Psychiatry and Clinical Psychopharmacology

Personalized treatment for depression

Psychiatry and Clinical Psychopharmacology 2014; 24: Supplement S25-S26
Read: 697 Published: 18 February 2021

The response ratio for the drug treatment of depression is between 30-50%. In the first line treatment of depression, different antidepressants have similar efficacy in moderate depression, to that of antidepressant medication combined with specific psychotherapies. In order to provide personalized treatment for depression, it must be identified characteristics of individual. The principle of “There is not illness, there is patient” that it has been emerged before almost one hundred years, has been formed the basis of personalized treatment. Numerous factors affect the response to drug treatment and to psychotherapy. In the previous studies, these factors have been evaluated according to outcomes of treatment as retrospectively. In these times, it is accepted that the success of treatment depends on personalized treatment. The evidences are necessary for this application. The better and more specific interventions are known as personalized medicine. In psychiatry, this approach includes the predictors of treatment response such as biological, genetic, behavioral, experiential, clinical, and environmental factors. The aims of personalized treatment are to select the most appropriate drug for depression, to arrange therapeutic doses, to identify treatment efficacy, to predict side effects and drug interactions. The predictors for personalized treatment could not yet be identified. The studies on this issue may review as follows: 1. Individual predictors: age, gender, genetic characteristics, metabolic rate (phenotype), personality structure, stressful or traumatic life events, patient treatment preference, family history of treatment response, adherence. 2. Clinical predictors: the subtypes of depression, clinical symptoms, comorbid illnesses, response of past treatment. 3. The characteristics of antidepressant: the pharmacodynamics and pharmacokinetic characteristics of antidepressant, mechanism of action, side effects, drug interactions. 4. The type of psychotherapy: interpersonal or cognitive therapy, relationship with the other features. 5. Biochemical and neuroendocrine predictors: neurotransmitter production or metabolism, receptor polymorphism, hypothalamic-pituitary-adrenal axis measures, urinary 3-methoxy-4-hydroxyphenylglycol, serotonergic measures in serum/platelets, dexamethasone-corticotropin releasing hormone tests, 6. Inşammatory predictors: cytokines, tumor necrosis factor-alpha, interleukin (IL)-1-beta, and IL-6, C-reactive protein, 7. Neuroimaging and physiological predictors: auditory evoked potentials, quantitative EEG, PET and fMRI studies, 8. Predictors of molecular genetics: Genetic factors affect the variation of response to drug treatment; they contribute for about 50% of side effects. Pharmacogenomics use the data emerged from the human genome to identify new targets for treatment and to predict drug responses. The elucidation of gene-environment interactions may help to understand the pathophysiology of depression and may provide predictors for a personalized depression treatment. The studies regarding these probable predictors have not satisfactory results. The causes: 1. For personalized treatment, it may be necessary the larger sample than in traditional clinical trials. 2. To identify person-level predictors of treatment response may need to consider response across multiple episodes of depression. 3. To predict response to specific treatments may require combinations of several weak predictors rather than a single powerful one. Replication is the first step in translating research findings to clinical tests or predictors. Even after replication, while use them must be careful. There is necessity numerous and various studies for personalized treatment for depression. When the predictors are identify, it will provide early diagnosis, more efficient treatment, less side effects, the shorter illness duration, higher remission rate.

EISSN 2475-0581