Personalized Medicine vs Guideline-Based Medicine

TWO PHILOSOPHICAL APPROACHES TO THE IMPLEMENtation of optimal health care are emerging—the use of evidence-based guidelines and the application of personalized (or “precision”) medicine. Even though both approaches have important merits, they both also can present conflicting priorities that must be reconciled before they can be best leveraged. Evidence-based guidelines are generated based on the body of clinical data available for a particular question. The highest level of evidence assigned in a guideline is based on multiple randomized controlled clinical trials. In general, randomized clinical trials have specific inclusion and exclusion criteria designedtorepresentapopulationbroadenoughandsufficiently enriched to attain a requisite number of end points and demonstrateastatisticallyandclinicallysignificantdifferenceinoutcome.Subgroupanalyses (both those thatareprespecifiedand other post hoc analyses) are often performed to identify characteristicswithin thestudypopulation thatareassociatedwith greater benefit from the intervention, with no benefit, or even withharm.Yettheseanalysesareaccompaniedbywarningsthat findings should be cautiously interpreted. Indeed, there is well-deserved skepticism regarding the utility and accuracy of subgroup analysis from clinical trials, and these analyses are therefore generally not used in the formulation of guidelines. Patients (including those enrolled in trials) have multiple characteristics, each of which may influence the behavior and significance of other characteristics. Analysis of a subgroup showing that a single characteristic influences outcome is of limited clinical significance unless multiple variables that may modify the importance of the single variable are considered. However, if well-conducted analyses from multiple sources demonstrate concordant findings, perhaps these subgroup analyses should be considered when guidelines are constructed and revised, given the impracticality of performing randomized clinical trials to answer the question of appropriateness for every possible subgroup. In the end, “the guidelines” are usually established based on the inclusion criteria for the trial. The applicability of the guidelinesmaybequestioned,orevensuspect,whenindividual patients within the heterogeneous population to which the guidelines areapplied inclinicalpracticediffer incertaincritical characteristics from those of the trial population on which the guideline recommendation is based. That is, the generalizabilityof trial results toclinicalpracticemaybecompromised by a number of factors involved in execution of the trial, such as where patients were recruited (eg, inpatient vs outpatient venue, tertiary referral centers vs primary care centers). The President’s Council of Advisors on Science and Technology noted that personalized medicine “refers to the tailoring of medical treatment to the individual characteristics of each patient. It does not literally mean the creation of drugs or medical devices that are unique to a patient, but rather the ability to classify individuals into subpopulations that differ in their susceptibility to a particular disease or their response to a specific treatment. Preventive or therapeutic interventions can then be concentrated on those who will benefit, sparing expense and side effects for those who will not.” Although the increasing attention directed to personalized medicine has largely focused on the interaction of an individual’s genome with specific treatments, any individual characteristics that affect treatment outcomes may be relevant to clinical decision making. If certain subpopulations within the total cohort of a clinical trial were considered unlikely to benefit from the intervention— based, for example, on actual subgroup analysis—this hypothesis would need to be tested prospectively in a separate clinical trial to achieve a sufficient level of evidence about the value of the intervention in this patient subpopulation. Although it is possible to make a case for equipoise in such a situation, once the guidelines include this subpopulation in the general group in which the intervention is recommended based on the results (or entry criteria) of clinical trials, it is difficult to overcome the multidimensional resistance to actually testing “not providing the intervention” when the guidelines recommend otherwise. Thus, the development of evidence-based guidelines based on a relatively broad set of enrollment criteria inhibits the subsequent development of personalized medicine within this “enrollment criteria” space.