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Personalized medicine is a new mantra evolving in health care. Harnessing each person's clinical, genetic, genomic, and environmental information drives the concept. The idea is simple. We can maximize a patient's chances of a better outcome if we base treatments on what we know. However, isn't this in many ways the way it's always been? Isn't this in part the basis for that old-time house call? To see how a disease or condition is being cared for in the home environment? Clinicians have long used personalized medicine, without overt use of single nucleotide polymorphisms, but certainly not totally void of genetic information. Of course, physicians of the past did not have gene chips, but they did have family histories often informing their decisions. Today as we raise the hopes for targeted therapies to break us free from the algorithmic treatments often followed by hit and miss approaches, there is a renewed fervor for personalized medicine. How do we get there and how does the average clinician or researcher understand the burgeoning array of information, talking heads, and latest hype of subgroup benefits? A key aspect is to trust your training, your experience, and your instincts, coupled with a few repeated doses of biostatistics.
Cutter et al. (Sat,) studied this question.