An article and commentary published in the Journal of the National Cancer Institute reviews available data on diagnosis and management of ductal carcinoma in situ (DCIS), and offers recommendations for the field. These include identification of better risk stratification methods, consideration of the elimination of the word “carcinoma” from the name, and further investigation into whether imaging technology and guidelines can be modified to focus on high-risk lesions.

The commentary is the conference statement from the National Institutes of Health state-of-the-science conference on DCIS. At the conference, speakers and panel members focused on five questions that tackled incidence, risk factors, screening, prognostic factors, and treatment of DCIS. The commentary provides a summary of the answers to those questions based on available research data, input from conference participants, and the panel’s assessment.

“Clearly, the diagnosis and management of DCIS is highly complex with many unanswered questions, including the fundamental natural history of untreated disease,” the panel writes. “Thus, the primary question for future research must focus on the accurate identification of patient subsets diagnosed with DCIS…”

The article by Beth A. Virnig, Ph.D., MPH, of the Division of Health Policy and Management, University of Minnesota School of Public Health, in Minneapolis, and colleagues is a review of literature on DCIS research from 1965 through January 2009. The review was generated for the conference to serve as a background paper.

Virnig covers the five questions discussed at the conference but also highlights areas that need further investigation: associations between mammography use and DCIS incidence and the modification of imaging and treatment guidelines to focus on clinically relevant tumors. Efforts should also be made to make full use of biomarkers, such as HER2 status and necrosis, to determine risk status, according to the paper. “This would allow for focusing aggressive treatment on those who have the greatest probability of benefit,” the authors write.