These factors help define who might need treatment in general based on the likelihood of a worse outcome. The terms predictive and prognostic are synonyms. It’s important to understand these differences in biomarkers so that patients may derive the optimal benefit from more individualized therapy, Luke concludes. Prognostic factors in breast cancer are those that define the natural history or outcomes of the disease, either without therapy or with standard therapy 9. Conversely, in lung cancer, EGFR mutations predict better prognosis and suggest that a patient is likely to respond to an EGFR inhibitor. For example, in melanoma, BRAF mutations indicate poor prognosis but are also predictive of the treatment effect of a BRAF inhibitor, says Luke. Prognostic models are normally used to make the best possible choices for a patient or group of patients with regard to a specific clinical scenario. In some cases, biomarkers can be prognostic and predictive, Luke explains. Limited data exist regarding the feasibility of its application in the real-world setting. The concept of biomarkers is important in all areas of oncology, but is especially relevant in the field of melanoma, explains Luke. Prognostic biomarkers can indicate how well a patient is going to do over time, whereas predictive biomarkers are commonly linked to an available therapeutic approach, Luke says. e17594 Background: CA-125 ELIMination Rate Constant K (KELIM) is considered a marker of chemosensitivity in ovarian cancer patients and its prognostic and predictive significance in Neo-adjuvant Chemotherapy (NACT) treated patients has been established through prospective trials. ![]() Luke, MD, FACP, an associate professor of medicine in the Division of Hematology/Oncology and director of the Cancer Immunotherapeutics Center Immunology and Immunotherapy Program at the University of Pittsburgh Medical Center Hillman Cancer Center, compares predictive and prognostic biomarkers in melanoma.
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