Words like “remarkable,” “exciting,” “very special,” and “huge impact” accompanied release of a study that classifies breast cancer into 10 different subgroups, a finding that can change the way the disease is diagnosed and treated. However, the ground-breaking research might make life more complicated for clinician executives at health insurance plans.
Just how groundbreaking are the findings? “Our work provides a definitive framework for understanding how gene copy number aberrations affect gene expression in breast cancer and reveals novel subgroups that should be the target of future investigation,” states “The Genomic and Transcriptomic Architecture of 2,000 Breast Tumours Reveals Novel Subgroups.” The study, published in the journal Nature, is the result of work by a research team at the University of Cambridge in Great Britain called the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC).
“It potentially complicates things for managed care organizations, which continue to have a fiduciary duty to match coverage of breast cancer to evidence-based appropriateness,” says Jaan Sidorov, MD, a consultant and member of MANAGED CARE’s Editorial Advisory Board. “Oncologists — who advocate on behalf of their patients — will need to work with and educate the managed care organization’s clinical staff on the rationale for the proposed treatments. It’ll take time — and patience — on both sides.”
The DNA and RNA of nearly 2,000 tumor samples were analyzed from between 5 and 10 years ago. “We present an integrated analysis of copy number and gene expression in a discovery and validation set of 997 and 995 primary breast tumours, respectively, with long-term clinical follow-up,” the study states.
Raju Kucherlapati, PhD, a genetics professor at Harvard Medical School (not part of the study team), tells the Los Angeles Times that “The fact that they have 997 samples for discovery and 995 for validation makes it very special.”
Time magazine reports that the new categories range from very treatable to extremely aggressive. “Because patient responses can’t be precisely predicted, it can lead to overtreatment, with doctors trying therapies even though the patient may not benefit. Having a more detailed system of tumor categories can not only help avoid that problem, but also tailor treatment to individual patients and predict women’s survival more accurately.”