Browsing by Subject "lung cancer"
Now showing 1 - 4 of 4
- Results Per Page
- Sort Options
Item Adverse Effects of Lung Cancer Immunotherapy Among Socioeconomically Marginalized Lung Cancer Patients(2022-08) Nwaogbe, Ogochukwu; Mathew, Stephen O.; Basha, Riyaz; Adorboe, AndrewLung cancer remains a major contributor of cancer-related deaths and account for more than half of lung cancer deaths. In the U.S., lung cancer accounts for almost 25% of all U.S. cancer deaths and certain population groups bear a disproportionate burden. Immunotherapy is a novel treatment for lung cancer that has shown improvements in stalling disease progression and overall survival. But these treatments are associated with a plethora of adverse events that can affect any organ in the body. Most of the evidence on the adverse effects associated with immunotherapy is documented from clinical trials which often exclude the socioeconomically marginalized population. Hence little evidence exists on the incidence and range of adverse events in this population group. This study contributes to the evidence on the frequency and types of immunotherapy side effects experienced by socioeconomically marginalized populations.Item Association between Lung Cancer/Multiple Myeloma Mortality and Exposure to Oncogenic Viruses- Statistical Analysis Using Non-model and Model-based Statistical Methods and Various Control Sampling Schemes for Cancer Mortality in Occupational Cohorts(2009-12-01) Ndetan, Harrison; Bae, SejongNdetan, Harrison Tatandam, M.Sc., MPH. Association between Lung Cancer/Multiple Myeloma Mortality and Exposure to Oncogenic Viruses – Statistical Analysis Using Non-model- and Model-based Statistical Methods and Various Control Sampling Schemes for Cancer Mortality in Occupational Cohorts. Doctor of Public Health (Biostatistics), December 2009; 119 pp., 9 tables, 7 appendices, 38 titles. This study was designed to compare non-model- and model- based statistical techniques typically applied in cohort mortality analyses, and various schemes for selecting controls in nested case-control studies to document risk for lung cancer and multiple myeloma mortality, among workers in poultry slaughtering/processing plants. These workers are conceived to have a high exposure to oncogenic viruses compared to the general public. Data from the ongoing Cancer Risk in Workers Exposed to Oncogenic Viruses (CRIWETOV) project for members in a local Union Pension Fund belonging to the United Food & Commercial Workers (UFCW) international union, and followed–up for mortality from January 1, 1972 to December 31, 2003 were used for analyses. This cohort comprised of two large groups: poultry slaughtering/processing and non-poultry workers. The statistical methods applied were direct and indirect standardizations, Poisson, Cox proportional hazards, and binary/multiple logistic regression models and the sampling schemes for selecting controls were the cumulative survival, cumulative incidence, case-cohort, and incidence density sampling schemes. The entire cohort and sub groups of poultry and non-poultry separately had higher risks of mortality from both malignant diseases (statistically significant for lung cancer) compared to the United States’ general population, but slightly lower (statistically not significant) risks among poultry compared to non-poultry workers. Results of comparative effect measures from the various statistical methods under consideration were similar with a very slight difference in variability/precision within the cohort analyses. The effect measures were also similar for nested case-control analyses that applied the cumulative survival, cumulative incidence and case-base sampling schemes in selecting controls. However, the incidence density sampling scheme led to markedly different results (both in magnitude and statistical significance), that were more profound with the Cox regression model. Where the Cox model was not appropriate the interval Poisson (exponential) model was used and predictions were similar to those obtained using other methods.Item Properties of a Human Metastatic Variant Lung Cancer Model(2003-05-01) Poirot, Julie E.; Mart Hart; Robert Wordinger; Rick KitsonPoirot, J. Properties of a Human Metastatic Variant Lung Cancer Model. Master of Science (Molecular Biology and Immunology). May 2003. 44 pp., 11 illustrations, 1 table, 39 bibliography titles. A model of non-small cell lung cancer (NSCLC) has been developed for screening and preclinical drug evaluation by implanting the A549 lung cancer cell line orthotopically into immunocompromised (SCID) mice. Aggressive metastatic sublines were then derived from metastases from the primary implant. The purpose of this project is to elucidate some of the cellular properties involved in the tumor aggressiveness of the metastatic variant cell lines. In vitro migration and invasion assays produced data showing no significant differences between the rates of migration or invasion of parental and metastatic sublines. In vivo tumor burden experiments, however, produced data showing significant differences in the numbers and sizes of metastatic tumors formed when the three cell lines were compared in SCID mice. RT-PCR analysis has indicated that there are differences in the mRNA levels of certain matrix metalloproteinases. The A549 parental cells have matrix metalloproteinase-2 (MMP-2) but not MMP-9, while both metastatic variants show MMP-9 mRNA but no MMP-2. Western blots and gelatin zymographies also confirm these findings. RT-PCR analysis and casein zymography experiments have also shown no differences in the message or activity of urokinase plasminogen activator *uPA0 among the cell lines. Multidrug resistance studies were done on the tumor cell lines in order to compare their resistance to various classes of antineoplastic drugs. These studies indicate that there is no significant difference in the resistance to doxorubicin or paclitaxel, but the parental cell line is substantially more resistant to cisplatin than either of the metastatic sublines.Item The Association Between Sleep Traits and the Risk of Lung Cancer: UK Biobank Cohort(2022-05) Peeri, Noah C.; Nguyen, Uyen-Sa D.T.; Tao, Meng-Hua; Demissie, SerkalemBackground: Lung cancer has the highest incidence of any cancer and is the leading cause of cancer-related death worldwide. As smoking rates have declined over the last few decades, the proportion of individuals diagnosed with lung cancer among those who have never smoked increases. Thus, it remains important to identify other factors involved in the etiology of the disease. Sleep traits have been hypothesized as potential modifiable risk factors for lung cancer. This dissertation aimed to 1) comprehensively examine the associations between sleep traits and lung cancer risk using traditional epidemiologic methods (e.g., Cox regression) and 2) to assess potential causal associations between sleep duration (per hour increase) and lung cancer risk, insomnia (per category increase) and lung cancer risk, and chronotype (per category increase) and lung cancer risk using Mendelian randomization (MR) analyses. Methods: Utilizing the United Kingdom Biobank Cohort I examined the association between sleep traits (sleep duration, chronotype, insomnia) and lung cancer risk. Cox Hazards regression was used to estimate Hazards Ratios (HRs) and 95% Confidence Intervals (CIs) of associations between these three sleep traits and lung cancer risk. Joint effects analyses were also conducted, and non-linearity of sleep duration and lung cancer risk associations was examined. MR analyses were conducted to estimate causal HRs for the associations between sleep duration, chronotype, insomnia, and lung cancer risk. Analyses were stratified by smoking status to examine associations unconfounded by smoking (i.e., among never smokers). Furthermore, analyses were stratified by biologic sex and smoking to examine potential effect measure modification of associations between sleep traits and lung cancer risk. Results: Results of this study suggested potential associations between sleep traits and lung cancer risk. In main effects analysis, long sleep, when compared to short sleep duration was positively associated with lung cancer risk. Usually experiencing insomnia symptoms, when compared to never/rarely experiencing insomnia symptoms, was positively associated with lung cancer risk. No associations between chronotype and sleep duration were evident in overall analysis. Evidence from both aims suggested positive associations between the presence of insomnia symptoms and lung cancer risk. However, among never smokers, no statistically significant associations were observed in either aim. Two-sample MR revealed minute positive associations between insomnia and lung cancer risk. Discussion: In this dissertation the association between insomnia and lung cancer risk may have been residually confounded by smoking status; among never smokers no evidence was found linking insomnia and lung cancer risk. In one-sample MR analysis, the strong positive association between insomnia and lung cancer risk may have resulted from violations of the independence assumption. In stratified one-sample MR, no association between insomnia and lung cancer was observed among the neversmoker strata. It remains unclear to what extent the observed association between insomnia and lung cancer risk in two-sample MR was impacted by smoking status. Future research should focus on examining associations between insomnia and lung cancer among a larger cohort of never smoking individuals. In conclusion, the associations observed between insomnia and lung cancer were likely impacted by smoking status, and future research is needed to tease apart the impact of smoking on lung cancer from that of insomnia on lung cancer.