Paul Dickman

Paul Dickman

Professor | Responsible for a study programme | Docent
Telephone: +46852486186
Visiting address: Nobels väg 12a, 17165 Solna
Postal address: C8 Medicinsk epidemiologi och biostatistik, C8 MEB Dickman, 171 77 Stockholm
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About me

  • I am Professor of Biostatistics at the Department of Medical Epidemiology and Biostatistics (MEB) at Karolinska Institutet in Stockholm, where I’ve been employed since March 1999. I am deputy head of department, head of the MEB Biostatistics group, and programme director for the Master's programme in biostatistics and data science.

Research

  • My primary research interests are developing and applying statistical methods for population-based studies of cancer patient survival, particularly the estimation and modeling of relative/net survival. I also have general interests in epidemiology, particularly cancer epidemiology.

Teaching

  • I am programme director for the Master's programme in biostatistics and data science as well as course director and course teacher for courses within the programme.

Articles

All other publications

Grants

  • Swedish Cancer Society
    1 January 2023
    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.
  • Swedish Cancer Society
    1 January 2020
    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.
  • Swedish Research Council
    1 December 2019 - 31 December 2023
  • Development and application of statistical methods in register-based cancer epidemiology
    Swedish Cancer Society
    1 January 2019
    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.

Employments

  • Professor, Biostatistics, Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, 2013-

Degrees and Education

  • Docent, Karolinska Institutet, 2002
  • PhD, Estimating Regional Variation in Cancer Patient Survival, Statistics, University of Newcastle Australia, 1997

Leadership and responsibility assignments

Supervision

Editorial work

Other expert reviewer/evaluation assignment

  • Evaluator of research applications in national competition, Member of evaluation committee Pk F, Swedish Cancer Society, 2023

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