||1R15CA152896-01A1 Interpret this number
||Northern Illinois University
||Lung Cancer Recurrence and Survival: Statistical Methods and Models for Ethnic an
DESCRIPTION (provided by applicant): Lung cancer is the leading cause of cancer death and has the second leading cancer incidence rate among men and women in the United States. African-American men have substantially higher death rates from lung cancer than white men whereas women have substantially lower mortality rates than men. Among women, black and white women have similar mortality rates from lung cancer whereas women who are Asian/Pacific Islanders or Hispanic have mortality rates that are 50% and 64% lower, respectively. There is a growing literature on the association of non-small cell lung cancer (NSCLC) with genetic and epigenetic markers. This project aims to develop statistical methods to explore whether a carefully selected list of epigenetic factors may be able to partially explain the differential impact of non-small cell lung cancer on different ethnic and gender groups. The epigenetic data will include promoter methylation measurements at multiple CpG sites in a focused gene panel including TP53, DAPK, RASSF1A, PTEN, p16 and MGMT; these will be combined with detailed data on molecular as well as clinical characteristics as well as comprehensive follow-up data on cancer recurrence and survival. These data will be obtained from a retrospective study of 400 patients about 125 of which are expected to be African-American and about 50% are expected to be female. Part of the data has already been collected from tumor specimens at Rush University Medical Center; another part will be collected from JH Stroger Hospital of Cook County. The primary goal of this project is to develop advanced statistical methods to investigate the association between the epigenetic factors, gender, ethnicity, and recurrence and survival from non-small cell lung cancer based on data from this patient group. The first specific aim of the project proposes to develop a competing risks cure rate model for lung cancer recurrence and survival which will allow the possibility of a fraction of patients to be cured as well as account for the risks from other causes in the general setting of Re 2 competing risks. The development of this unified statistical model will consider the bounded cumulative hazard and the latent factor formulation of cure rate models. The second specific aim will develop covariate adjusted regression models in the same unified framework of competing risk cure rate model which will be used to assess the effect of the epigenetic factors, gender and ethnicity on recurrence and survival. The third specific aim will develop variable and model selection methods which will be essential for measuring the importance of the covariates and factors. The fourth specific aim considers the missing cause-of-death, missing covariate in the data and proposes to develop statistical methods both for missing at random as well as non-ignorable missing frameworks. Together, these methodological developments will provide a collection of advanced statistical techniques which will be instrumental in assessing the relation and association between the epigenetic factors and gender/ethnic disparities in lung cancer recurrence and survival.
PUBLIC HEALTH RELEVANCE: The statistical methods developed in this project will play a vital role in understanding the association between genetic/epigenetic variability and gender/ethnic diversities in non-small cell lung cancer recurrence and survival. This will further provide insight into the complex phenomena that underlie the observed disparities and may help develop targeted, personalized therapies for lung cancer that may have substantially higher success rate and/or less toxicity and reduced adverse effects.