I am a biostatistician with primary research interests in developing and applying statistical methods for population-based cancer survival analysis, particularly the estimation and modeling of relative survival. Current research, in collaboration with Professor Paul Lambert (University of Leicester), focusses on the development and application of methods for presenting patient survival that are relevant for patients, clinicians, and the general public. I also have general interests in epidemiology, particularly cancer epidemiology, and methods for register-based research.
Research in the area of cancer patient survival
Patient survival is the most important single measure of cancer patient care (the diagnosis and treatment of cancer) and together with incidence and mortality is one of the key measures of cancer control. The optimal method for monitoring and evaluating the effectiveness of cancer patient care is through the population-based study of cancer patient survival, which is only possible using data collected by population-based cancer registries (Dickman and Adami, 2006). It is standard in population-based studies to use relative survival as the measure of cancer patient survival. Relative survival is the ratio of observed (all-cause) to expected survival proportion and provides a measure of excess mortality associated with diagnosis of cancer. Excess mortality is the difference between the observed (all-cause) mortality and the mortality that would have been expected if the patients were not diagnosed with cancer. It has the advantage that cause of death information is not required and that it captures mortality both directly due to the cancer as well as indirectly due to the cancer (e.g., increased risk of non-cancer mortality caused by the treatment). In cancer clinical trials it is standard to estimate cause-specific survival but this is less frequently used in population-based studies since information on cause of death is not as accurate as it is in clinical trials.
I have contributed to several developments in methodology for estimating and modelling relative survival. Our 2004 paper on modelling relative survival has been cited over 400 times and the model proposed therein is one of the most commonly applied models for relative survival. In recent years I have collaborated closely with Prof. Paul Lambert from the University of Leicester; we have developed and applied cure models for relative survival and methods for estimating the probability of death due to cancer in the presence of competing risks. We have investigated the assumptions underlying relative survival and evaluated approaches to predicting cancer patient survival. We have also developed methods for partitioning excess mortality that have been applied to estimating treatment-related mortality among patients with Hodgkin lymphoma. We have developed freely-available user-friendly software (primarily Stata but also SAS) to implement our methods and hold courses each year (http://cansurv.net/) to train cancer researchers working in the area. I collaborate closely with clinicians; all of my methods are developed to address relevant clinical questions. We typically publish details of the new methods in statistical methods journals and applications of the methods in clinical journals.
Research in cancer epidemiology (other than patient survival)
My primary training is in statistics and my primary research interests are in the development and application of statistical methods for cancer patient survival. However, I also have a strong interest in cancer epidemiology in general and consider myself as much a cancer epidemiologist as a biostatistician.
Research in perinatal and reproductive epidemiology
I am an active and enthusiastic teacher. I particularly enjoy teaching courses in the analysis of cancer patient survival to cancer researchers since I learn so much from discussions with the participants. Details of my teaching can be found on my personal web page.
From 2005-2007 I was director of postgraduate studies and member of the working group of the postgraduate program in epidemiology and continue to teach postgraduate courses at KI.
Together with Paul Lambert, I teach a 1-week course on statistical methods for population-based cancer survival analysis each June in Veneto, Italy. Dates for 2014 are June 16-21.
From 2006-2010 I was responsible for coordinating all undergraduate education at MEB (grundutbildningsansvarig) and heavily involved in teaching in the KI medical program, where I was chair of chair the group that had an overall responsibility for coordinating scientific development within the program including specific responsibility for 5 weeks coursework integrated throughout the program and a 20 week project.
Current supervision of PhD students
- 1990, BMath, University of Newcastle, Australia.
- 1992, BMath (honours class 1), Statistics, University of Newcastle, Australia.
- 1997, PhD, Department of Statistics, University of Newcastle, Australia.
- 1998, Postdoc (Cancer Epidemiology), Karolinska Institutet.
- 2002, Docent (Biostatistics), Karolinska Institutet.