Sevilay Karahan*, Osman Saraçbaşı
Department of Biostatistics, School of Medicine, Hacettepe University, Ankara, Turkey
Introduction: In some chronic diseases, such as cancer, the treatment may affect the quality of the patient’s life. In such diseases, lifetime is expected to be longer with high quality. Therefore, quality-adjusted survival analysis has been developed to evaluate the survival and quality of life together. The purpose of the study is to investigate the consequences of the shares of different survival periods and survival periods according to different health state durations on threshold.
Materials and Methods: The Q-TWiST (Quality adjusted Time Without Symptoms of disease and Toxicity of treatment) method should be used to compare the treatment groups in quality-adjusted survival analysis. The Q-TWiST method is based on estimating the adjusted survival time by using the effect of quality of life on certain periods. The weights indicating the quality of life of periods vary between 0 and 1. The weight of poor quality of life (death) is 0 and the weight of excellent health state is 1. These weights are called utility coefficients. Comparisons of survival times between the different treatment or cure groups are performed according to these new adjusted times. Threshold utility analysis has been done for indicating the consequences of different treatment groups on different utility coefficient combinations.
Results: It has been discovered that TWiST time increase for treatment causes a prominence of that treatment on threshold utility analysis, and it also causes an increase in Q-TWiST gain.
Conclusion: In survival analysis, the quality of patients’ life should be considered in addition to the survival time and the efficiency of treatment should be evaluated according to the Q-TWiST.
Quality of life, survival analysis, utility coefficient, threshold utility analysis.