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, inclinical judgment and in medical resources supplying. Statistical tools like linear regression are widely used toassess the predictors of quality of life. But when the response is not normal the results are misleading. The aimof this study is to determine the predictors of quality of life in breast cancer patients, using quantile regressionmodel and compare to linear regression.
Methods: A cross-sectional study conducted on 119 breast cancer patientsthat admitted and treated in chemotherapy ward of Namazi hospital in Shiraz. We used QLQ-C30 questionnaireto assessment quality of life in these patients. A quantile regression was employed to assess the assocciatedfactors and the results were compared to linear regression. All analysis carried out using SAS.
Results: Themean score for the global health status for breast cancer patients was 64.92±11.42. Linear regression showedthat only grade of tumor, occupational status, menopausal status, financial difficulties and dyspnea werestatistically significant. In spite of linear regression, financial difficulties was not significant in quantile regressionanalysis for and dyspnea was only significant for first quartile. Also emotion functioning and duration of diseasewere statistically predicted QOL's score in third quartile.
Conclusion: The results have demonstrated that usingquantile regression leads to better interpretation and richer inference about predictors of breast cancer patient'squality of life.