Path Toward Prognostication and Prediction: An Evolving Matrix

The popular buzz phrase “personalized medicine” represents an attractive concept to patients and clinicians alike with its promise of optimizing therapeutic results and minimizing toxicities that can be linked to biologic characteristics of each individual. Certainly it is true, or at least should be true, that clinicians routinely attempt to harmonize individual patient characteristics and circumstances when formulating recommendations and selecting an oncology care plan. Factors that are usually considered include disease stage and other pathologic findings, selected molecular or other biologic factors, psychosocial issues, expectations and perceptions of the patient and family members, performance status, comorbidities, and symptoms. The quest to apply highly specific individual host and/or tumor profiles as prognostic and predictive markers, however, has been elusive and has cast the concept of personalized medicine more as a work in progress and future goal rather than a current reality. The ability to prognosticate is based on data from population observations over time, which usually segregate patients by disease and stage to provide survival statistics for a given subset of patients, regardless of treatment intervention. The introduction of prognostic factors into discussions between the clinician and an individual patient has the potential to inform recommendations and decisions based on the risk of recurrence. Once the estimated risk of recurrence is determined by available population data, the focus of discussion usually centers on options for intervention and monitoring approaches, particularly for patients who have cure as their major goal. Although considering risk of recurrence, as well as the potential benefits and harms of an intervention, are critical for decision making, too often the oncologist is limited in estimating the benefit of therapeutic intervention for the individual patient because of lack of strong and clinically validated predictive factors. Indeed, one of the greatest challenges in cancer medicine is the need to fuse prognostic and predictive markers derived from studies of groups of patients into a cohesive assessment that has relevance for an individual patient, including risks from the disease and both the risks and benefits from potential interventions. Prognostic determination for patients with colorectal carcinoma has long centered on stage of disease as the most powerful predictor of outcome. Colorectal cancer staging has been further refined in the seventh edition of the American Joint Committee on Cancer staging manual (AJCC-7) published in 2010, particularly for stages II and III disease. New subsets of patients are now listed and include new lymph node subsets, based on survival information generated from the National Cancer Data Base and Surveillance, Epidemiology and End Results database. The latest AJCC staging manual exemplifies the potential offered by well-constructed databases to generate information that can be integrated into a prognostic tool. Furthermore, with the development of robustly annotated clinical databases of patients with cancer, including those from international clinical trials, and the collection of biologic specimens linked to these clinical databases, the opportunities to identify additional prognostic and predictive biomarkers become more feasible. The most widely used prognostic factors for estimating recurrence risk and survival for patients with colorectal cancer are from pathologic assessment including T (depth of invasion) and N (lymph node metastasis) categories that define stage in patients without distant metastasis. On the basis of well-established data on prognosis and improvement in survival after adjuvant chemotherapy, patients with stage III colon cancer are routinely treated with postoperative chemotherapy rather than surgery alone, despite wide variability in survival among the subsets of patients with stage III disease, especially in AJCC-7. In contrast to stage III guidelines, in patients with stage II disease, additional pathologic findings are taken into consideration for postoperative decisions, including histologic grade, perineural invasion, lymphovascular invasion, inadequate number of lymph nodes sampled, length of negative margins, and perforation, along with clinical assessment of obstruction. Preand postoperative carcinoembryonic antigen is a marker that has also been used, not only to predict recurrence but also as a monitoring tool for development of recurrence. During the last few years, a molecular tumor marker (ie, microsatellite instability [MSI] status) has emerged as relevant for select patients with colon cancer. High levels of MSI (MSI-H) are characteristic of Lynch syndrome (hereditary nonpolyposis colorectal cancer syndrome). In addition, Sargent et al reported a pooled analysis of patients with stages II and III disease enrolled onto five completed randomized clinical trials of fluorouracil with levamisole or leucovorin versus surgery alone to evaluate the outcome of patients with deficient mismatch repair (dMMR) cancer defined by the presence of either JOURNAL OF CLINICAL ONCOLOGY E D I T O R I A L S VOLUME 29 NUMBER 35 DECEMBER 1