Mechanisms of action of antidepressants and their combination for major depressive disorder treatment: a theoretical and clinical approach
Bibliographic record
Abstract
Background: Annually, an estimated 8.2% of Canadians aged 18 or older are affected by major depressive disorder (MDD). Nearly half of those suffering from MDD will fail to achieve remission while also having an inadequate response to an initial and continuous 6-week single antidepressant treatment. This failure to remit or respond to monotherapy, referred to as treatment-resistant depression (TRD), affects more than 30% of those suffering from MDD. The addition of a second antidepressant to improve upon the effects or alleviate the side-effects of the initial antidepressant has repeatedly shown encouraging therapeutic benefits. Unfortunately, the use of combination therapy in clinical settings has remained relatively low. Objective: With knowledge and understanding of the mechanisms of action of each of the seven different classes of antidepressants attained from preclinical studies (in vitro and in vivo electrophysiology) conducted at the Neurobiological Psychiatry Unit (NPU) at McGill University, the therapeutic efficacy of combination therapy can be maximized and adverse interactions and events minimized. The main goal of this thesis was to review the extensive literature concerning antidepressant studies conducted at the NPU as well as the clinical literature from PubMed and OvidSP in order to discern the most efficacious antidepressants and antidepressant combination treatments. The data collected from the literature was critically compared with the clinical database of the Mood Disorders Clinic (MDC) at the McGill University Health Centre (MUHC), in order to establish the clinical pertinence of using antidepressant combinations. Methods: A literature review was conducted to discern the most frequently prescribed antidepressants and efficacious antidepressant combination treatments. Subsequently, we analyzed the database of the MUHC; 133 outpatients with a current DSM-IV diagnosis of MDD aged 18 years or older were included in this study. Sociodemographic and clinical information of each patient was obtained during his or her initial diagnostic evaluation by a multidisciplinary team and chart review. Patients were also asked to complete a self-reported BDI-II questionnaire in order to assess the severity of depressive symptoms. Statistical analyses between prescribed antidepressant combinations and symptom severity were performed to determine effectiveness. A critical comparison of the findings from the literature with the clinical information obtained from patients referred to the MDC was conducted. Results: Significantly more women than men were diagnosed with MDD. Within the six months of their initial diagnostic evaluation, 87.2% of the patients had been prescribed an antidepressant. The most frequently prescribed antidepressant was a selective serotonin reuptake inhibitor (SSRI), followed by a serotonin-norepinephrine reuptake inhibitor (SNRI) and bupropion. Consistent with the literature, the most frequent antidepressant combination treatments were i) SSRI + bupropion, ii) SNRI + bupropion, and iii) SNRI + mirtazapine. No significant difference was found between antidepressant combination treatments and mean total BDI-II scores. Conclusions: Clinical findings were generally consistent with the literature. The literature supported the use of antidepressant combinations for effective and time-efficient treatment of MDD, particularly at the beginning of treatment, yet psychiatrists still appeared hesitant on using this approach. The combinations of bupropion with an SSRI or SNRI were found to be the most efficacious combinations, receiving frequent support in the literature and in this study. Limitations: Low completion rate of the BDI-II resulted in the powers of performed tests to be lower than the desired powers, thus reducing the likelihood of detecting a difference when one may have actually existed. A larger cohort of patients could allow for clinically meaningful differences to be observed.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".