• Research data sources span the spectrum from electronic health records (EHRs) to disease registries to clinical research protocol repositories, with varying degrees of completeness, quality, and research utility. In silico research depends on having complete and valid information.
• caBIG is undergoing renovations and new informatics project review criteria are being implemented; NCI is open and receptive to communications from interested parties.
In the first session, an overview of the current status of cancer informatics was provided from the perspectives of cancer centers, cancer cooperative groups, and clinical translational researchers. Panelists also discussed the lessons that could be learned from the ongoing evolution of NCI’s caBIG.
Rapid advances in technology have led to a dramatic increase in the output of genomic and molecular data related to cancer biology, said Lawrence Shulman, chief medical officer and chief of the Division of General Oncology at the Dana-Farber Cancer Institute. These emerging data can inform our understanding of basic cancer biology, epidemiology, and behavior, as well as response to therapies, toxicity of therapies, and optimal care for an individual patient or cohort. However, the sheer volume of information presents significant data management and analysis challenges and is becoming overwhelming from a clinical decision-making standpoint.
To be optimally useful, data should be structured in a database, and we are still in the learning stages of how best to structure genomic and molecular data, Shulman noted. For clinical data to be useful, they should contain certain critical elements. From an oncology perspective, examples of key data elements include patient demographics; tumor type and anatomic and non-anatomic staging; treatment plan, treatment intent (e.g., curative or palliative), and actual treatment; tumor response; toxicity; patient-reported outcomes; and disease-free and overall survival. The nation is moving, albeit