Statistical methods

The development of statistical data analysis methods helps us gain a better understanding of the causes of cancer and epidemiology, and of cancer screening in Finland.


Cancer research is supported and conditioned by appropriate statistical methods. The assessment of cancer survival is a key part of methodological research. It has focused on more reliable long-term survival and better computational regional comparative methods. Methods based on computational statistics have also been developed for assessing Population Attributable Fractions. The modeling of the hidden structures of cancer was investigated in co-operation with Aalto University, as well as new ways to evaluate the overdiagnostics associated with screening. In addition, evaluating the new methods of assessing the heredity and family cumulative cancer and also utilizing computational statistics on learning in cancer coding will be investigated within the Finnish Cancer Registry


All of the projects described above are in operation

Top 3 publications:

Comparing net survival estimators of cancer patients

Choosing the net survival method for cancer survival estimation

Regional variation in relative survival—quantifying the effects of the competing risks of death by using a cure fraction model with random effects

Research team: Janne Pitkäniemi, Karri Seppä, Joonas Miettinen, Tiina Hakanen, Matti Rantanen, Heidi Ryynänen

Funding: Cancer Society of Finland, Cancer Foundation of Finland.

Collaborating institutions: University of Helsinki / Department of Computer Science, Aalto University, University of Oulu, Department of Public Health

Lead researcher: Janne Pitkäniemi