Application of log-linear models to cancer patients: a case study of data from the National Cancer Institute.

ABSTRACT

Cancer is a noninfectious disease which is on the increase throughout the world and has become a serious problem for public health in many countries, including Thailand. In Thailand, cancer has risen significantly to become a leading cause of death and most patients are admitted to the National Cancer Institute. The objective of this study is to identify the associated factors between personal, cancer/clinical variables of cancer patients using log-linear models. Tests of independence are used (chi-square and Cramer's V-value tests) to find out the relationships between any two variables. In addition two- and three-dimensional log-linear models are used to obtain estimated parameters and expected frequencies for these models. Amongst the models fitted, the best are chosen based on the analysis of deviance. The results of this study show that most paired variables of personal, cancer/clinical variables are significantly related at p-value <0.05. For both male and female patients, the variable site of the cancer is highly related to marital status, diagnostic evidence and treatment, which provide the highest Cramer's V value. Moreover, the site of cancer also affects the method of diagnostic evidence and treatment. Since the site of cancer in each sex is different, prevention for various sites of cancer should be considered for each specific sex. In addition, for male and female patients, treatment is related to the site of cancer. Consequently, physicians may consider these factors before selecting the appropriate method of treatment.