factor for PFS.

A retrospective review of nutritional status and immunotherapy in lung cancer.

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. e14112-e14112
Author(s):  
Chung-Shien Lee ◽  
Rebecca Sin ◽  
Joanna Stein Fishbein ◽  
Craig E. Devoe ◽  
Xinhua Zhu ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Nutritional Status ◽  
Cancer Patients ◽  
Retrospective Review ◽  
Cox Regression ◽  
Checkpoint Inhibitors ◽  
Normal Weight ◽  
Rank Test ◽  
Cancer Center ◽  
Lung Cancer Patients

e14112 Background: Immunotherapy has transformed cancer treatment, including lung cancer. Approximately 20-25% of patients respond, therefore making it pivotal in understanding what factors may effect outcomes. There have been previous reports of obesity associated with an increased efficacy of PD-1/PD-L1 blockade and cachectic patients not responding as well. In this study, we aim to assess the association of body mass index (BMI) with outcomes of lung cancer patients being treated with immunotherapy. Methods: An IRB approved retrospective review of lung cancer patients receiving immunotherapy between 2014 and 2017 at the Monter Cancer Center, Northwell Health was conducted. Patients were categorized in underweight (BMI < 18.5), normal weight (BMI of 18.5 to < 25), overweight (BMI 25 to 30) or obese (BMI > 30) arms. The groups were compared using the log-rank test. Kaplan-Meier was used for overall survival (OS) and progression free survival (PFS) and Cox regression models were used to adjust for potential confounders. Results: A total of 116 were included in the analysis, with a median age of 70 (95% CI, 62.5 to 75.5). Ten (8.6%) were underweight, 44 (37.9%) were normal weight, 32 (27.6%) were overweight, and 30 (25.9%) were obese. BMI classification were not found to be a significant predictor of survival, after adjusting for therapy duration (p = 0.44). PFS was 6.6, 6.0, and 6.9 months for patients in the underweight, normal weight, and overweight/obese groups, respectively. Of 116 subjects, 46 (40%) died within the follow up period: 3 (30%), 17 (39%), 11 (34%), and 15 (50%) respectively. Additional post hoc analysis showed that patients with low nutritional status as defined by either a BMI < 18.5 and/or baseline albumin < 3.5 mg/dL had a median PFS of 2.2 months compared to those who did not of 5.2 months (p < 0.00032). Conclusions: In this single institution retrospective review, BMI or albumin as solitary factors did not have a significant effect on outcomes receiving immunotherapy in lung cancer patients. However, a more comprehensive nutritional assessment using a composite endpoint of BMI and serum albumin predicted response to checkpoint inhibitors. Additional studies are needed to validate these findings.

Sign in / Sign up

Export Citation Format

Share Document