Therese Andersson

Therese Andersson

Senior Lecturer | Docent
Visiting address: ,
Postal address: C8 Medicinsk epidemiologi och biostatistik, C8 MEB II Andersson, 171 77 Stockholm
Part of:

About me

  • I am a biostatistician, working with statistical methods for cancer epidemiology. My main research interest is cancer patient survival and I have published studies on cancer patient survival for a range of cancer sites. I have also worked on international benchmarking of cancer patient survival,  for example the International Cancer Benchmarking Partnership SURVMARK-2, run by the International Agency for Research on Cancer (IARC) and in a Nordic collaborative project. I develop statistical methods as well as apply the methods to register-based data to answer important epidemiological and clinical research questions. I’m currently working in several projects, a description of two projects I'm heavily involved with currently are described below.

Research

  • *Loss in life expectancy due to cancer*
    One useful summary measure for survival data is the life expectancy, which is
    calculated by obtaining the area under a survival curve. Life expectancy is a
    well-established, easily understood concept that quantifies the expected
    number of life years remaining. In comparison to many other measures, it
    takes the whole time scale into account instead of at particular points
    during follow-up (such as the 1- or 5-year survival). Another statistic,
    closely related to the life expectancy, is the loss in life expectancy (LLE),
    a measure of how much a patient's life expectancy is reduced due to a cancer
    diagnosis. The LLE is defined as the difference in life expectancy between
    the cancer patients and a comparable group in the general population. The
    LLE can be used to address a wide range of research questions on both
    individual and population levels, and to quantify survival differences
    between groups. Another use of LLE is to quantify the burden of cancer on
    society as the total number of life years lost in the population; in this
    way, it can be useful for measuring cancer control progress and to provide
    guidance for resource allocation. I have developed methods for estimating the
    LLE for cancer patients, and further extend and evaluate the methodology to
    enable use of the measure in different contexts.


    *Survival after hematological cancers, with a focus on MPN*
    Compared to many other hematological
    malignancies MPNs are rather indolent diseases. Despite efforts to optimize
    treatment and prophylactic measures, patients with MPNs have a shorter
    survival than the general population and experience complications, such as
    thromboembolism and bleedings, due to their MPN. There are few
    population-based studies on MPNs, and most studies are small with short
    follow-up time and do not include population controls. It is therefore of
    great importance to gain a further understanding of the disease trajectory
    and risk of complications for this group of patients. By taking advantage of
    the Swedish health registers and novel statistical methods, we will improve
    the understanding of the clinical course and prognosis among MPN patients.

Teaching

  • I have been involved in teaching and/or course organising, for example:
    * Development of a MSc programme in Biostatistics and Data Science given within the Stockholm Trio, i.e. Karolinska Institutet, KTH Royal Institute of Technology and Stockholm University.
    * Survival analysis (biostat III), within the Doctoral Programme in
    Epidemiology
    * Data Management within epidemiological research, including lectures on
    laws and regulations concerning the use of personal data in research
    * Competing risks and multistate models
    * IARC summer school on cancer epidemiology, module 1, cancer survival
    methods for cancer registries.
    * Summer school on modern methods in biostatistics and epidemiology.
    Survival analysis using Stata (a 1-day course) and Statistical Methods for
    Population-based Cancer Survival (a 1-week course). Treviso, Italy.
    * Workshops on epidemiological designs and cancer survival analysis
    * Pre-conference courses on Statistical Methods for Population-based Cancer
    Survival
    * Biostatistics/evidence based medicine within the medical program at KI

Articles

All other publications

Selected grants

  • Swedish Research Council
    1 January 2020 - 31 December 2023
  • Development of flexible parametric survival models with multiple time-scales – with applications to Myeloproliferative Neoplasm (MPN)
    Swedish Cancer Society
    1 January 2019
    To understand the disease progression and survival after a cancer diagnosis, it is important to fully capture the complex disease pathways that can occur. More advanced statistical methods are needed to be able to do this in the best way. MPN is a chronic blood tumor disease, with 400 new cases in Sweden annually. Despite efforts to optimize treatment and take preventive measures against complications, patients with MPN have poorer survival than the general population and a high risk of complications such as thromboembolism and bleeding. Within this project, I will develop statistical models for survival data with several time scales and several possible outcomes. A major focus will be to enable reporting of the results of complex analyzes in a way that is easy to understand and to develop user-friendly software so that others can use the methods. The utility of the methods will be demonstrated for myeloproliferative neoplasias (MPNs), with unanswered, clinically important research questions. I will use a population-based cohort of MPN patients with long follow-up time and with matched population controls. 1. Measure how the risk of thromboembolism and bleeding among MPN patients changes over time since diagnosis and changes due to the fact that patients age. Determine whether the risk of thromboembolism increases among patients who have had bleeding and whether the risk of bleeding increases among patients who have had thromboembolism. Describe the entire disease chain from MPN to complications of thromboembolism and bleeding, and finally death, and the proportion of patients who suffered from thromboembolism and bleeding, or both, and died over time. 4. Calculate the life expectancy of MPN patients and lost life years.

Grants

  • Swedish Research Council
    1 December 2024 - 30 November 2028
    Sweden has numerous linkable registers which are a goldmine for research in the medical and social sciences. However, as increasingly more complex research questions are being addressed, there are challenges to correctly and efficiently analyse such data, and further methods development is needed. We aim to develop and apply methods for register-based research that are relevant for a wide range of settings. We also aim to transfer new methodology to subject-matter scientists and train the next generation of biostatistical scientists. The long-term goal is to leverage the rich information within the registers for the benefit of patients, policy-makers and society. Specifically, we will develop, evaluate and apply methods for:1. Missing data in registers2. Causal mediation analysis3. Policy-relevant complex disease models and lifetime outcomes in health economics 4. Federated analyses and synthetic data to share information.Our proposal focuses on the development of statistical methods, but each aim is motivated by real problems in medicine and social science, e.g. improving cancer screening, understanding causal mechanisms for social inequalities in cancer survival, time trends in disease incidence trends and situations when individual-level data cannot cross borders. Our team of biostatistical scientists will work in close collaboration with an extended network of Swedish and Nordic register holders, epidemiologists, clinical and social scientists, and relevant stakeholders.
  • Swedish Research Council
    1 January 2024 - 31 December 2026
    The prognosis following a diagnosis of cancer, or other diseases, is often measured using survival proportions. Recently, however, there has been an increased interest in presenting other measures of patient survival, that are easier to interpret and can give a better understanding of the impact a diagnosis has on an individual’s life span. I have previously developed such methods, namely methods for estimating the life expectancy for cancer patients and the loss in life expectancy (LLE) compared to cancer-free individuals. To further enhance the usefulness of the measures, further extensions are needed. The aim of this project is to further develop and apply the methods, specifically toCombine causal mediation analysis and LLE to quantify the impact of potential drivers of socioeconomic differences in survivalIncorporate uncertainty in general population mortality in the estimation of LLEInvestigate assumptions in survival extrapolation for estimation of LLEThe developed methods will be applied to cancer registry data, to answer research questions of clinical and public health importance. For example, to investigate socioeconomic inequalities in survival of patients with malignant melanoma and colorectal cancer, to estimate the LLE for hematological cancers with an indolent disease course, as well as for patients diagnosed with malignant melanoma at a young age. The methods have potential to be used also in other disease areas.
  • Extensions and applications of loss in life expectancy for cancer patients
    Cancerfonden
    1 January 2023 - 31 December 2025
  • Swedish Cancer Society
    1 January 2023
    The prognosis for cancer patients is often measured using survival rates. Recently, however, there has been increased interest in presenting other measures of cancer patient survival, which are easier to interpret and which can provide a better understanding of the impact a cancer diagnosis has on an individual's lifespan. I have previously developed such methods, namely methods for estimating the average life expectancy of cancer patients and the loss in life expectancy (LLE) compared to cancer-free individuals. In order to further increase the usefulness of the measurements, they need to be further developed. The purpose of this project is to further develop and apply the methods. The new methods will be applied to cancer registry data, to answer research questions of clinical interest and which are important from a public health perspective. For example, to investigate socio-economic inequalities in survival in patients with malignant melanoma and colorectal cancer, to estimate the LLE for hematological cancers with an indolent course of disease, as well as for patients diagnosed with malignant melanoma at a young age. More specifically, I will: - Combining causal analysis and LLE to quantify the impact of potential causes behind socioeconomic disparities in cancer patient survival - Include uncertainty in general population mortality in the estimate of the LLE, so that confidence intervals for the LLE are correctly estimated - Examine assumptions made when estimating LLE, to see in which situations assumptions do not apply and design alternative assumptions
  • Swedish Cancer Society
    1 January 2020
    To understand the disease progression and survival after a cancer diagnosis, it is important to fully capture the complex disease pathways that can occur. More advanced statistical methods are needed to be able to do this in the best way. MPN is a chronic blood tumor disease, with 400 new cases in Sweden annually. Despite efforts to optimize treatment and take preventive measures against complications, patients with MPN have poorer survival than the general population and a high risk of complications such as thromboembolism and bleeding. Within this project, I will develop statistical models for survival data with several time scales and several possible outcomes. A major focus will be to enable reporting of the results of complex analyzes in a way that is easy to understand and to develop user-friendly software so that others can use the methods. The utility of the methods will be demonstrated for myeloproliferative neoplasias (MPNs), with unanswered, clinically important research questions. I will use a population-based cohort of MPN patients with long follow-up time and with matched population controls. 1. Measure how the risk of thromboembolism and bleeding among MPN patients changes over time since diagnosis and changes due to the fact that patients age. Determine whether the risk of thromboembolism increases among patients who have had bleeding and whether the risk of bleeding increases among patients who have had thromboembolism. Describe the entire disease chain from MPN to complications of thromboembolism and bleeding, and finally death, and the proportion of patients who suffered from thromboembolism and bleeding, or both, and died over time. 4. Calculate the life expectancy of MPN patients and lost life years.

Employments

  • Senior Lecturer, Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, 2020-
  • Postdoctoral Researcher, Danish Cancer Society, 2015-2016

Degrees and Education

  • Docent, Karolinska Institutet, 2020
  • Degree Of Doctor Of Philosophy, Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, 2013
  • MSc, Mathematical Statistics, Uppsala University, 2007

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