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

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.

Modeling of AIDS incidence and the response of transmission rates to increase prevention effort: a case study of the Thai province of Nakhon Pathom.

AIDS is a serious public health problem. Our projections of the likely incidence of AIDS are of vital importance to the assessment of future healthcare needs. This paper considers an epidemic model of the population dynamics of AIDS, which has been adjusted to take into account the changes in the transmission rate in response to changes in risk behaviors and increased AIDS awareness due to public health policy, AIDS campaigns, and other means of disease prevention. The model, adjusted for reporting delays and for the variable incubation period of the disease, has been applied to AIDS incidence data gathered in Nakhon Pathom, Thailand. Using the least-squares criterion, we solved for the appropriate values of the parameters which gave the best fit of the model to the observation data. The model was found to be capable of generating short-term projections, and offers an explanation for the decline in the number of cases that is evident in more recent data.