May 2012, Vol 1, No 1

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Precision Medicine: Applying Predictive and Prognostic Indices to Risk-Adapted Treatment Selection

Sandra Kurtin, RN, MS, AOCN, ANP-C


The shift from dose-intense standard chemotherapy to therapies targeting specific signaling pathways, molecular targets, or elements of the tumor microenvironment presents a number of challenges to the oncology professional and the patient. Cancer diagnosis and treatment requires precision in the diagnostic evaluation (asking all the critical diagnostic questions at the time of diagnosis), comprehensive assessment of the individual patient (personal attributes that place a patient at risk), and consideration of a life-span approach (the concept of a marathon as opposed to a sprint).

Precision medicine allows for the best evidence- based approach to treatment for each individual patient, while limiting unnecessary exposure to potentially toxic and costly therapies in order to preserve future treatment options for patients unlikely to respond. Implementing the principles of precision medicine requires ongoing integration of advances in molecular biology, diagnostic imaging, and risk-adapted treatment selection. Scientific practicality (knowing how to adapt these key elements and clinical trials data for the individual patient based on the goals of therapy) is essential to the best possible outcome. This paper describes the key elements of precision medicine with clinical insights gained over 27 years of oncology practice, including 22 years as an advanced practitioner in oncology.

Advances in Molecular Biology: The Foundation for Effective Treatment

Precision medicine is the application of predictive biomarkers, together with consideration of prognostic biomarkers and patient attributes, in the selection of therapy using a personalized life-span approach (Table 1).1,2 Prognostic biomarkers reflect the likely natural history of a given disease in untreated patients3 and may influence the approach to treatment based on high-risk or low-risk disease. For example, a patient with multiple myeloma with the 17p cytogenetic abnormality is known to have an inferior disease trajectory independent of other disease attributes and will be considered for autologous stem cell transplant earlier in the phase of treatment.4 Similarly, a patient with triple-negative breast cancer (negative estrogen, progesterone, and HER2) is felt to have high-risk disease, which with no option for hormonal therapy will require combination therapy with drugs thought to be effective in this setting.5

Predictive biomarkers, on the other hand, are attributes of the tumor thought to identify patients who may benefit from a given therapy.3 These biomarkers are used to guide treatment selection. For example, a patient with metastatic colorectal cancer who is found to have wild-type KRAS is more likely to benefit from epidermal growth factor receptor inhibitor (EGFR-I) therapy, whereas a patient who has mutated KRAS is not likely to benefit.6 A single biomarker can have both predictive and prognostic value, but each has different clinical utility. For example, HER2 testing in patients with breast cancer serves as a negative prognostic indicator (considered higher risk) but also has positive predictive value (patients are likely to respond to HER2-directed therapies). 5,7

Thus, biomarker-driven treatment selection may limit exposure of potentially toxic treatments in patients not likely to benefit and is therefore more cost-effective and offers the best option for therapy in patients with positive predictive biomarkers. Optimally, all subpopulations of patients with predictive and prognostic biomarkers enrolled in clinical trials will be enrolled in tandem trials for tissue banking and longitudinal analysis to further characterize these attributes and clinical outcomes. Selected predictive and prognostic indices for common solid tumors are included in Table 2.5-12 Examples of high-risk features for common hematologic malignancies are provided in Table 3.1

The growing trend in risk-adapted treatment selection – based on specific attributes of the tumor, extent of disease, and the individual patient – challenges the oncology professional to maintain a working knowledge of tissue diagnoses and specific pathology techniques. This is necessary to facilitate accurate diagnoses and consider all necessary testing at the time of the original biopsy or resection. Selecting treatment based on the global diagnosis for both solid and liquid tumors is no longer adequate, and several technologies are now available for obtaining molecular biomarkers, including interphase cytogenetics, fluorescence in situ hybridization, polymerase chain reaction, and gene expression profiling. Individual testing may be performed on tissue or blood, and diagnostic packages such as the Oncotype DX, a 21-gene assay estimating a recurrence score in breast cancer with both prognostic and predictive value, have become more common.

Risk-Adapted Treatment Selection: What You See Is What You Get

Applying the concepts of predictive and prognostic indices in risk-adapted treatment selection is expected, based on recent scientific discoveries. However, selecting therapies based on the diagnostic evaluation adds an element of complexity to the treatment of each patient. The selection of primary therapies in some tumors, the sequencing of therapies, and the choice of therapies in metastatic disease or in the instance of disease progression are driven by these principles. For effective treatment planning, a comprehensive disease-specific diagnostic evaluation is essential, as each disease requires specific testing.

Asking key questions at the time of the initial tissue diagnosis is perhaps the most critical step in the diagnostic process. For example, it is well established that a fine-needle aspirate is inadequate for the diagnosis of lymphoma, that obtaining fewer than 12 regional lymph nodes with primary colorectal surgery is suboptimal, and that an adequate bone marrow analysis requires an aspirate with spicules, a core biopsy, and analysis of cytogenetics to provide adequate diagnostic and prognostic information. In all cases, a complete diagnostic evaluation prior to implementing any antineoplastic therapy is essential, because once treatment has been administered, the tissue will be altered and testing will not provide similar prognostic or predictive information.

Most tumor types require baseline diagnostic imaging. Because appropriate baseline imaging for each tumor type will vary, however, it is critical to understand the best approach to diagnosing each tumor type in order to adequately plan the diagnostic process and prepare the patient and family. For example, bone involvement is common in a patient with multiple myeloma; however, a bone scan is of limited diagnostic value. Similarly, whereas obtaining a PET/CT scan for staging a patient with follicular non-Hodgkin lymphoma (NHL) is not useful, it may provide diagnostic benefit in a patient with more aggressive diffuse large B-cell NHL.

Appropriate diagnostic imaging at baseline and at defined intervals can also provide the most accurate analysis of response to treatment, but the timing for evaluation varies for each tumor type. For example, a patient with Hodgkin lymphoma will typically have undergone a PET/CT scan after 2 months of treatment, and negative results from the scan in this setting are considered a positive predictor of long-term survival. A patient with follicular lymphoma, on the other hand, generally receives 3 to 4 months of treatment prior to undergoing repeat imaging, unless a physical exam and analysis of laboratory measures such as serum lactate dehydrogenase show no evidence of improvement. It should be noted that PET/CT evaluation is only recommended in selected cases of follicular lymphoma. Common approaches to diagnostic imaging are reviewed in Table 4.10-18

Scientific practicality is perhaps the most important component of precision medicine. This is a term I use to describe the application of clinical trials data to the population at large in a way that allows effective control of the disease for as long as possible with an acceptable level of toxicity. This concept is of particular importance in patients with metastatic or incurable disease. Many tumor types have limited treatment options. Perhaps the best example is the patient with metastatic colorectal cancer, with FDA-approved therapies limited to 6 agents; patients with mutated KRAS are limited to 4 FDA-approved therapies. Thus, each agent must be used to its fullest potential over the longest period of time.

The goals of therapy and the degree of flexibility with treatment must be adapted to the individual patient. For example, in the setting of metastatic disease, achieving stable disease is an acceptable outcome. In patients with potentially curable disease, however, a more aggressive approach to treatment is preferred, with application of the principles of precision medicine and an attempt to emulate the clinical trial protocol associated with the most favorable outcomes. Nevertheless, the patient’s tolerance of therapy must also be considered, including reversible versus potentially irreversible adverse events and the severity of symptoms despite optimal management.

Risk-adapted treatment selection for non–small cell lung cancer is illustrated in the Figure. This algorithm illustrates the variability in approach to treatment based on the application of principles of precision medicine. Similar algorithms and guidelines are available online through the National Cancer Institute, the National Comprehensive Cancer Network, the American Society of Clinical Oncology, and the American Society of Hematology. To remain effective as members of the oncology team, advanced practice clinicians in oncology and oncology nurses must maintain a current working knowledge of all of these concepts.


Figure. Application of Biomarkers in NSCLC


Made-to-Order Clinical Trials: The Way Forward

Predictive and prognostic indices and the notion of precision medicine have evolved as a result of ongoing clinical trials in oncology. The integration of functional imaging, sequential tissue analysis, and use of biomarker assays has developed as a result of these trials. The shift from a one-size-fits-all model of drug development, where a new agent is tested in a wide variety of tumor types to determine the maximum tolerated dose and sensitivity to individual diseases, is now being replaced by trials with a specific patient prototype in mind. These made-to-order clinical trials are designed based on a predetermined biomarker profile generated by laboratory disease models, with inclusion criteria specific to the biomarker and disease prototype.2

This approach will require a shift in the definition of clinical efficacy and clinical trial end points as well as development of new technologies to obtain these measures. Because these trials will be costly, with the potential benefit focused on only a small population of patients, it will be necessary to address hard questions, such as who will spend the time and money discovering, designing, and developing novel drugs for newly discovered targets. The current environment of skepticism toward pharmaceutical corporations, despite their significant contributions to clinical research in oncology and limited funding sources outside of these corporate entities, will make this new drug development process more difficult, particularly for orphan diseases.

Cancer Happens in Humans – Most Often the Older Adult

We must always remember that beyond the tissue diagnosis, diagnostic imaging results, and laboratory values, there is a patient with all of the unique characteristics of age, comorbidities, lifestyle, treatment goals, and available resources. These are what I consider the personalized aspects of oncology care. The goal of personalized medicine is to apply the principles of precision medicine in a way that provides the greatest benefit with the least amount of risk to the individual patient.

Consideration of the effect of comorbidities, the cost of treatment, self-care capabilities, available caregiver support, proximity to the clinical setting, and quality of life must be central to the treatment plan. The patients and their primary caregivers should be provided with adequate information to make an informed choice. As clinicians, we must find ways to educate ourselves and our patients about these complex concepts. Continued enrollment of patients in clinical trials that include tissue banking and biomarker assays will promote refinement of risk-adapted treatment selection based on predictive and prognostic indices.


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  17. National Comprehensive Cancer Network. NCCN Clinical Practice Guidelines in Oncology™: Non-Hodgkin’s Lymphomas. V.2.2012. Published February 23, 2012. Accessed March 16, 2012.
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