About me

I obtained my doctoral degree in Statistics at Southampton University (U.K.) in 1996. In 2005, I was appointed Senior Lecturer in Biostatistics at Karolinska Institutet at the Department of Medical Epidemiology and Biostatistics. In 2019, I was appointed as Professor in Biostatistics in the same department. I am interested in a broad range of statistical methods topics such longitudinal data analysis, statistical genetics, graphical modeling, measurement error and machine learning. I have been heavily involved in genetic association and other epidemiological, studies of breast cancer, at Karolinska Institutet and have published on genetic risk prediction models of breast cancer.

Research description

I am involved in a number of research projects which have a general aim to contribute to the understanding of breast cancer tumour progression and to the identification of women with high risk for breast cancer, in particular that which is aggressive/has poor prognosis. We develop novel statistical approaches and apply them to large, and detailed, studies of breast cancer/mammography screening. My research builds on previous work on the identification of genetic variants for breast cancer, the development of statistical models of breast cancer risk and tumour growth and the development of novel approaches for measuring mammographic density.   

Selected publications

  • Strandberg R and Humphreys K (2019) Statistical models of tumour onset and growth for modern breast cancer screening cohorts. Mathematical Biosciences. 2019 Oct 15:108270. doi: 10.1016/j.mbs.2019.108270. [Epub ahead of print]
  • Abrahamsson L, Isheden G, Czene K, Humphreys K. Continuous tumour growth models, lead time estimation and length bias in breast cancer screening studies. Statistical Methods in Medical Research. 2019 : 962280219832901.
  • Isheden G, Abrahamsson L, Andersson TM-L, Czene K, Humphreys K. Joint models of tumour size and lymph node spread for incident breast cancer cases in the presence of screening. Statistical Methods in Medical Research. 2019 Jan 3. doi: 10.1177/0962280218819568. [Epub ahead of print]
  • Isheden G and Humphreys K. (2019) Modeling breast cancer tumour growth for a stable disease population. Statistical Methods in Medical Research. 28: 681-702.
  • Alsheh Ali M, Eriksson M, Czene K, Hall P, Humphreys K. (2019) Detection of Potential Microcalcification Clusters Using Multi Vendor For-presentation Digital Mammograms for Short-term Breast Cancer Risk Estimation. Medical Physics. 46:4 1938-1946.
  • Andersson TML, Crowther M, Hall P, Czene K, Humphreys K. (2017) Mammographic density reduction as a prognostic marker for postmenopausal breast cancer; results using a joint longitudinal-survival modeling approach. Am. J. Epidemiology. 186: 1065-1073.
  • Abrahamsson L and Humphreys K. (2016) A statistical model of breast cancer tumour growth with estimation of screening sensitivity as a function of mammographic density. Statistical Methods in Medical Research. 25: 1620-1637.
  • Abrahamsson L, Czene K, Hall P, Humphreys K. (2015) Breast cancer tumour growth modeling for studying the association of body size with tumour growth rate and symptomatic detection. Breast Cancer Research. 17: 116.
  • Darabi H, Czene K, Zhao W, Liu J, Hall P, Humphreys K. (2012) Breast Cancer risk prediction and individualized screening based on common genetic variation and breast density measurement. Breast Cancer Research 14:R25.
  • Cheddad A, Czene K, Shepherd JA, Li J, Hall P and Humphreys K (2014) Enhancement of mammographic density measures in breast cancer risk prediction. Cancer Epidemiol Biomarkers Prev. 23: 1314-1323.
  • Darabi H and Humphreys K. (2011) Single SNP and pathway tests of genetic association incorporating phenotype heterogeneity. Human Heredity. 71; 11-22. 
  • Humphreys K, Grankvist A, Leu M, Hall P, Ripatti S, Groop L, Klareskog L, Grönberg H, Pedersen NL, Mattingsdal M, Andreassen OA, Lichtenstein P, Purcell S, Sklar P, Sullivan P, Hultman C, Palmgren J, Magnusson P. (2011) The Genetic Structure of the Swedish population. PLoS One. 6(8):e22547.
  • Grunewald M, Humphreys K and Hössjer O. (2010) A stochastic EM type algorithm for parameter estimation in models with continuous outcomes, under complex ascertainment. International Journal of Biostatistics. Vol.6: Iss. 1, Article 23.
  • Sjölander A, Vansteelandt S. and Humphreys K. (2010) A principal stratification approach to assess the differences in prognosis between cancers caused by hormone replacement therapy and by other factors. International Journal of Biostatistics. Vol.6: Iss. 1, Article 20.
  • Hössjer O, Hartman L and Humphreys K. (2009) Ancestral recombination graphs under nonrandom ascertainment with applications to gene mapping. Statistical Applications of Genetics and Molecular Biology. Vol. 8. Issue 1.
  • Jonasdottir G, Humphreys K, Palmgren J. (2007) Testing Association in the Presence of Linkage - A powerful score for binary traits. Genetic Epidemiology. 31: 528-540.
  • Humphreys, K. and Titterington, D.M. (2003) Variational approximations for categorical causal modelling with latent variables. Psychometrika, 68: 391-412.
  • Hall, P., Humphreys, K. and Titterington, D.M. (2002). On the adequacy of variational lower bound functions for likelihood-based inference in Markovian models with missing values. Journal of the Royal Statistical Society, B, 64, 549-564. 
  • Humphreys, K. and Titterington, D.M. (2000). Improving the mean field approximation in belief networks using Bahadur's reparameterisation of the multivariate binary distribution. Neural Processing Letters, 12, 183-197.
  • Skinner, C.J. and Humphreys, K. (1999). Weibull regression for lifetimes measured with error. Lifetime data analysis, 5, 23-37.

Current supervision of PhD students and Postdoctoral researcher


  • 1996, PhD (Social Statistics), Southampton University, U.K.
  • 1997, Postdoc (Statistics/Psychometrics), Stockholm University
  • 1999, Postdoc (Statistics), Glasgow University, U.K.
  • 2002, Docent (Biostatistics), Karolinska Institutet