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Andrew K. Lee and Christopher L. Amling

For decades physicians have attempted to accurately predict post-treatment outcomes before performing prostate cancer interventions. Use of basic clinical factors, such as clinical T-stage, biopsy Gleason sum, and pretreatment prostate specific antigen, has allowed some level of prediction of pathologic and clinical outcomes. However, these basic tables and risk stratification schema provide a broad range of potential outcomes. The rapid growth of retrospective research in prostate cancer has yielded an abundance of additional potential prognostic factors that may influence outcomes of interest; however, incorporating and understanding the significance of these ever-expanding factors is difficult for even the most experienced physicians. Nomograms incorporate these factors (including treatment-specific) and assign them relative weights to provide a probability of the outcome of interest on a graphical scale. They distill large numbers of data into a manageable format and provide the probability of outcomes on a continuous scale rather than in categoric groups. However, because they require a computation to generate a probability, they are not amenable to memorization, which decreases ease of use. Furthermore, these numbers still have associated confidence intervals and the models are largely derived from retrospective data, which have inherent drawbacks. Clinicians and patients should still exercise due diligence when interpreting the results of these nomograms, and these prediction tools should not serve as a stand-alone substitute for clinical decision-making.

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Lydia T. Madsen, Deborah A. Kuban, Seungtaek Choi, John W. Davis, Jeri Kim, Andrew K. Lee, Delora Domain, Larry Levy, Louis L. Pisters, Curtis A. Pettaway, John F. Ward, Christopher Logothetis and Karen E. Hoffman

Clinical oncology trials are hampered by low accrual rates, with fewer than 5% of adult patients with cancer treated on study. Clinical trial enrollment was evaluated at The University of Texas MD Anderson Cancer Center's Multidisciplinary Prostate Cancer Clinic (MPCC) to assess whether a clinical trial initiative, introduced in 2006, impacted enrollment. The trial initiative included posting trial-specific information in clinic, educating patients about appropriate clinical trial options during the treatment recommendation discussion, and providing patients with trial-specific educational information. The investigators evaluated the frequency of clinical trial enrollment for men with newly diagnosed prostate cancer seen in the MPCC from 2004 to 2008. Logistic regression evaluated the impact of patient characteristics and the clinical trial initiative on trial enrollment. The median age of the 1370 men was 64 years; 32% had low-risk, 49% had intermediate-risk, and 19% had high-risk disease. Overall, 74% enrolled in at least one trial and 29% enrolled in more than one trial. Trial enrollment increased from 39% before the initiative (127/326) to 84% (880/1044) after the trial initiative. Patient enrollment increased in laboratory studies (from 25% to 80%), quality-of-life studies (from 10% to 26%), and studies evaluating investigational treatments and systemic agents (from 6% to 15%) after the trial initiative. In multivariate analysis, younger men (P<.001) and men seen after implementation of the clinical trial initiative (P<.001) were more likely to enroll in trials. Clinical trial enrollment in the MPCC was substantially higher than that seen nationally in adult patients with cancer, and enrollment rates increased after the introduction of a clinical trial initiative.