Comparative Effectiveness of Pharmacogenomics for Treatment of Depression — CEPIO-D  

Major Depressive Disorder Clinical Trial

Official title: Comparative Effectiveness of Pharmacogenomics for Treatment of Depression

Status Completed

Clinical Trial Summary

The overall goal of this study is to assess the effectiveness of a widely available and widely used combinatorial pharmacogenomic (PGx) test for the treatment of major depressive disorder. Pharmacogenomic tests use genetic information to guide medication treatment decisions. The tests inform clinicians and patients of potential gene-drug interactions by analyzing pharmacokinetic (PK) genes (how drugs are metabolized) as well as pharmacodynamic (PD) genes (how drugs work). While combinatorial PGx testing is attractive to clinicians, patients, healthcare systems, and insurers, limited data demonstrate that PGx testing will result in better outcomes compared to evidence-based guideline treatment. Therefore, the investigators will conduct a prospective randomized comparative effectiveness study of best practice guidelines plus combinatorial PGx-guided treatment versus best-practice guideline concordant treatment alone.

Clinical Trial Description

Depressive disorders are the fourth leading cause of the burden of disease worldwide and is projected to be the first cause by 2030 1. According to the World Health Organization depression carries the greatest burden of disability among all mental and behavioral disorders. Specifically, depression accounts for 3.7% of all U.S. disability-adjusted life years and 8.3% of all U.S. years lived with disability. In 2014, it was estimated that 15.7 million adults in the United States had at least one major depressive episode in the past year and 43% people with severe depressive symptoms reported serious difficulties in work, home, and social activities 2. The current standard of care is based on trial-and-error of a multitude of medications; this approach often leads to patient and clinician frustration after each treatment failure (side effects or non-response) and can decrease compliance and engagement in treatment. One way to reduce this trial-and-error process, is to use pharmacogenomic (PGx) testing to guide medication treatment and increase the likelihood of response by reducing the number of ineffective medication trials. Pharmacogenomics, the use of genetic information by patients, clinicians, and healthcare systems to match patients with pharmacologic treatments, is an important step towards precision/personalized medicine. Pharmacogenomics can make the practice of medicine more efficient by giving the right medications specifically to those who are most likely to benefit from them and to avoid giving the wrong medications to those who are most likely not to benefit based on each patient's individual genetic makeup. The PGx test for the treatment of depression is now commercially available and is reimbursable by insurance, including Medicaid and Medicare. A recent comprehensive overview of the state of PGx testing for depression, its promise, and limitations concluded that more research is needed in this rapidly-developing field3. Specifically, the gap is that while PGx-guided antidepressant treatment results in better outcomes compared to treatment as usual in tightly controlled clinical trials, it has not yet been tested in real world settings, nor has it been compared to best practice guidelines. It is less clear how well PGx tests make a difference in short and long-term patient-centered outcomes compared to guideline-concordant care of depression. For this study, the investigators are collaborating with Assurex Health and their product GeneSight® Psychotropic powered by CPGx® technology, the only test for depression reimbursable by Medicaid and Medicare. GeneSight® is a neuropsychiatric, combinatorial, PGx test that provides recommendations for psychotropic medications (antidepressants, mood stabilizers, hypnotics for insomnia, and antipsychotics) based on a patient's individual genetic profile. The test combines pharmacokinetic (PK) metabolism genes (how drugs are metabolized) as well as pharmacodynamic (PD) genes (how drugs work) to predict dosing adjustments and response. GeneSight® classifies medications based on the severity of the gene-drug interactions in color-coded categories: green "use as directed," yellow "moderate gene-drug interaction," and red "significant gene-drug interaction." The results are presented in a report which is easily understandable by patients and clinicians. Furthermore, GeneSight® addresses concerns reported by individuals in MoodNetwork: alleviating symptoms, identifying effective alternative treatments, reducing barriers to care/treatment, and using genetic studies to identify responders to treatment. This study answers questions that patients and clinicians care about and has the potential to improve outcomes. Cogito, Inc. is the industry leader in the mobile sensing technology of mood. Cogito has developed a mobile phone application that assesses depression by tracking everyday usage of mobile phones, without the need to actively input data (e.g., rating depression). The application uses indicators such as phone call/text frequency or voice parameters to deduce depression severity. To date, this application has been tested in two studies: Defense Advanced Research Projects Agency (DARPA) funded a study in 73 patients with major depression and PTSD3, and a more recent NIMH funded study with 200 patients with major depression and bipolar disorder in collaboration with the MoodNetwork PPRN. The application is highly sensitive and specific in detecting depression. However, given the preliminary nature of these findings, the study investigators will use the Cogito platform as a secondary (more exploratory) outcome measure and the use of this application will be optional. The use of passive sensing technology has the advantage that it does not rely on patients' self-report and can be used for low cost longitudinal monitoring of patients for the changes in depression symptoms. If a study clinician meets with one of their patients and determines that they may be eligible for the study, a member of the study staff (i.e. site PI, treating clinician, or research assistant) will describe the study to the patient and answer any questions. If the participant is interested, they will complete the consent form accessed via MoodNetwork.org. Patients will be offered to take home the Consent Form and call back if they wish to participate. If they decide to participate, they will contact the member of the research team and will be given the study website link to sign consent. Following their consent, participants will be prompted to complete questionnaires to determine study eligibility on MoodNetwork.org. If the patient is eligible for the study, they will be informed of the option to use the Cogito Companion mobile app and if they want to use it, they will be asked to download the mobile app (so that the study team can passively monitor any potential depressive symptoms throughout the course of the study) and they will be randomized to either the PGx-guided psychiatric treatment arm or the best practice guidelines arm. A member of study staff will then administer the PGx test (i.e., a buccal swab). If the participant is in the PGx-guided psychiatric treatment arm, the treating clinician will receive their results within two business days and contact the participant to inform them of the results and discuss any medication changes. If the participant is in the best practice guidelines arm, the treating clinician will not receive the PGx test results until after the follow-up phase (one year). The clinician, however, will still contact the patient to discuss medication changes (in line with the Canadian Network for Mood and Anxiety Treatments (CANMAT) guidelines instead of the GeneSite test results). ;

Related Conditions & MeSH terms

• Depression
• Depressive Disorder
• Depressive Disorder, Major
• Major Depressive Disorder

• NCT number: NCT03749629
• Study type: Interventional
• Source: Massachusetts General Hospital
• Status: Completed
• Phase: N/A
• Start date: May 1, 2019
• Completion date: March 15, 2022