scholarly journals Metformin Treatment and Cancer Risk: Cox Regression Analysis, With Time-Dependent Covariates, of 320,000 Persons With Incident Diabetes Mellitus

2019 ◽  
Vol 188 (10) ◽  
pp. 1794-1800 ◽  
Author(s):  
Rachel Dankner ◽  
Nirit Agay ◽  
Liraz Olmer ◽  
Havi Murad ◽  
Lital Keinan Boker ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Lung Cancer ◽  
Cancer Risk ◽  
Time Dependent ◽  
Incident Diabetes ◽  
Diabetic Patients ◽  
Defined Daily Dose ◽  
Metformin Treatment ◽  
Health Maintenance ◽  
Cox Regression Analysis

Abstract There is conflicting evidence regarding the association between metformin use and cancer risk in diabetic patients. During 2002–2012, we followed a cohort of 315,890 persons aged 21–87 years with incident diabetes who were insured by the largest health maintenance organization in Israel. We used a discrete form of weighted cumulative metformin exposure to evaluate the association of metformin with cancer incidence. This was implemented in a time-dependent covariate Cox model, adjusting for treatment with other glucose-lowering medications, as well as age, sex, ethnic background, socioeconomic status, smoking (for bladder and lung cancer), and parity (for breast cancer). We excluded from the analysis metformin exposure during the year before cancer diagnosis in order to minimize reverse causation of cancer on changes in medication use. Estimated hazard ratios associated with exposure to 1 defined daily dose of metformin over the previous 2–7 years were 0.98 (95% confidence interval (CI): 0.82, 1.18) for all-sites cancer (excluding prostate and pancreas), 1.05 (95% CI: 0.67, 1.63) for colon cancer, 0.98 (95% CI: 0.49, 1.97) for bladder cancer, 1.02 (95% CI: 0.59, 1.78) for lung cancer, and 0.88 (95% CI: 0.56, 1.39) for female breast cancer. Our results do not support an association between metformin treatment and the incidence of major cancers (excluding prostate and pancreas).

Risk of Second Malignancy After Hodgkin’s Disease in a Collaborative British Cohort: The Relation to Age at Treatment

2000 ◽  
Vol 18 (3) ◽  
pp. 498-498 ◽  
Author(s):  
A.J. Swerdlow ◽  
J.A. Barber ◽  
G. Vaughan Hudson ◽  
D. Cunningham ◽  
R.K. Gupta ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Lung Cancer ◽  
Cancer Risk ◽  
Gastrointestinal Cancer ◽  
Hodgkin's Disease ◽  
Hodgkin’S Disease ◽  
Chemotherapeutic Agents ◽  
Second Malignancy ◽  
Increased Risk ◽  
Mixed Modality

PURPOSE: To assess long-term site-specific risks of second malignancy after Hodgkin’s disease in relation to age at treatment and other factors. PATIENTS AND METHODS: A cohort of 5,519 British patients with Hodgkin’s disease treated during 1963 through 1993 was assembled and followed-up for second malignancy and mortality. Follow-up was 97% complete. RESULTS: Three hundred twenty-two second malignancies occurred. Relative risks of gastrointestinal, lung, breast, and bone and soft tissue cancers, and of leukemia, increased significantly with younger age at first treatment. Absolute excess risks and cumulative risks of solid cancers and leukemia, however, were greater at older ages than at younger ages. Gastrointestinal cancer risk was greatest after mixed-modality treatment (relative risk [RR] = 3.3; 95% confidence interval [CI], 2.1 to 4.8); lung cancer risks were significantly increased after chemotherapy (RR = 3.3; 95% CI, 2.4 to 4.7), mixed-modality treatment (RR = 4.3; 95% CI, 2.9 to 6.2), and radiotherapy (RR = 2.9; 95% CI, 1.9 to 4.1); breast cancer risk was increased only after radiotherapy without chemotherapy (RR = 2.5; 95% CI, 1.4 to 4.0); and leukemia risk was significantly increased after chemotherapy (RR = 31.6; 95% CI, 19.7 to 47.6) and mixed-modality treatment (RR = 38.1; 95% CI, 24.6 to 55.9). These risks were generally greater after treatment at younger ages: for patients treated at ages younger than 25 years, there were RRs of 18.7 (95% CI, 5.8 to 43.5) for gastrointestinal cancer after mixed-modality treatment, 14.4 (95% CI, 5.7 to 29.3) for breast cancer after radiotherapy, and 85.2 (95% CI, 45.3 to 145.7) for leukemia after chemotherapy (with or without radiotherapy). CONCLUSION: Age at treatment has a major effect on risk of second malignancy after Hodgkin’s disease. Although absolute excess risks are greater for older patients, RRs of several important malignancies are much greater for patients who are treated when young. The increased risk of gastrointestinal cancers may relate particularly to mixed-modality treatment, and that of lung cancer to chemotherapy as well as radiotherapy; there are also well-known increased risks of breast cancer from radiotherapy and leukemia from chemotherapy. The roles of specific chemotherapeutic agents in the etiology of solid cancers after Hodgkin’s disease require detailed investigation.

Metformin decreases lung cancer risk in diabetic patients in a dose-dependent manner

Lung Cancer ◽  
2014 ◽  
Vol 86 (2) ◽  
pp. 137-143 ◽  
Author(s):  
Ming-Ju Tsai ◽  
Chih-Jen Yang ◽  
Ya-Ting Kung ◽  
Chau-Chyun Sheu ◽  
Yu-Ting Shen ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Cancer Risk ◽  
Lung Cancer Risk ◽  
Diabetic Patients ◽  
Dependent Manner ◽  
Dose Dependent

scholarly journals Immune-related lncRNAs as predictors of survival in breast cancer: a prognostic signature

2020 ◽  
Vol 18 (1) ◽  
Author(s):  
Wei Ma ◽  
Fangkun Zhao ◽  
Xinmiao Yu ◽  
Shu Guan ◽  
Huandan Suo ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Regression Analysis ◽  
Cox Regression ◽  
Risk Group ◽  
Curve Analysis ◽  
Time Dependent ◽  
Training Set ◽  
Roc Curve Analysis ◽  
Cox Regression Analysis ◽  
Validation Set

Abstract Background Breast cancer is a highly heterogeneous disease, this poses challenges for classification and management. Long non-coding RNAs play acrucial role in the breast cancersdevelopment and progression, especially in tumor-related immune processes which have become the most rapidly investigated area. Therefore, we aimed at developing an immune-related lncRNA signature to improve the prognosis prediction of breast cancer. Methods We obtained breast cancer patient samples and corresponding clinical data from The Cancer Genome Atlas (TCGA) database. Immune-related lncRNAs were screened by co-expression analysis of immune-related genes which were downloaded from the Immunology Database and Analysis Portal (ImmPort). Clinical patient samples were randomly separated into training and testing sets. In the training set, univariate Cox regression analysis and LASSO regression were utilized to build a prognostic immune-related lncRNA signature. The signature was validated in the training set, testing set, and whole cohorts by the Kaplan–Meier log-rank test, time-dependent ROC curve analysis, principal component analysis, univariate andmultivariate Cox regression analyses. Results A total of 937 immune- related lncRNAs were identified, 15 candidate immune-related lncRNAs were significantly associated with overall survival (OS). Eight of these lncRNAs (OTUD6B-AS1, AL122010.1, AC136475.2, AL161646.1, AC245297.3, LINC00578, LINC01871, AP000442.2) were selected for establishment of the risk prediction model. The OS of patients in the low-risk group was higher than that of patients in the high-risk group (p = 1.215e − 06 in the training set; p = 0.0069 in the validation set; p = 1.233e − 07 in whole cohort). The time-dependent ROC curve analysis revealed that the AUCs for OS in the first, eighth, and tenth year were 0.812, 0.81, and 0.857, respectively, in the training set, 0.615, 0.68, 0.655 in the validation set, and 0.725, 0.742, 0.741 in the total cohort. Multivariate Cox regression analysis indicated the model was a reliable and independent indicator for the prognosis of breast cancer in the training set (HR = 1.432; 95% CI 1.204–1.702, p < 0.001), validation set (HR = 1.162; 95% CI 1.004–1.345, p = 0.044), and whole set (HR = 1.240; 95% CI 1.128–1.362, p < 0.001). GSEA analysis revealed a strong connection between the signature and immune-related biological processes and pathways. Conclusions We constructed and verified a robust signature of 8 immune-related lncRNAs for the prediction of breast cancer patient survival.

scholarly journals Immune-Related LncRNAs as Predictors of Survival in Breast Cancer: A Prognostic Signature

2020 ◽  
Author(s):  
wei ma ◽  
fangkun zhao ◽  
xinmiao yu ◽  
shu guan ◽  
huandan suo ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Regression Analysis ◽  
Cox Regression ◽  
Risk Group ◽  
Curve Analysis ◽  
Time Dependent ◽  
Training Set ◽  
Roc Curve Analysis ◽  
Cox Regression Analysis ◽  
Validation Set

Abstract Background: Breast cancer is a highly heterogeneous disease, this poses challenges for classification and management. Long non-coding RNAs play acrucial role in the breast cancers development and progression, especially in tumor-related immune processes which have become the most rapidly investigated area. Methods: We obtained breast cancer patient samples and corresponding clinical data from The Cancer Genome Atlas (TCGA) database. Immune-related lncRNAs were screened by co-expression analysis of immune-related genes which were downloaded from the Immunology Database and Analysis Portal (ImmPort). Clinical patient samples were randomly separatedinto training and testing sets. In the training set, univariate Cox regression analysis and LASSO regression were utilized to build a prognostic immune-related lncRNA signature. The signature was validated in the training set, testing set, and whole cohorts by the Kaplan–Meier log-rank test, time-dependent ROC curve analysis, principal component analysis, univariate and multivariate Cox regression analyses. Results: A total of 937 immune- related lncRNAs were identified, 15 candidate immune-related lncRNAs were significantly associated with overall survival (OS). Eight of these lncRNAs (OTUD6B-AS1, AL122010.1, AC136475.2, AL161646.1, AC245297.3, LINC00578, LINC01871, AP000442.2) were selected for establishment of the risk prediction model. The OS of patients in the low-risk group was higher than that of patients in the high-risk group( p= 1.215e−06 in the training set; p =0.0069 in the validation set; p =1.233e−07 in whole cohort). The time-dependent ROC curve analysis revealed that the AUCs for OS in the first, eighth, and tenth year were 0.812, 0.81, and 0.857, respectively, in the training set, 0.615, 0.68, 0.655 in the validation set, and 0.725, 0.742, 0.741 in the total cohort. Multivariate Cox regression analysis indicated the model was a reliable and independent indicator for the prognosis of breast cancer in the training set (HR= 1.432; 95% CI 1.204−1.702, p <0.001), validation set (HR= 1.162; 95% CI 1.004−1.345, p = 0.044), and whole set (HR=1.240; 95% CI 1.128−1.362, p <0.001). GSEA analysis revealed a strong connection between the signature and immune-related biological processes and pathways. Conclusions: We constructed and verified a robust signature of 8 immune-related lncRNAs for the prediction of breast cancer patient survival.

Lung Cancer Risk Reduction After Smoking Cessation: Observations From a Prospective Cohort of Women

2003 ◽  
Vol 21 (5) ◽  
pp. 921-926 ◽  
Author(s):  
J.O. Ebbert ◽  
P. Yang ◽  
C.M. Vachon ◽  
R.A. Vierkant ◽  
J.R. Cerhan ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Smoking Cessation ◽  
Cancer Risk ◽  
Risk Reduction ◽  
Prospective Cohort ◽  
Lung Cancer Risk ◽  
Smoking History ◽  
Cox Regression Analysis ◽  
Former Smokers ◽  
Never Smokers

Purpose: We conducted this study because the duration of excess lung cancer risk among former smokers has been inconsistently reported, doubt has been raised regarding the population impact of smoking cessation, and differential risk reduction by histologic cell type after smoking cessation needs to be confirmed. Methods: The Iowa Women’s Health Study is a prospective cohort study of 41,836 Iowa women aged 55 to 69 years. In 1986, mailed questionnaires were used to collect detailed smoking history. Age-adjusted lung cancer incidence through 1999 was analyzed according to years of smoking abstinence. Relative risks were estimated using Cox regression analysis. Results: There were 37,078 women in the analytic cohort. Compared with the never smokers, former smokers had an elevated lung cancer risk (relative risk, 6.6; 95% confidence interval, 5.0 to 8.7) up to 30 years after smoking cessation for all former smokers. However, a beneficial effect of smoking cessation was observed among recent and distant former smokers. The risk of adenocarcinoma remained elevated up to 30 years for both former heavier and former lighter smokers. Conclusion: The risk for lung cancer is increased for both current and former smokers compared with never smokers and declines for former smokers with increasing duration of abstinence. The decline in excess lung cancer risk among former smokers is prolonged compared with other studies, especially for adenocarcinoma and for heavy smokers, suggesting that more emphasis should be placed on smoking prevention and lung cancer chemoprevention.

scholarly journals Metformin Use and Lung Cancer Risk in Diabetic Patients: A Systematic Review and Meta-Analysis

2019 ◽  
Vol 2019 ◽  
pp. 1-9 ◽  
Author(s):  
Long Yao ◽  
Mengke Liu ◽  
Yunlong Huang ◽  
Kaiming Wu ◽  
Xin Huang ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Cancer Risk ◽  
Cohort Studies ◽  
Cancer Incidence ◽  
Lung Cancer Risk ◽  
Meta Analysis ◽  
Diabetic Patients ◽  
Lung Cancer Incidence ◽  
Lower Lung ◽  
The Relationship

Background. Antidiabetic medications (ADMs) can alter the risk of different types of cancer, but the relationship between lung cancer incidence and metformin remains controversial. Our aim was to quantitatively estimate the relationship between incidences of lung cancer and metformin in patients with diabetes in this meta-analysis. Methods. We performed a search in PubMed, Embase, ISI Web of Science, and Cochrane Library until September 20, 2017. The odds ratio (OR), relative risk (RR) or hazard ratio (HR), and 95% confidence interval (95% CI) were estimated using the random-effect model. The Newcastle-Ottawa Scale (NOS) was used to assess the study quality. Results. A total of 13 studies (10 cohort studies and 3 case-control studies) were included in the meta-analysis. Compared to nonmetformin users, metformin probably decreased lung cancer incidence in diabetic patients (RR=0.89; 95% CI, 0.83-0.96; P=0.002) with significant heterogeneity (Q=35.47, I2=66%, P=0.0004). Subgroup analysis showed that cohort studies (RR=0.91; 95% CI, 0.85-0.98; P=0.008), location in Europe (RR=0.90; 95% CI, 0.86-0.94; P<0.0001), the control drug of the sulfonylurea group (RR=0.91; 95% CI, 0.86-0.96; P=0.001), and adjusting for smoking (RR=0.86; 95% CI, 0.75-1.00; P=0.05) may be related to lower lung cancer risk. No significant publication bias was detected using a funnel plot. Conclusion. Metformin use was related to a lower lung cancer risk in diabetic patients compared to nonusers, but this result was retrieved from observational studies and our findings need more well-designed RCTs to confirm the association.

scholarly journals The Effect of Metformin on Mortality Among Diabetic Cancer Patients: A Systematic Review and Meta-analysis

2017 ◽  
Vol 1 (1) ◽  
Author(s):  
Xun Cao ◽  
Yaopan Wu ◽  
Jing Wang ◽  
Kuiyuan Liu ◽  
Xin Wang
Keyword(s):  
Breast Cancer ◽  
Systematic Review ◽  
Cancer Patients ◽  
Fixed Effects ◽  
Meta Analysis ◽  
Cancer Site ◽  
Diabetic Patients ◽  
Metformin Treatment ◽  
Breast Cancer Patients ◽  
The Past

Abstract Background Most data suggest that cancer patients with diabetes have worse outcomes, which may be reversed with metformin. Metformin might modulate the clinical outcomes of diabetic cancer patients. We performed a systematic review and meta-analysis based on published studies over the past five years to summarize the effects of metformin on diabetic cancer patients. Methods We systematically searched for studies that were published over the past five years. Then, we evaluated these studies for inclusion and extracted the relevant data. The summary risk estimates for the association between metformin treatment and all-cause mortality (ACM) and cancer-specific mortality (CSM) were analyzed using random or fixed-effects models. Stratified analyses by cancer site and country were also conducted. Results Based on the 42 studies included in our analysis (37 015 diabetic cancer patients), we found a significant benefit associated with metformin treatment on survival corresponding to 27% and 26% reductions in ACM (hazard ratio [HR] = 0.73, 95% confidence interval [CI] = 0.68 to 0.79, P < .001) and CSM (HR = 0.74, 95% CI = 0.64 to 0.86, P < .001), respectively. The ACM rates for colorectal cancer, endometrial cancer, breast cancer, prostate cancer, and ovarian cancer showed significant benefits associated with metformin treatment in our stratified analyses by cancer site. Stratified analyses by cancer site also showed a significant reduction in CSM for breast cancer. This association between metformin treatment and reduced CSM for diabetic breast cancer patients was also observed in our country subgroup analyses. Conclusions We found an association between metformin exposure and reduced ACM and CSM in diabetic patients with cancer. Our findings suggest that metformin treatment could be an effective treatment option for diabetic cancer patients.

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