Relation between demographic factors and type of gastrointestinal cancer using probit and logit regression.

BACKGROUND: Approximately 50,000 new cases of cancer occur each year in the Iranian population of 70.4 million. The organ system involved with more than 38% of all cancers is the gastrointestinal (GI) tract. The objective of this study was to investigate the relation between demographic factors and type of gastrointestinal cancer using probit and logit models. METHODS: This study was designed as a cross-sectional survey including all consecutive GI cancer patients admitted over a one year period in a randomly selected hospital group located in Tehran in 2006. RESULTS: The largest number of cases were colorectal cancers (40.0%), followed by gastric cancers (34.5%) and esophagus cancers (17.1%). There was a significant gender effect in the colorectal, gastric and esophagus cancer also there was a significant association between age and gastrointestinal cancers in both logit and probit regression. The factor of duration was not significant in gastric cancer. CONCLUSION: Men are more likely have colorectal cancer than women. Older people are more likely to have gastric cancer than younger people. For esophagus cancer all factors were significant. Results from probit and logit models were similar, indicating that probit analysis can be employed as a logit model to analyze relationships between demographic factors and cancer type.

Quality of life in breast cancer patients--a quantile regression analysis.

BACKGROUND: Quality of life study has an important role in health care especially in chronic diseases, in clinical judgment and in medical resources supplying. Statistical tools like linear regression are widely used to assess the predictors of quality of life. But when the response is not normal the results are misleading. The aim of this study is to determine the predictors of quality of life in breast cancer patients, using quantile regression model and compare to linear regression. METHODS: A cross-sectional study conducted on 119 breast cancer patients that admitted and treated in chemotherapy ward of Namazi hospital in Shiraz. We used QLQ-C30 questionnaire to assessment quality of life in these patients. A quantile regression was employed to assess the assocciated factors and the results were compared to linear regression. All analysis carried out using SAS. RESULTS: The mean score for the global health status for breast cancer patients was 64.92+/-11.42. Linear regression showed that only grade of tumor, occupational status, menopausal status, financial difficulties and dyspnea were statistically significant. In spite of linear regression, financial difficulties were not significant in quantile regression analysis and dyspnea was only significant for first quartile. Also emotion functioning and duration of disease statistically predicted the QOL score in the third quartile. CONCLUSION: The results have demonstrated that using quantile regression leads to better interpretation and richer inference about predictors of the breast cancer patient quality of life.