Paul Dickman

Randomized trials are considered the ideal approach to compare the effectiveness of different cancer treatments, but such trials are not always feasible. Important knowledge about treatment effects can also be obtained by studying the survival of cancer patients without randomly assigning treatment. However, such studies require advanced statistical methods to be able to identify the factors that influence patient survival. With the nationwide Swedish cancer registry, we can study the survival of all patients with cancer, which gives a more accurate picture of the development of cancer healthcare in the population. The goal of the current research project is to further develop existing statistical methods, as well as to apply these, to study clinical and biological hypotheses related to the survival of cancer patients. The new methods will be used to study the cost-effectiveness of treatments for chronic myeloid leukemia. These methods will be developed and applied using user-friendly computer programs and will be made available to other researchers. The goal is to further develop and apply methods that can be used to study the life expectancy of cancer patients and the cost-effectiveness of cancer treatments. The availability of relevant statistics, such as life expectancy, which reflect the prognosis of cancer patients can be guiding in the communication of risk as well as helping to improve patients' understanding of their own disease, which enables an informed decision regarding the clinical treatment to be made.

Randomized studies are considered the ideal approach to comparing the effects of various cancer treatments, but such studies are not always feasible. Important knowledge of treatment effects can also be obtained by studying the survival of cancer patients without random treatment. However, such studies require advanced statistical methods to identify the factors that affect patient survival. With the nationwide Swedish cancer register, we can study the survival of all patients with cancer, which provides a more accurate picture of the development of cancer care in the population. The aim of the current research project is to further develop existing statistical methods, and to apply these, to study clinical and biological hypotheses related to the survival of cancer patients. Special focus will also be placed on developing methods for presentation of survival statistics that are relevant for both patients and doctors. These methods will be developed and applied using user-friendly computer programs and will be made available to other researchers. The availability of clinically relevant statistics that reflect cancer patients 'prognosis can be indicative of communication of risk and help to improve patients' understanding of their own disease, which enables an informed decision regarding the clinical treatment to be taken. Increased knowledge of mortality as a result of treatment-related complications will be considered in clinical treatment decisions, which in turn may lead to a reduction in the morbidity and mortality among new patients.

Randomized studies are considered the ideal approach to comparing the effects of various cancer treatments, but such studies are not always feasible. Important knowledge of treatment effects can also be obtained by studying the survival of cancer patients without random treatment. However, such studies require advanced statistical methods to identify the factors that affect patient survival. With the nationwide Swedish cancer register, we can study the survival of all patients with cancer, which provides a more accurate picture of the development of cancer care in the population. The aim of the current research project is to further develop existing statistical methods, and to apply these, to study clinical and biological hypotheses related to the survival of cancer patients. Special focus will also be placed on developing methods for presentation of survival statistics that are relevant for both patients and doctors. These methods will be developed and applied using user-friendly computer programs and will be made available to other researchers. The availability of clinically relevant statistics that reflect cancer patients 'prognosis can be indicative of communication of risk and help to improve patients' understanding of their own disease, which enables an informed decision regarding the clinical treatment to be taken. Increased knowledge of mortality as a result of treatment-related complications will be considered in clinical treatment decisions, which in turn may lead to a reduction in the morbidity and mortality among new patients.