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Biostatistics is a key component of biomedical research and is essential for the interpretation of study results. Statistical techniques inform, among others, about the experimental design, treatment plan, evaluation of a new versus a standard treatment, and identify prognostic factors. The Biostatistics Center provides statistical expertise to researchers and doctors on diverse topics from all areas of observational and experimental biomedical cancer research. This involves developing and implementing statistical approaches to cover a wide range of topics including the design and analysis of epidemiologic studies and clinical trials, the identification of prognostic and predictive biomarkers, sample size calculations, risk prediction, as well as animal and in vitro experiments. In the recent past, the Biostatistics Center has been involved in, among others, prediction of hearing loss after cisplatin-based chemoradiation in patients with locally advanced head-and-neck cancer, biomarker-based treatment of breast cancer with adjuvant tamoxifen, comparison of platforms for array comparative genomic hybridization (aCGH) to identify breast cancers with a BRCA-like copy number profile, and dysphagia and trismus after concomitant chemo-Intensity-Modulated Radiation Therapy (chemo-IMRT) in advanced head and neck cancer. Moreover, the Biostatistics Center is closely involved with several international epidemiological studies on cancer incidence and exposure to chemicals and radiation, and it offers the annual Basic Medical Statistics Course.     

Statistical consulting

Any researcher or doctor can contact us for advice on statistical and general research methodology and data analysis. Support may range from one-time advice to extensive scientific collaboration. You can contact us by e-mail (Mr. Zavrakidis: or phone (Mr. Zavrakidis: 7990) to make an appointment. In general, after a brief intake, your project will be assigned to one of us based on availability and subject-specific knowledge. In order to make collaboration as smooth as possible, we have developed the following list of guidelines based on our past experience:

  • For all but very minor projects/issues, we prefer collaboration over consultation.
  • Please contact us early in the planning stage of a new study/experiment. We rather avoid bias or other issues by design than trying to fix it by analysis.
  • For all other than small projects, we recommend a meeting with all participating collaborators (including the statistician) during the planning stage and possibly at regular intervals throughout the course of the project.
  • We will decide together with you who will perform the statistical analyses.
  • We expect you to provide us with the final product of collaboration or consultancy (usually a manuscript or grant proposal), so that we can make sure the description of the applied methods and the interpretation of the results of the analyses is appropriate. If the analysis (or a non-trivial part of it) is performed by one of us, authorship on the resulting paper is strongly encouraged according to the guidelines of most scientific journals.
  • We ask you to not contact more than one statistician for the same project. If we are not familiar with the specific analyses required for your data, we will consult with other statisticians or bioinformaticians within and outside NKI to make sure that state-of-the-art advice is being provided.
  • If you previously worked with one of us on a project (e.g., for a project proposal), please contact that person directly for any further advice on the same or closely related topics (e.g., study design after funding has been obtained, or analysis after data have been collected). If you contact somebody else, please mention previous assistance provided.
  • Make sure we have seen and approved of any document on which one or more of us is mentioned before it is submitted outside the NKI (manuscripts, project proposals, abstracts of presentations, etc.). This applies also to manuscripts being re-submitted to another journal after they have previously been approved no matter whether any changes have been made.
  • We expect that any editorial decision on manuscripts we collaborated on and corresponding reviewer comments will be forwarded to us without delay.
  • Do not send any data unless we ask you to. In this case, please send the data as described here.

Basic Medical Statistics Course

This full week course explains statistical techniques for the evaluation of biomedical data. We provide an introduction into design aspects, methods of summarizing and presenting data, estimation, confidence intervals and hypothesis testing, including multivariable regression methods for the assessment of association. For more information click here.

Statistical Workshops

We offer a series of workshops on state-of-the-art analytic techniques commonly used in biomedical research. For this first series, we selected the following topics: sample size and power calculation, multiple testing, interaction analysis, and imputation of missing data. For more information click here.

Online statistical tools and statistics references

Click here for a list of links to online statistical tools and statistics references. 

Statistical web-tool for pre-clinical experiments

We have built a web-tool tailored to mice experiments, providing fundamental statistical theory, as well as sample size calculations and guidelines for performing basic statistical tests for the most common designs. Researchers conducting such experiments are highly encouraged to visit and use this web-tool. Temporarily, it is available only internally on Antonet here.


Staff of the Biostatistics Center

John Zavrakidis, Junior researcher/Biostatistician

Sander Roberti, PhD student



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