We have a fundamental responsibility as oncologists to deliver personalized care tailored to each individual. In addition to an unprecedented expansion of treatment options for patients, recent advances in molecular profiling and functional assessments have greatly improved our ability to predict risks, benefits, and outcomes for older patients with cancer., Molecular profiling identifies genomic abnormalities and allows oncologists to predict response to cancer therapy. Functional assessment such as a geriatric assessment allows oncologists to predict risks of treatment-related morbidity and mortality. Ongoing efforts aim to further refine our ability to predict outcomes for individuals by identifying relevant clinically meaningful thresholds (e.g., cut-off values for variant allele frequency, fitness criteria for a specific disease). Complex risk prediction models are now routinely used to integrate these data and produce personalized estimates of survival and response to cancer therapies, helping oncologists to provide personalized, high-quality care. Assessments of the disease and function of the patient, however, are insufficient to guide personalized treatment recommendations—we must understand patient preferences for treatment outcomes in order to tailor treatment.
Keywords: Clinical decision-making; Geriatric oncology; Patient outcome assessment; Patient preference; Patient-centered care.