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Care at the Close of Life: Evidence and Experience
Stephen J. McPhee, Margaret A. Winker, Michael W. Rabow, Steven Z. Pantilat, Amy J. Markowitz
Part D Other Patient Management Issues
Chapter 19. Complexities in Prognostication in Advanced Cancer: “To Help Them Live Their Lives the Way They Want”
Elizabeth B. Lamont, MD, MS, Nicholas A. Christakis, MD, PhD, MPH
Examples of Disease-Specific Prognostication

Topics Discussed: cancer, advanced, measures of outcome, prognosis

Excerpt: "Often, prognostication is most often based on staging of cancer by the Union Internationale Contre le Cancer (UICC) TNM system, which describes the extent of cancer in a patient's body by the size of the tumor, lymph nodes involved, and metastasis. For example, with newly diagnosed colorectal cancer, prognostication has traditionally relied on stage as defined by the UICC-TNM and American Joint Committee on Cancer classifications. The most important morphologic prognostic factors include tumor extent, lymph node status, tumor grade, and the assessment of lymphatic and venous invasion. Newer evidence suggests that tumor budding and tumor border configuration are important. For example, a multivariate analysis of 1324 patients with rectal cancer (confirmed among 316 patients in a separate data set in a validation analysis) identified both nodal status (P = .001) and circumferential margin involvement (P = .001) as the most important factors for estimating 5-year cancer-specific survival.63 In addition, there are suggestions that molecular features of the colorectal cancer can assist in refining prognosis.64 In adenocarcinoma of the esophagus and gastroesophageal junction, recent molecular pathology studies have identified a host of potential genetic and molecular factors that might have prognostic value both in identifying mechanisms of disease progression and in predicting response to targeted therapies.65Investigators have sought to predict patient survival more accurately by combining many of these previously identified clinical predictors. The most recent iteration of studies report integrated models that render a single prognostic score from a combination of prognostic variables. For example, Morita et al56 developed a regression model predicting survival from performance status and specific clinical signs and symptoms termed the Palliative Prognostic Index. The investigators report that the index predicted 3-week survival with a sensitivity of 83% and a specificity of 85% and 6-week survival with a sensitivity of 79% and a specificity of 77%. This model was developed in a sample of patients enrolled in palliative care and validated in another sample...."
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