Development of a prostate cancer metagram: a solution to the dilemma of which prediction tool to use in patient counseling.

Many treatment options are available to the human with clinically localized prostate cancer, including surgery, radiation, and even active surveillance. To the authors' knowledge, there is no consensus on the optimal management of this patient population, with most clinicians tending to recommend the treatment with which they are most familiar. Effective patient counseling allowing informed decision making can be best achieved with a formalized system that offers accurate predictions of outcomes for all available treatment approaches. The authors organized the currently available prostate cancer prediction tools toward the formation of a metagram that can be used to tailor management to the individual patient. A comprehensive review of the literature was performed to identify published prediction tools intended for use in prostate cancer. Tools were categorized by a combination of treatment modality and the outcome being predicted, and incorporated into a metagram constructed of 16 different treatment options and 10 outcomes related to cancer control, survival, and morbidity. A search of the literature revealed 44 prostate cancer prediction tools that assessed at least 1 of the 160 treatment/outcome combinations that comprise the metagram. Only 31 cells of the metagram were populated with currently available tools. Prediction tools offer the most accurate estimates of outcomes in prostate cancer, but their current role in patient counseling is complicated by the large number of existing tools, as well as a lack of comparative data. To address this, the authors incorporated the most relevant prediction tools currently available into a prostate cancer metagram that may offer evidence-based and individualized predictions for multiple endpoints after all available treatment options in clinically localized prostate cancer. The metagram also reveals areas of deficiency in the current catalog of prediction tools. Many more prediction tools are needed. Cancer 2009;115(13 suppl):3039-45. (c) 2009 American Cancer Society.