This interview is with Cancer Informatics editorial board member Dr Grant Izmirlian. Cancer Informatics is an open access journal published by Libertas Academica.

Editor in Chief Dr James Willey has recently issued a call for papers.

What is the primary focus of your research?

1. Statistical issues related to the design and interim analysis of prevention trials.

2. Methods of stochastic processes and natural history models for cancer progression in the design, analysis and interpretation of case control studies of cancer screening and of "case group" analyses of randomized cancer screening trials.

3. Machine learning and variable selection.

What are the most exciting developments arising from current research in your area?

1. We are now in a position to address whether or not screening a healthy population lowers cancer specific mortality using data from a large randomized trial of cancer screening.

2. It now looks like the most promising use of bio-molecular profiling will be for tailoring the prognosis and treatment of patients with early stage cancers. One exciting area of research for a statistician (who leans towards being a trialist) is research investigating how, if at all, one can design a sequential trial with the goal of defining such patient subgroups, with the enrichment of 'winner' treatments corresponding to each particular bio-molecular profile.

Who are your main collaborators? Please describe your work with them.

1. Phil Prorok and Richard Fagerstrom: the design of an interim analysis plan for a cancer prevention trial; work on the "case analysis" of a randomized cancer screening trial.

2. Paul Doria Rose: statistical issues in the design analysis and interpretation of a case control study of cancer screening.

3. Robert Grubb and Adam Kibel: longitudinal model for the effect of PSA velocity and DRE on incident prostate cancer with verification bias adjustment

4. Vernon Steele: oligotide microarray study of andosterones DHEA and DHT on the LNCAP cell line.

How did you come to be working in your research area?

I have always been keenly interested in applying mathematical ideas to problems from the world around us. I decided that I to pursue graduate study in a department of pure mathematics in order to obtain the best possible training in mathematics. Upon finishing a Ph.D. in probability theory I then did post-doctoral study in mathematical demography in the biostatistics department at UNC Chapel Hill. I then did an IRTA fellowship with the Epidemiology Demography and Biometry program of the National Institute on Aging.

Since 1999 I have been a mathematical statistician in the Division of Cancer Prevention at the National Cancer Institute. In the last 10 years I have been involved with the prostate lung colo-rectal and ovarian (PLCO) trial of cancer screening working in the prostate subcommittee. Since 2002 I have been doing the interim analysis for all 4 component sub-trials. With the lead statistician of the national lung screening trial (NLST) I have led the design of the interim analysis plan of that trial, and have been performing its annual interim analyses since the adoption of that plan in 2005.

What do you think about the development of open access publishing? Have you published in an open access journal? What motivated you to do so?

I very much like the idea of open access publishing--it ties in very nicely with open source software, of which I am an active contributor. My only reservation in sending material to an open access journal is the fear that such work will be looked upon as if the review had been less strenuous simply because it appears in an open access journal. This should not be a problem for well established scientists, but for someone like me who is early to mid career, it is still an issue.

What articles and/or books have you published recently?

Andriole, GL; Grubb, RL; Buys, SS, et al. Mortality Results from a Randomized Prostate-Cancer Screening Trial NEJM 360(13): 1310-1319 [Pubmed]

Steele, VE; Arnold, JT; Le, H, et al. Comparative effects of DHEA and DHT on gene expression in human LNCaP prostate cancer cells. Anticancer Research 26(5A): 3205-3215 [Pubmed]

Izmirlian, G. Application of the random forest classification algorithm to a SELDI-TOF proteomics study in the setting of a cancer prevention trial. Applications of Bioinformatics in Cancer Detection. 1020:154-174 [Pubmed]

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