| dc.description.abstract | Major depressive disorder (MDD) is a major psychiatric illness and it is predicted to be the second leading cause of disability by 2020 with a lifetime prevalence of about 13%. Selective serotonin reuptake inhibitors (SSRIs) are the most commonly used therapeutic class for MDD. However, response to SSRI treatment varies considerably between patients. Biomarkers of treatment response may enable clinicians to target the appropriate drug for each patient. Biomarkers need to have accuracy in real life, sensitivity, specificity, and relevance to depression. Introduction of MDD biomarkers into the health care system can increase the overall cost of clinical diagnosis of patients. Because of that, decisions to allocate health research funding must be based on drug effectiveness and cost-effectiveness. The assessment of MDD biomarkers should include reliable evidence of associated drug effectiveness, adverse events and consequences (reduced productivity and quality of life, disability) and effectiveness of alternative approaches, other drug classes or behavioral or alternative therapies. In addition, all the variables included in an economic model (probabilities, outcomes, and costs) should be based on reliable evidence gained from the literatureideally meta-analysesand the evidence should also be determined by informed and specific expert opinion. Early assessment can guide decisions about whether or not to continue test development, and ideally to optimize the process. Drug Dev Res 77 : 374-378, 2016. | en |
