Antidepressant class and concurrent rTMS outcomes in major depressive disorder: a systematic review and meta-analysis
Bibliographic record
Abstract
Background Repetitive transcranial magnetic stimulation (rTMS) is frequently used as an adjunctive treatment with antidepressants for depression. We aimed to evaluate the clinical efficacy and safety of antidepressant classes when administered concurrently with rTMS for the management of major depressive disorder (MDD). Methods In this systematic review and meta-analysis, MEDLINE, Embase, PsycINFO, and the Cochrane Library were searched from inception to April 12th 2024 for terms relating to medication, depression, and rTMS and appraised by 2 independent screeners. All randomized clinical trials that prospectively evaluated a specific antidepressant adjunctively with sham rTMS as a control in MDD were included. The study was registered with PROSPERO (CRD42023418435). The primary outcome measure assessed symptomatic improvement measured by formal depression scales. We used a random-effects model with pooled Standardized Mean Differences (SMDs) and log odds ratios (OR). All studies were assessed for their methodological quality and bias using the Cochrane Collaboration Risk of Bias tool version 2 (RoB2). Findings 14 articles from 5376 identified studies were included in the systematic review and meta-analysis. There was only sufficient trial data to evaluate the effects of rTMS and combination therapy with selective serotonin reuptake inhibitors (SSRIs) and serotonin norepinephrine reuptake inhibitors (SNRIs). Across studies, 848 participants (mean [SD] age:41.1 [18.7] years for SSRIs, 51.8 [3.8] years for SNRIs) prospectively examined the efficacy of antidepressant medication with rTMS. Combining rTMS with SSRIs led to significantly lower depression scores, (SMD [CI] of −0.65 [−0.98, −0.31], p = 0.0002, I 2 = 66.1%), higher response (OR = 0.97 [0.50, 1.44], p < 0.0001, I 2 = 25.33%) and remission rates (OR = 1.04 [0.55, 1.52], p < 0.0001, I 2 = 0.00%) than medication with sham rTMS. No additive benefit was found for SNRIs with rTMS (SMD of 0.10 [−0.14, 0.34], p = 0.42, I 2 = 0.00%; OR = 0.12 [−0.39, 0.62], p = 0.64, I 2 = 0.00%; OR = −0.31 [−0.90, 0.28], p = 0.86, I 2 = 39.9%). The overall risk of bias for the included studies ranged from low to high, with 1 study having a high risk of bias. Interpretation The combination of rTMS with SSRIs, but not SNRIs, significantly reduced depression severity, increasing response and remission rates. Some analyses demonstrated high heterogeneity, which was influenced by an SSRI trial with a high effect size. Overall, these results suggest that not all antidepressant combination therapies are alike, and SSRIs should be considered when initiating rTMS. Funding Donald T. Stuss Young Investigator Research Innovation Award from the Sandra Black Centre for Brain Resilience & Recovery and the Harquail Centre for Neuromodulation through the Sunnybrook Foundation.
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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 | 0.012 | 0.027 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.021 | 0.040 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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".