Biotechnology Healthcare - June 2008 - (Page 37) rious flaws,” says Richard M. Simon, DSc, chief of the Biometric Research Branch in the Division of Cancer Treatment & Diagnosis at the National Cancer Institute. Published in the Journal of the National Cancer Institute, the review focused on microarray use in cancer outcomes studies.1 Because these microassays can measure the expression of as many as 35,000 genes, Simon cautions that their data require more sophisticated statistical techniques than studies that measure only one variable. 1 “Biologists and clinical investigators want to use technology like this because it’s very powerful, but it’s a real challenge for them because the data analysis is complicated,” he says. “There are not enough statisticians available or necessarily knowledgeable on how to do this, and so they’re sort of doing the best they can.” WHAT TO LOOK FOR IN A STUDY But it’s not just about the biostatistical challenges. In a 2006 article in Clinical Advances in Hematology 2 Dupuy A, Simon RM. Critical review of published microarray studies for cancer outcome and guidelines on statistical analysis and reporting. J Natl Cancer Inst. 2007;99:147–157. Simon RM. Checklist for Evaluating Reports of Expression Profiling for Treatment Selection. Clin Adv Hematol Oncol. 2006;4:219–224. & Oncology,2 Simon included 17 “key issues” that may call study results into question. The following are among the most important: Is it a developmental or validation study? Developmental and validation studies are akin to phase 2 and 3 clinical trials. For example, Oncotype DX developmental studies identified the 21 genes (16 cancer related and 5 reference genes) whose expression appeared to have prognostic (cancer recurrence) and predictive (chemotherapy benefit) value, and gave a mathematical “weight” to each gene (the algorithm). Together, this generated the recurrence score (the classifier). Validation studies corroborated that the 21-gene expression assay Gary Wagner “We basically took a lot of the good principles used in how to develop drugs and get the evidence to justify the use of a new drug and applied those same principles,” says Steven Shak, MD, of Genomic Health. MAY/JUNE 2008 · BIOTECHNOLOGY HEALTHCARE 37
For optimal viewing of this digital publication, please enable JavaScript and then refresh the page. If you would like to try to load the digital publication without using Flash Player detection, please click here.