127IN - Can PET imaging help individualize the treatment of colorectal cancer patients?
|Date||01 October 2012|
|Event||ESMO Congress 2012|
|Session||ESMO-JSMO Joint symposium: Recent advances in the treatment of GI tract and liver cancer in the EU and Japan|
|Topics|| Colon Cancer
Imaging, Diagnosis and Staging
While the science of medicine tries to understand the rules and hidden laws behind diseases and their management, the art of medicine aims to treat individual patients by matching clinical observations and existing knowledge. The ambiguity between the art and the science of medicine has never been so obvious than in our attempts to tailor cancer treatment to individual patients: the growing evidence of tumor heterogeneity makes understanding a patient's disease increasingly complex, especially when one considers the inadequacy of current assessment tools, which is becoming more apparent each day. In the setting of advanced colorectal cancer (aCRC), three main clinical situations coexist: metastasis that is immediately resectable with curative intent, borderline resectable disease and definitively non-resectable disease. Despite broad parameters within which to treat disease, clinicians lack tools that can rapidly and reliably point out treatment inefficiency in order to allow a therapeutic strategy to be quickly stopped or adapted. The usual endpoints of prospective randomized trials, which form the basis of the science of medicine, are seldom usable at the bedside to exercise the art of medicine. Death (overall survival) and progression (progression-free survival) both occur too long after the beginning of a treatment, and quality of life is much too subjective. The RECIST-based response rate is more readily available and relatively well standardized, but careful analysis reveals a definite but only small correlation with survival outcome in the aCRC setting. Several alternates for tumor response assessment have been studied: plasma tumor markers, circulating tumor cells, and functional imaging, notably the FDG-PET scan. However, few data from well-structured studies are available, and they are sometimes discordant. Among these alternatives, metabolic imaging by FDG-PET appears to be the most promising, bearing the highest and the most reproducible negative predictive value. This means that it could become useful both in the daily clinic and to develop new concepts for clinical trials. The aim of this review is to present the available evidence, point out areas of weakness, and consider how current findings might shape the future development of both FDG-PET techniques and study designs.Disclosure
The author has declared no conflicts of interest.