A committee of national experts, led by a Cleveland Clinic researcher, has established first-of-its-kind guidelines to promote more accurate and individualized cancer predictions, guiding more precise treatment and leading to improved patient survival rates and outcomes. These guidelines were published by Kattan et al in CA: A Cancer Journal for Clinicians.1
These new guidelines are changing the traditional approach of cancer staging methods for cancer treatment. The new risk calculators, which will complement the existing staging system, will enable physicians to more accurately and precisely determine the best treatment for individual patients.
The American Joint Committee on Cancer (AJCC), which is responsible for periodically evaluating and updating the cancer stages, has acknowledged that cancer stages are imperfect, and it is committed to enhancing the system with more prognostic, statistically based risk calculators in 2016.
Precision Medicine Core
In preparation for these changes, the AJCC invited a group of top health-care statistical experts from across the country to form the Precision Medicine Core (PMC). Led by Michael Kattan, PhD, MBA, Chair of Cleveland Clinic’s Department of Quantitative Health Sciences at Cleveland Clinic’s Lerner Research Institute, the group discussed characteristics necessary for developing a quality risk model in cancer patients. The emphasis centered on performance metrics, implementation clarity, and clinical relevance.
“This represents a new paradigm shift for the future of cancer treatments,” Dr. Kattan said.
The PMC was tasked with developing a criteria checklist to evaluate possible cancer risk calculators and determine which calculators will be endorsed by AJCC. The group identified 13 inclusion and 3 exclusion criteria for AJCC risk model endorsement in cancer.
Breast, colon, prostate, lung, melanoma, and head and neck cancers will be the first malignancies to be evaluated for existing prediction models, with the goal being to comprehensively include all cancers in the future.
The formulas must predict overall survival or death from a particular type of cancer and have to pass all 16 criteria. “Our checklist should open the door to a wave of statistical prediction models that get used clinically across many different cancers,” said Dr. Kattan, a pioneer in the development of cancer risk calculators called nomograms. “It could potentially be applied outside cancer as well—anywhere statistical prediction models are being considered for widespread usage.”
The current cancer staging system (stages I–IV), otherwise known as TNM, has been used for decades and is a simple way to universally assess cancer progression in patients around the world. However, many believe that the system is outdated, lumping all cancer patients into four stages, which do not account for individual differences in risk factors—such as genetics, age, gender, and lifestyle. As a result, a patient who is, for example, a “bad” stage III might be undertreated for a cancer that is likely to metastasize. On the other hand, a “good” stage III patient might receive more aggressive treatment than is necessary, which can lead to toxic side effects on the heart, kidneys, or other organs.
Next Steps
Now that the guidelines have been established, researchers across the world will be invited to submit their cancer risk formulas for review by AJCC, with the potential of changing the face of cancer treatment for millions of people worldwide.
“When the models get into physicians’ hands, the way patients are treated and managed and counseled will be forever changed for the better,” Dr. Kattan said. “This is truly a great example of how precision medicine will help cancer patients in the not-so-distant future.”
The next step will be distribution of this checklist, as well as the process, to authors of prediction models. They will then be invited to submit their models for consideration.
The PMC consists of researchers from Cleveland Clinic; The University of Texas MD Anderson Cancer Center; Cedars-Sinai Medical Center; Stanford University; UMC Utrecht, The Netherlands; University of Pennsylvania; Duke University; Sage Bionetworks; Queen’s University; University of Illinois Hospital & Health Sciences System; Mayo Clinic; Memorial Sloan Kettering Cancer Center; and Arizona State University. ■
Disclosure: Dr. Kattan reported no potential conflicts of interest.
Reference
- Kattan MW, Hess KR, Amin MB, et al: American Joint Committee on Cancer acceptance criteria for inclusion of risk models for individualized prognosis in the practice of precision medicine. CA Cancer J Clin. January 19, 2016 (early release online).
