Personalized psychiatry: many questions, fewer answers.

Clinical practice in many areas of medicine is shifting toward personalized treatment. In other words, clinicians aim to treat patients based on their individual characteristics, including clinical presentation and/or biological markers. Biomarkers can help clinicians select the most effective treatments or reduce the risk of side effects by avoiding certain treatments in susceptible patients. In addition, new treatments are being developed for specific patient populations based on better under standing of disease processes associated with identifiable markers. Advantages of an individualized approach are obvious — patients should receive treatments that are effect ive and better tolerated. And in theory, personalization of treatment should lead to lower health care costs. Medical spending continues to increase in most countries (more or less in parallel with increases in life expectancy). Personalization should optimize health care spending by selecting treatments that are effective and avoiding those that are unnecessary. Psychiatry is following the same trends, but its situation is seemingly more difficult. Psychiatric disorders represent a mix of diagnostic categories of variable validity and predict ive value. Practically all medications used to treat psychiatric disorders have been discovered in a nonsystematic, seren dipitous way or have been derived from existing prototypical drugs. Most psychiatric conditions are probably heterogen eous, which makes the search for biomarkers even more imperative, as practically no treatments are universally effective in patients whose conditions are diagnosed within broad and nonspecific categories. At present, we do not have any clin ic ally applicable biomarkers in a narrow sense (laboratory test), yet there exist clinical findings that might allow personalization of treatment in patients with certain psychiatric conditions. Clues to individualized treatments are hardly rec ognized in current treatment guidelines, which are often based on levels of evidence derived from clinical trials in undifferentiated patient samples. Arguably, in most areas of psych iatry, predictors of treatment response or side effects are simply unavailable. Studies have attempted to find such predictors; however, many of them were derived in studies designed for purposes other than response prediction and rely on variables that could be viewed as opportunistic. Never theless, there are examples of psychiatric treatments that can be selected rationally without resorting to a trial and error approach and that can make a great difference for patients, their families and society. So where in psychiatry can we do better than chance? There are some promising examples, but they seem to be lost in the vast sea of DSM 5 diagnostic categories. Disorders that offer the most promise with respect to effective treatment selection might be periodic catatonia, bipolar disorder responsive to lith ium and melancholic depression. These are also among conditions where treatment can make a substantial difference with respect to disability; on the other hand, benefits of treatments for cognitive (neurodegenerative) disorders or substance abuse are quite limited. So it is those relatively few selected treatments indicated in specific patient populations that can produce excellent results (if applied properly), but that can also be overlooked easily, perhaps for one of the following reasons.