T
Timo Hakulinen
Researcher at University of Helsinki
Publications - 241
Citations - 19556
Timo Hakulinen is an academic researcher from University of Helsinki. The author has contributed to research in topics: Cancer & Population. The author has an hindex of 73, co-authored 240 publications receiving 18561 citations. Previous affiliations of Timo Hakulinen include Karolinska University Hospital.
Papers
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Journal ArticleDOI
Flavonoid intake and risk of chronic diseases
Paul Knekt,Jorma Kumpulainen,Ritva Järvinen,Harri Rissanen,Markku Heliövaara,Antti Reunanen,Timo Hakulinen,Arpo Aromaa +7 more
TL;DR: The risk of some chronic diseases may be lower at higher dietary flavonoid intakes, and a trend toward a reduction in risk of type 2 diabetes was associated with higher quercetin intakes.
Journal ArticleDOI
Cancer survival in five continents: a worldwide population-based study (CONCORD)
Michel P Coleman,Manuela Quaresma,F Berrino,Jean-Michel Lutz,Roberta De Angelis,Riccardo Capocaccia,Paolo Baili,Bernard Rachet,Gemma Gatta,Timo Hakulinen,Andrea Micheli,Milena Sant,Hannah K. Weir,J. Mark Elwood,Hideaki Tsukuma,Sergio Koifman,Gulnar Azevedo e Silva,Silvia Francisci,Mariano Santaquilani,Arduino Verdecchia,Hans H. Storm,John L. Young +21 more
TL;DR: This is, to the authors' knowledge, the first worldwide analysis of cancer survival, with standard quality-control procedures and identical analytic methods for all datasets, and should eventually facilitate joint assessment of international trends in incidence, survival, and mortality as indicators of cancer control.
Journal ArticleDOI
Regression models for relative survival.
TL;DR: The model can be estimated in any software package that estimates GLMs with user‐defined link functions and utilizes the theory of generalized linear models for assessing goodness‐of‐fit and studying regression diagnostics.
Book
Survival of cancer patients in Europe: The Eurocare Study
TL;DR: Part 1: Introduction and Methodology F.P. Coleman, C. Cummins, G. Rider, J. Smith and J. Youngson: Health care system, cancer registration and follow-up of cancer patients in the United Kingdom.
Journal ArticleDOI
Cancer survival corrected for heterogeneity in patient withdrawal.
TL;DR: A method based on the concept of an 'expected life table' is proposed for removal of the bias and it is suggested that the practical performance of the proposed method is better than that of other alternatives, even when the relative survival rates in the subgroups are not equal.