Deep brain stimulation for major depressive disorder: A Systematic Review and Meta-Analysis

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Deep brain stimulation (DBS) is a surgical intervention under investigation for TRD which has shown promise in some settings but inconsistent outcomes overall. We conducted a random-effects meta-analysis of open-label and randomized controlled trials to provide an up-to-date assessment of DBS efficacy in TRD. Depressive symptoms improved across short-term (6–9 months), moderate-term (12–24 months), and long-term (>24 months) time points after DBS initiation, with effect sizes (Hedges’ g) of 2.40, 2.83, and 4.33, respectively. Neither study design nor stimulation target significantly influenced outcomes, although subcallosal cingulate stimulation was generally associated with more pronounced effects. Furthermore, higher follow-up frequency correlated positively with rate of symptom improvement. Our findings support that DBS can exert sustained antidepressant effects, and provide insights that can be used to better establish its efficacy vs. placebo and optimize its clinical implementation. Biological sciences/Neuroscience/Cognitive neuroscience Biological sciences/Neuroscience/Emotion Health sciences/Diseases/Psychiatric disorders/Depression Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Introduction Major depressive disorder (MDD) affects approximately 350 million people worldwide, with a lifetime prevalence of 5–20% 1 . First-line treatments for MDD typically include pharmacotherapy - such as selective serotonin reuptake inhibitors (SSRIs) and selective norepinephrine reuptake inhibitors (SNRIs) - alongside psychotherapeutic approaches such as cognitive behavioral therapy (CBT) and interpersonal therapy (IPT) 2,3 . However, approximately 30% of individuals will not respond to these treatments and are classified as having treatment resistant depression (TRD) 4 . Neuromodulation is a promising treatment approach for various treatment-resistant psychiatric disorders 5 , ranging from incisionless procedures such as ECT, repetitive transcranial magnetic stimulation (rTMS), ketamine, and focused ultrasound lesioning, to more invasive procedures such as deep brain stimulation (DBS), which modulate dysfunctional brain circuits via surgically implanted electrodes 6,7 . DBS is FDA approved for use in Parkinson’s disease and essential tremor, and has received a humanitarian device exception for use in obsessive compulsive disorder 8,9 . Its success in these conditions has sparked notable interest in its potential application in TRD 10 . Multiple brain regions implicated in the pathophysiology of TRD have been investigated as targets for DBS, including the subcallosal cingulate cortex (SCC), ventral capsule/ventral striatum (Vc/Vs), bed nucleus of the stria terminalis (BNST), and superolateral branch of the medial forebrain bundle (slMFB) 11-17 . To date, results from randomized controlled trials (RCTs) have been mixed, particularly during the blinded sham-controlled phases. The first randomized controlled trial (RCT), published in 2015, found no difference between active and sham Vc/Vs stimulation after 16 weeks 15 and similarly, a RCT evaluating SCC DBS failed to differentiate between active and sham stimulation at 6-months 12 . Notably, both studies demonstrated response rates close to 25% and 50%, respectively, at 2-year follow-up, suggesting that inadequate treatment duration may have contributed to early null findings. Open-label studies investigating outcomes at greater than 2 years have demonstrated robust positive effects further supporting that DBS outcomes tend to improve over time 13,16,18-21 . Emerging evidence suggests individual predictors of response to DBS such as; shorter duration of illness/fewer failed mediation trials, higher emotional reactivity, early clinical response, and a lack of substance-abuse comorbidity have been linked with improved response to DBS 14,20,22-25 . Preoperative structural imaging studies have found that responders to DBS had larger SCC, thalamus and amygdala volumes compared to non-responders 26 . Further, integrity of the white matter tracts connected to the SCC, such as the uncinate fasciculus have been associated with better response rates to DBS 11 . Finally, millimetric deviations in electrode placement may influence the constellation of tracts modulated, and ultimately, the extent of clinical response 24 . Together, these findings suggest that a combination of clinical, structural, and connectivity-based characteristics may help identify patients most likely to benefit from DBS 26,27 . Four prior meta-analyses have examined the effects of DBS on TRD, demonstrating promising pooled remission rates with larger treatment effects among open-label trials compared to RCTs 28-31 . Most recently, a 2024 meta-analysis reviewed 15 studies encompassing 275 participants, each with a minimum follow-up of one year. The study reported a 47% improvement in depressive symptoms from baseline to last follow up, with an average of 23 months required to achieve a 50% reduction in depression severity 31 . This meta-analysis builds on this foundation by including a larger and more temporally nuanced dataset, comprising 24 studies and 429 participants. We report outcomes at short-term (6-9 months), moderate-term (12-24 months) and long-term (>24 months) time-points, offering a comprehensive view of DBS efficacy over time. Beyond examining the influence of stimulation target and study design, we introduce a novel exploratory analysis assessing the impact of follow-up frequency on overall depression scores and the rate of symptom improvement. The findings from this study provide critical insights that can inform the design of future studies on DBS for depression and may help guide clinical strategies for optimizing DBS treatment in TRD. Methods Data Sources and Search This study was preregistered in PROSPERO (CRD42024577570). Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines 32 , MEDLINE and Embase databases were searched on July 24 2024 using the MeSH terms “Deep brain stimulation”, and “Major Depressive Disorder” and a comprehensive list of search terms (Supp. Fig.1). Databases were monitored for new eligible studies until June 30 2025. Peer-reviewed studies on human subjects, published in English-language journals beginning in2005 (the first published series of DBS for TRD) were eligible. PICO criteria selection were as follows: population: adults with TRD; intervention: DBS to any intracranial target; comparison: pre-treatment depression scores; outcomes: Hamilton depression rating scale (HAMD) and the Montgomery-Asberg Depression Rating Scale (MADRS) with at least 6 months follow-up. Data Extraction and Quality Assessment Two independent reviewers (JE and FM) used Covidence 33 to independently screen study titles and abstracts, and then full-text, with any conflicts resolved by a third reviewer (BD). To ensure the integrity of the dataset, all full-texts were reviewed in detail, and clinical trial registration numbers were cross-referenced to verify that multiple publications did not originate from the same participant cohort. Data were extracted by two independent reviewers (FM & BD) and were cross-checked by two additional independent reviewers (AA & MP) using Excel. The extracted data from each study included study design, target, sample size, participant demographics, depression scores (MADRS, HAMD-17) at baseline and all available follow-up time points, response and remission rates, Hamilton Anxiety Rating Scale (HAM-A), quality of life measures, global assessment of functioning (GAF), DBS stimulation parameters, and adverse events. HAMD-17 scores were converted to MADRS scores using the conversion method described by Leucht et al. (2018) 34 . Additionally, the two studies that reported percentage change scores were standardized to mean MADRS scores from baseline mean scores. All included studies defined response as a ≥50% reduction in depression scores. Definitions of remission varied slightly across studies: ten studies used HAMD-17 ≤7 11,18-21,35-39 , one used HAMD-24 ≤10 40 , one used HAMD-28 ≤10 16 , five used MADRS ≤10 12,15,41-43 , one study defined remission as MADRS ≤8 44 , one study did not define remission scores 45 , and four studies did not assess remission 13,14,17,46,47 . Given the variability in follow-up durations across studies, we included all reported time points ≥6-months and categorized them into short-term (6-9 months), moderate-term (12-months to 24-months), long-term (>24-months), and last follow-up (LFU) time-point clusters. When multiple time-points within a cluster were reported (i.e. both 6 and 9-months short-term data), the later time point was used. For studies that reported results in graphs, we extracted values from figures using Automeris.io (http://automeris.io/). For studies that included a randomized ON/OFF period of sham versus active stimulation for 6-months or greater, data from the sham group were only included once they transitioned into active stimulation. For example, if a study included 6-months of active versus sham stimulation, 12-month time-point data was labelled as 6-months for the sham group, and 12-months for the active group 12 . Assessment of Risk of Bias The Cochrane Risk of Bias in Non-Randomized Studies (ROBINS-I) tool 48 was used to evaluate the bias (Supplemental Table S2) by two independent reviewers (FM & AA), with conflicts resolved by a third (BD). Visual and statistical assessment of publication bias was performed using funnel plots with Egger’s test. Statistical Analysis Statistical analyses were conducted in RStudio (v4.4.3) using the metafor, metaviz, and dplyr packages. Random-effects meta-analyses were used to estimate effect sizes and account for between-study heterogeneity. For MADRS outcomes, Hedges’ g was calculated as the difference between baseline and follow-up scores (baseline minus follow-up), with positive values indicating improvement. Meta-regressions were performed across all time-point clusters using DBS stimulation target and study design as moderators. Heterogeneity was assessed using the I² statistic, between-study variance with τ² , and the proportion of variance explained by moderators with R². Statistical significance was set at p<0.05. Means were reported alongside standard deviations. A leave-one-out sensitivity analysis was performed across all timepoints to identify influential studies. Secondary analyses of anxiety symptoms and global functioning were performed. As an exploratory assessment of the relationship between follow-up frequency and clinical improvement, we conducted both linear regression and Spearman correlation analyses using GraphPad-Prism 10. Follow-up visit frequency was extracted from each study and used to calculate a visit rate over a standardized 6–24 month period, excluding two studies with exceptionally long follow-up durations to minimize skew. The corresponding MADRS score reported at the same follow-up time point was used as the outcome measure. These variables were then plotted and analyzed to explore potential associations. Results Study Selection The search yielded 2472 articles across both databases and after duplicates and pre-2005 studies were removed, 1782 articles remained for screening. 24 studies met final inclusion , consisting of 7 RCT’s 12,15,21,38,40,42,47 and 17 open-label studies 8,11,13,16-18,20,35-37,39,41,43-46 . Participants A total of 429 unique adult participants with a mean age of 46.90 years (SD=9.18) were included. The mean age at disease onset was 26.96 years (SD=8.62), and 51% of the participants were female. Participants had moderate depression at baseline (MADRS score of 33.55 (SD=4.35)). The average sample size across studies was 16.5 participants (range: 4 to 90), with a mean follow-up duration of 30.93 months (SD=36.61). Stimulation target and outcome measures The most common targets for DBS stimulation included the SCC (11 studies, n=224), Vc/Vs (5 studies, n=91), slMFB (3 studies, n=33), and BNST (1 study, n=5). Four studies (n=41) compared effects of stimulation on multiple targets 21,37,39,44 . All included studies reported either MADRS (n=13) or HAMD-17 (n=11) scores (see Figure 2 for MADRS/MADRS-converted scores in all studies). 19 studies (n=243) reported short-term results. MADRS scores improved by 41.7% +/- 16.5, with a significant and large effect size (Hedges’ g = 2.40, p<0.01, 95% CI: 1.80–3.00). Heterogeneity was high (I²=83.89%, Q(df=18)=98.09, p<0.01), indicating substantial variability in effect sizes (H²=6.21, τ²=1.36). Leave-one-out sensitivity analysis revealed that no single study contributed significantly to the overall heterogeneity and did not influence the pooled effect size (range: 2.24-2.50) ( I²= 79.3% to 85.2%). A moderate follow-up timepoint was reported by 19 studies (n=329). MADRS scores improved 48.04% +/- 13.72%, with a large effect size (Hedges’ g =2.83, p<0.01, 95% CI, 2.04, 3.61). Heterogeneity was significant (I²=92.33%, Q (df=18)=166.78, p < 0.01), indicating substantial variability in effect sizes (Tau²=2.71, H²=13.04). Leave-one-out sensitivity analysis revealed that no individual study contributed significantly to the overall heterogeneity (I²=85.99% to 92.99%) and did not influence the overall effect size (range: 2.53-2.95) Long-term follow-up data ranged from 3 to 7 years and consisted of 88 participants across five studies. MADRS scores at long-term follow-up improved 64.11% +/-15.58% compared to baseline. Analysis of these studies revealed a significant positive effect (Hedges' g =4.33, p=0.01, 95% CI: 1.76-6.89). Heterogeneity was significant (I²=96.38%, Q(df=4)=53.15, p < 0.01), indicating substantial variability between studies (H²=27.60, τ²=7.98). The leave-one-out sensitivity analysis revealed no single study significantly contributed to the overall heterogeneity (Hedges’ g =3.12-5.05; I²=88.1% to 97.6%). The LFU time point was analyzed for all 24 studies (n=393), revealing a 50.38% +/- 15.98 improvement in MADRS scores. The average duration of follow-up at LFU was 22.5 months. Meta-analysis revealed a large and statistically significant effect of DBS on MADRS scores (Hedges’ g =2.88, p<0.01, 95% CI, 2.16 to 3.60). Heterogeneity was high (I²=92.56%, Q(df=25)=188.22, p50% reduction in HAMD17/MADRS) was 53.36%. The mean remission rate at LFU was 41.5% (reported in 21 studies). Leave-one-out sensitivity analysis revealed that no individual study contributed significantly to the overall heterogeneity (I²=88.83% to 93.08%) or influenced pooled effect sizes (range: 2.65-2.97) Target Site DBS target did not significantly influence outcomes at short-term, moderate-term, long-term, and LFU respectively (QM(df=5)=2.49, p= 0.78; QM(df=5)=2.67, p=0.75; QM(df=2)=1.30, p=0.52 ; QM(df=7)=2.19, p=0.95). Residual heterogeneity remained high across time-points ( I²>87%), with target site accounting for 0% of the variability across short, moderate and LFU and 6.26% of the observed variability at long-term follow-up. Pooled effects for each stimulation target, revealed strong effect sizes across all targets at all time-points. The SCC demonstrated the most robust effects across all time-points (Short-term Hedges’ g =2.82, 95% CI: 1.82-3.81; Moderate-term: Hedges’ g =3.59, 95% CI: 2.10-5.09; Long-term: Hedges’ g =5.68, 95% CI: 1.92-9.45; LFU: Hedges’ g =3.55, 95% CI: 2.10-4.99). Study Design Study design (RCT vs. open-label) was not a significant moderator of effect size at any time-point (short-term: QM(df=1)=0.01, p=0.91; moderate-term: QM(df=1)=0.03, p=0.86, long-term: (QM(df=1)=0.13, p=0.71), LFU: (QM(df=1)=0.09, p=0.76. Heterogeneity was high across time-points (I²>83.77%), with 0% variance explained by study design at short-, moderate-, long-term follow up and LFU. There was no significant difference in the proportion of RCT’s and open-label studies representing each target site (p=0.96, Fisher’s exact test). Baseline Depression Severity Baseline heterogeneity was assessed by comparing average baseline MADRS scores across stimulation targets (SCC, Vc/Vs, MFB) and study designs (RCTs vs. open-label) (Figure 5; Supplemental Figures A2.A–B). No significant differences were observed, suggesting that initial depression severity and episode duration are unlikely to confound outcomes. (Supplemental Figure A1). Secondary outcome measures GAF scores at the short-term timepoint were available from 5 studies (n=129), demonstrating a 30.96% ± 3.01% improvement from baseline. The overall effect size was very large (Hedges’ g =1.98, 95% CI: 1.17 to 2.80, p < 0.01). At the moderate-term follow-up, data from 6 studies (n=124) showed a 44.27% ± 3.06% improvement (Hedges’ g =2.22, 95% CI: 1.53 to 2.90, p<0.01). GAF scores at long-term follow-up were available for 8 studies (n=162), demonstrating a 43.03% ± 3.59% improvement from baseline (Hedges’ g =1.94, 95% CI: 1.44 to 2.43, p66%) HAM-A scores were available for 7 studies (n=77). The overall effect size at LFU was significant (Hedges’ g =1.58, 95% CI: 1.22 to 1.93, p < 0.01). Heterogeneity was not significant (Q=3.78, p=0.81), indicating similar effect sizes between studies. Frequency of Follow-Up Visits and MADRS Score We examined whether the frequency of follow-up visits after DBS was associated with clinical improvement. Follow-up rate (visits per month) was plotted against percent reduction in MADRS score at each timepoint (Figure 6A). Follow-up visits included all documented clinical encounters, including those involving stimulation adjustments. Linear regression revealed no significant relationship between follow-up rate and MADRS reduction (R²=0.12, p =0.14), and Spearman correlation similarly showed no significant association (ρ=0.24, p =0.32). To assess not just how much patients improved but how quickly they improved, we also examined the relationship between follow-up rate and the rate of MADRS score improvement (i.e., percent reduction per month; Figure 6B). In this analysis, linear regression showed a significant positive association (R²=0.28, p =0.02), and Spearman correlation confirmed a similar result (p=0.50, p =0.03). These findings suggest that more frequent follow-up is associated with faster symptom improvement over time, though not necessarily with greater overall improvement at any given time-point. Assessment of Bias A moderate risk of bias was found in 67% of studies due primarily to concerns related to confounding, missing data, measurement of outcomes, and selection of reported results (Table S2). A low risk of bias was found in 29% of studies, with a general low concern for bias with respect to selection of participants, classification of interventions, and deviations from intended interventions. Serious risk of bias was identified across 6 of 7 domains in one open-label study evaluating VC/VS stimulation. RCTs accounted for 3 of 7 low-risk studies and were not more likely than open-label studies to have low overall RoB (p=0.37, Fisher’s exact test). A funnel-plot and Egger’s test revealed significant asymmetry (z=2.91, p<0.01) and a limit estimate of (b=0.35, CI: -1.42 to 2.12), suggesting that smaller studies with non-significant results may be underrepresented in the analysis (Figure 7). Discussion This meta-analysis provides an uptodate evaluation of the available evidence for DBS in the treatment of TRD. Our analysis revealed very large and significant effect sizes at all timepoints, with the greatest effect at long-term follow-up (Hedges’ g =). This is consistent with the overall trend in previously published cohort studies and meta-analyses, which show gradual symptom improvement over years across study types and stimulation targets 28-31 . While previous meta-analyses have primarily explored outcomes at single time-points, this study provides a temporal perspective by demonstrating that the antidepressant effect of DBS is maintained from short to long-term time-points. The present meta-analysis includes the longest pooled follow-up data on depression outcomes after DBS to date. These sustained effects are particularly noteworthy given the high relapse rates associated with other treatments for TRD, including electroconvulsive therapy (ECT). While effect sizes were consistently large across all time points and aligned with prior meta-analyses 29,49 , the average clinical response—defined as a ≥50% reduction in depression severity—was not reached until beyond 24-months of follow-up. This delay underscores a critical point: patients undergoing DBS for TRD may not achieve conventional responder status until more than two years post-implantation. A prior meta-analysis similarly found an average time to response of 23 months, reinforcing this observation 31 . These findings have important implications for future trial design, suggesting that studies may need extended durations to fully capture treatment effects. Alternatively, they raise the question of whether the conventional 50% reduction threshold is appropriate for DBS. For example, Holtzheimer et al. (2017) used a 40% reduction criterion, which may better reflect meaningful clinical improvement in this context 12 .Substantial heterogeneity was observed across timepoints, consistent with prior meta-analyses 30,31 . While meta-regression did not identify stimulation target or study design as significant moderators of effect size, a previous meta-analysis attributed a considerable proportion of heterogeneity to these factors—particularly greater treatment effects in open-label trials. Differences in analytic approach, timepoint selection, and sample composition may explain the discrepancy. Unmeasured variables, such as stimulation parameters or clinical heterogeneity across cohorts, likely contributed as well. Clarifying these sources will require harmonized reporting standards and access to individual patient-level data. Stimulation Target Identifying the optimal target site remains an unresolved question. Our meta-regression of all 24 selected studies revealed that stimulation target did not influence treatment outcomes across time-points. This is generally in agreement with two prior meta-analyses investigating stimulation site differences in MDD outcomes. Hitti et al. (2020) found that stimulation site, including the SCC, internal capsule, slMFB and inferior thalamic peduncle, did not influence depression score outcomes 29 . Further, a more recent meta-analysis demonstrated no statistical difference between stimulation targets 31 , however it found that 40% of the observed heterogeneity was due to stimulation site, favouring the MFB and Vc/Vs. A small number of trials have addressed this question directly. For example, a comparison of SCC vs. Vc/NAc stimulation revealed no significant difference in therapeutic effect 44 . Similarly, Raymaekers et al. (2017) did not detect a statistical difference between the anterior limb of the internal capsule/BNST and inferior thalamic peduncle stimulation, though they reported a trend possibly favouring the former. More recently, Wang et al. (2024) provided correlational evidence that the BNST may be a more effective target than the NAc 39 . While our analysis did not identify a significant difference between targets, we found that the strongest antidepressant effects were observed in studies targeting the SCC across all time-points. We also addressed the possibility that heterogeneity in baseline MADRS scores among the stimulation site sub-groups may have confounded our meta-regression. Reassuringly, we found no significant differences in baseline symptom severity between patients receiving SCC, Vc/Vs, or MFB stimulation. Overall, the small number of available trials with head-to-head comparisons and heterogeneity of targets limits our understanding of the impact of this variable. Future studies carrying out systematic comparisons may help clarify this question. Insights into the circuit dynamics underlying depression have led to the notion that the optimal target may differ according to the symptom cluster being treated 50 . Considering the lack of consistent evidence favoring one target, identifying a single “best” stimulation site may be less relevant. Rather, it is possible that stimulating regions broadly implicated in MDD may be sufficient to produce clinical benefit. Moving forward, the field may need to shift focus toward developing a more nuanced understanding of how target selection should be tailored and adjusted based on patient presentation. Study type We did not observe a significant difference between outcomes from RCTs vs. open-label trials at any of the main follow-up time points analyzed, with study type explaining little to none of the variance. This is in contrast to previous meta-analyses which have generally found better outcomes in open-label studies. The recent report by Reddy et al. showed a 20% greater improvement in depression scores in open-label studies compared to RCTs, citing differences in average sample size or baseline patient characteristics as possible factors 31 . Our study found no difference in baseline MADRS scores between patients from RCTs and those from open-label studies, suggesting that our analysis of study type as a moderator of outcomes was not confounded by baseline symptom severity differences. However, prior meta-analyses which have exclusively evaluated blinded studies have reported significant effects of active stimulation over sham 29 , therefore more work is needed to clarify this discrepancy. One important factor to reconcile is timeframe, since existing meta-analyses range from those focused on earlier phases 29 to those like ours which examine outcomes at later timepoints when all studies are in the open-label phase. Number of follow-up time-points To better understand factors contributing to our observed outcomes, we examined whether the frequency of clinic visits including parameter adjustments, impacted treatment outcomes. Interestingly, we found a significant linear relationship between the rate of follow up visits after study initiation and the rate of symptom improvement. In contrast, there was no such relationship for the rate of follow-up on the absolute improvement in depressive symptoms. While exploratory in nature, these findings are similar to psychotherapy studies which found that increased session frequency was associated with more rapid symptom reduction 51 . These findings may hold important clinical relevance, as faster symptom relief is associated with greater retention and adherence to therapies to treat depression 52 . These insights may inform future study design by emphasizing the value of frequent follow-up visits with participants, particularly in earlier stages of treatment. Secondary outcomes Functional improvement and anxiety symptoms following DBS were evaluated. Eight studies included GAF outcomes, which demonstrated significant and sustained improvements across time-points indicating that DBS improves social, psychological and occupational functioning. Considering that MDD significantly impacts functioning and quality of life, future research might benefit from incorporating functional outcome measures that may identify improvements in burden of disease 53 . Furthermore, quality of life was not consistently assessed across studies, and the variability in measurement tools limited our ability to analyze these outcomes. Future research should consider incorporating standardized quality of life measures to provide a more comprehensive evaluation of treatment effects beyond symptom reduction alone. Anxiety outcomes significantly improved following DBS. Heterogeneity was low across studies, indicating that the observed anxiolytic effects were consistent and reliable across studies. This is notable as depression and anxiety frequently coexist 54 . An alternative explanation for the low heterogeneity observed could reflect heightened preoperative anxiety, commonly seen in patients undergoing surgical procedures, which diminish gradually following successful recovery. Nevertheless, the consistent improvement across studies suggests that DBS may directly contribute to alleviating both depressive and anxiety symptoms along with improving functional outcomes, supporting its potential for broader therapeutic effects beyond mood symptomatology alone. Limitations While this study expands on existing meta-analytical evidence for DBS in the treatment of MDD, it faced limitations through small sample sizes, particularly the low number of RCT’s compared to open-label studies along with the wide spread of stimulated targets with small sample sizes for certain targets. Short blinding periods in RCT’s may have impacted the internal validity, limiting conclusions about the efficacy of active vs. Sham stimulation and optimal targets. High cross study variance remained unexplained despite subgroup analyses and variability may have been introduced by converting HAMD-17 scores into MADRS scores. Lastly, many studies did not report adverse events in sufficient detail, limiting our ability to accurately and confidently assess the safety profile of DBS treatment. Conclusion The present meta-analysis represents the most comprehensive evaluation to date of the efficacy of DBS in the treatment of MDD. Our findings indicate that DBS significantly reduces depressive symptoms across short-, moderate- and long-term follow-up, with the most pronounced effects observed at long-term follow-up. Notably, treatment outcomes did not vary significantly by stimulation target or study design. However more frequent follow-up assessments were associated with a faster rate of symptom improvement. 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Neurol Ther 12 , 5-12, doi:10.1007/s40120-023-00469-6 (2023). Table 1 Table 1. Overview of included studies Study Target Design Number of patients† (b, s, m, l) Age Percent female Baseline MADRS Follow-up duration (years) Fitzgerald, 2018 (Australia) BNST Open label 5, 5, 5, - 44.6 (12.3) 100 38.6 (1.98) 1.5-2 Wang, 2024 (China) BNST/NAc Open label 23, -, 21, - 32.6 (9.9) 13 31.3 (6.3) 2 Raymaekers, 2017 (Belgium) Vc/BNST, ITP RCT 7, -, -, 7 50 (5.6) 43 38.1 (7) 5.25 Bewernick, 2017 (Germany) slMFB Open label 8, 8, 8, - 41.9 (8.7) 37.5 30 (7.39) 4 Coenen, 2019 (Germany) slMFB RCT 16 (8 active, 8 sham), -, 14, - 51.6 (10.2) 37.5 29.6 (4) 1 Fenoy, 2022 (USA) slMFB Open label 9, -, 9, - 50.4 (7.8) 60 33.56 (5.39) 1 Millet, 2014 (France) NAc, caudate nucleus Open label 4, 4, 4, - 52 (8.28) 25 32.5 (3.88) 1.25 Rizvi, Giacobbe, 2025 (Canada) SCC RCT 35, 35, 29, 26 44.96 (9.33) 55.6 33.1 (2.81) 2 Alagapan, 2023 (USA) SCC Open label 10, 10, -, - 49.4 (11.2) 60 28.3 (2.08) 0.5 Alemany, 2023 (Spain) SCC Open label 16, -, 16, 16 48.6 (9.8) 75 27.1 (3.08) 11 Conroy, 2021 (USA) SCC Open label 5, 5, -, - 45 (5.33) 50 28.5 (2.51) 0.75 Crowell, 2019 (USA) SCC Open label 28, -, 27 ,26 44.9 (9.8) 68 29.5 (3.4) 8 Holtzheimer, 2017 (USA, Canada,UK) SCC RCT 90 (60 active, 30 sham), 80, 68, - Active - 50.53 (9.73); sham - 48.7 (0.56) Active - 50; sham - 57 Active – 33.8 (4.5); sham – 37.3 (3.8) 2.5 Kennedy, 2011 (Canada) SCC Open label 20, -, 16, 14 47.4 (10.4) 55 31.4 (4.5) 6 Lozano, 2012 (Canada) SCC Open label 21, -, 20, - 47.3 (6.1) 61.9 47.4 (5.8) 1 Merkl, 2018 (Germany) SCC RCT 8, 8, 4, - 48.25 (12.89) 25 35 (3.4) 2 Ramasubbu, 2015 (Canada) SCC Open label 4, 4, -, - 50.25 (4.19) 75 39.75 (3.71) 0.75 Ramasubbu, 2020 (Canada) SCC RCT 22 (10 LPW, 12 SPW), 22, 22, - 46.31 (14.35) LPW - 45.5; SPW - 45.4 LPW - 30.45 (2.7); SPW – 30 (1.2) 1 Conen, 2018 (UK) SCC, Vc/NAc Open label 7, 7, 7, - 48.6 (11.7) 75 39.51 (7.48) 3.75 Bergfeld, 2022 (Netherlands) Vc/Vs Open label 25, -, -, 25 53.2 (8.4) 68 34 (5.8) 6 Bewernick, 2012 (Germany) NAc Open label 11, 11, 11, 5 48.46 (11.08) 33 32.3 (3.7) 2.08 Dougherty, 2015 (USA) Vc/Vs RCT 30 (16 active, 14 sham), -, 26, - 47.4 (12) 43 36.7 (4.3) 2 Lai, 2023 (China) Vc/Vs Open label 10, 10, -, - 33.9 (9) 10 29.2 (6.7) 7.4 Malone, 2009 (USA) Vc/Vs Open label 15, 15, 11, - 46.3 (10.8) 73.3 34.8 (7.3) 1 Number of studies (pts) slMFB Vc/Vs BNST Multiple targets RCT Open label Total 3 (33) 5 (91) 1 (5) 4 (41) 7 (208) 17 (221) 24 (429) SCC = subcallosal cingulate; Vc/Vs = ventral capsule/ventral striatum; BNST = bed nucleus of the stria terminalis; NAc = nucleus accumbens; slMFB = superolateral medial forebrain bundle; MADRS = Montgomery–Åsberg Depression Rating Scale † Numbers represent N at baseline (b), short-term follow-up (s), moderate follow-up (m), and long-term follow-up (l), or “-“ if not applicable Additional Declarations There is NO Competing Interest. 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Frequency and MADRS Score Improvement. Holtzheimer, 2017* = active condition in RCT, Holtzheimer, 2017** = sham condition in RCT, Ramasubbu 2020* = long pulse width (LPW), Ramasubbu, 2020** = short pulse width (SPW) , Rizvi, 2025* = open label phase, Rizvi, 2025** = ON/ON phase\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7238063/v1/bec87c99ad1c38c7208c76ae.png"},{"id":89993369,"identity":"39ebc91b-9ae9-48a1-828c-d7321b19d648","added_by":"auto","created_at":"2025-08-27 07:43:43","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":113026,"visible":true,"origin":"","legend":"\u003cp\u003ePooled MADRS scores at baseline, short-term (6-9 months), moderate-term (12-24 months), long-term (\u0026gt;24 months) and Last Follow Up (Mean=22.5 months).\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-7238063/v1/7844ca1424577e4013c8464a.png"},{"id":89993377,"identity":"57cc2199-eebe-42ca-acef-d2d8ee3231a7","added_by":"auto","created_at":"2025-08-27 07:43:44","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":612409,"visible":true,"origin":"","legend":"\u003cp\u003eForest Plot of Treatment Effects at short-, moderate-, long-term and last follow up with pooled effects by stimulation target\u003c/p\u003e\n\u003cp\u003eHoltzheimer, 2017* = active condition in RCT, Holtzheimer, 2017** = sham condition in RCT, Ramasubbu 2020* = long pulse width (LPW), Ramasubbu, 2020** = short pulse width (SPW) , Rizvi, 2025* = open label phase, Rizvi, 2025** = ON/ON phase\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-7238063/v1/50da0572904892d4c019671f.png"},{"id":89994631,"identity":"f5148560-055a-48fe-807d-b5438c36a30e","added_by":"auto","created_at":"2025-08-27 07:51:44","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":180601,"visible":true,"origin":"","legend":"\u003cp\u003eBaseline MADRS scores according to stimulation target and study type. Comparison of baseline scores (mean ± standard deviation) among (A) patients from different stimulation site sub-groups (F(2, 18)=0.27, p=0.77) and (B) patients from RCTs vs. open-label studies (p=0.84).\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-7238063/v1/d0ac4d4628e89eacc9a5c2b2.png"},{"id":89993372,"identity":"43470f40-4c85-46d2-95dc-791d953a37fe","added_by":"auto","created_at":"2025-08-27 07:43:44","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":593637,"visible":true,"origin":"","legend":"\u003cp\u003eMADRS score percent reduction correlated with rate of follow up visits post-DBS (A). Rate of MADRS score percent reduction correlated with rate of follow up visits post-DBS (B).\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-7238063/v1/2b30ed57354b8d74ac14595f.png"},{"id":89993371,"identity":"65fa6c12-b9b9-440b-bf3f-570b2933b70f","added_by":"auto","created_at":"2025-08-27 07:43:43","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":394535,"visible":true,"origin":"","legend":"\u003cp\u003eFunnel Plot of Effect Size and Standard Error at Long-Term Follow-Up\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-7238063/v1/f7b749b9a9178db1573d36b6.png"},{"id":89993373,"identity":"80c5e716-fde7-42f3-bf1f-a4cdb5e7e556","added_by":"auto","created_at":"2025-08-27 07:43:44","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":717876,"visible":true,"origin":"","legend":"\u003cp\u003eSummary of Key Findings and Recommendations by Efficacy, Stimulation Target, Time to Response, and Follow-Up Frequency\u003c/p\u003e","description":"","filename":"8.png","url":"https://assets-eu.researchsquare.com/files/rs-7238063/v1/28c0fe3bbeff26b9437afa08.png"},{"id":93211400,"identity":"27a82663-7224-49cd-bd94-ead76705d220","added_by":"auto","created_at":"2025-10-10 09:03:51","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":5426938,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7238063/v1/9fbb17d4-d515-489d-b47d-dd55b830825c.pdf"},{"id":89993376,"identity":"1719429c-e89e-48cc-8066-47a2ecf036a4","added_by":"auto","created_at":"2025-08-27 07:43:44","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":298837,"visible":true,"origin":"","legend":"Supplemental Material","description":"","filename":"SupplementalMaterialMDDDBSMETA.docx","url":"https://assets-eu.researchsquare.com/files/rs-7238063/v1/1ed0b23c6e64e1d01734c9f9.docx"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"Deep brain stimulation for major depressive disorder: A Systematic Review and Meta-Analysis","fulltext":[{"header":"Introduction","content":"\u003cp\u003eMajor depressive disorder (MDD) affects approximately 350 million people worldwide, with a lifetime prevalence of 5\u0026ndash;20%\u003csup\u003e1\u003c/sup\u003e. First-line treatments for MDD typically include pharmacotherapy - such as selective serotonin reuptake inhibitors (SSRIs) and selective norepinephrine reuptake inhibitors (SNRIs) - alongside psychotherapeutic approaches such as cognitive behavioral therapy (CBT) and interpersonal therapy (IPT)\u003csup\u003e2,3\u003c/sup\u003e. However, approximately 30% of individuals will not respond to these treatments and are classified as having treatment resistant depression (TRD)\u003csup\u003e4\u003c/sup\u003e.\u003c/p\u003e\n\n\u003cp\u003eNeuromodulation is a promising treatment approach for various treatment-resistant psychiatric disorders\u003csup\u003e5\u003c/sup\u003e\u003ca id=\"_anchor_1\" href=\"#_msocom_1\" language=\"JavaScript\" name=\"_msoanchor_1\"\u003e\u003c/a\u003e, ranging from incisionless procedures such as ECT, repetitive transcranial magnetic stimulation (rTMS), ketamine, and focused ultrasound lesioning, to more invasive procedures such as deep brain stimulation (DBS), which modulate dysfunctional brain circuits via surgically implanted electrodes\u003csup\u003e6,7\u003c/sup\u003e. DBS is FDA approved for use in Parkinson\u0026rsquo;s disease and essential tremor, and has received a humanitarian device exception for use in obsessive compulsive disorder\u003csup\u003e8,9\u003c/sup\u003e. Its success in these conditions has sparked notable interest in its potential application in TRD\u003csup\u003e10\u003c/sup\u003e. \u003c/p\u003e\n\n\u003cp\u003eMultiple brain regions implicated in the pathophysiology of TRD have been investigated as targets for DBS, including the subcallosal cingulate cortex (SCC), ventral capsule/ventral striatum (Vc/Vs), bed nucleus of the stria terminalis (BNST), and superolateral branch of the medial forebrain bundle (slMFB)\u003csup\u003e11-17\u003c/sup\u003e.\u003ca id=\"_anchor_2\" href=\"#_msocom_2\" language=\"JavaScript\" name=\"_msoanchor_2\"\u003e\u003c/a\u003e To date, results from randomized controlled trials (RCTs) have been mixed, particularly during the blinded sham-controlled phases. The first randomized controlled trial (RCT), published in 2015, found no difference between active and sham Vc/Vs stimulation after 16 weeks\u003csup\u003e15\u003c/sup\u003e and similarly, a RCT evaluating SCC DBS failed to differentiate between active and sham stimulation at 6-months\u003csup\u003e12\u003c/sup\u003e. Notably, both studies demonstrated response rates close to 25% and 50%, respectively, at 2-year follow-up, suggesting that inadequate treatment duration may have contributed to early null findings. Open-label studies investigating outcomes at greater than 2 years have demonstrated robust positive effects further supporting that DBS outcomes tend to improve over time\u003csup\u003e13,16,18-21\u003c/sup\u003e. \u003c/p\u003e\n\u003cp\u003eEmerging evidence suggests individual predictors of response to DBS such as; shorter duration of illness/fewer failed mediation trials, higher emotional reactivity, early clinical response, and a lack of substance-abuse comorbidity have been linked with improved response to DBS\u003csup\u003e14,20,22-25\u003c/sup\u003e. Preoperative structural imaging studies have found that responders to DBS had larger SCC, thalamus and amygdala volumes compared to non-responders\u003csup\u003e26\u003c/sup\u003e. Further, integrity of the white matter tracts connected to the SCC, such as the uncinate fasciculus have been associated with better response rates to DBS\u003csup\u003e11\u003c/sup\u003e. Finally, millimetric deviations in electrode placement may influence the constellation of tracts modulated, and ultimately, the extent of clinical response\u003csup\u003e24\u003c/sup\u003e. Together, these findings suggest that a combination of clinical, structural, and connectivity-based characteristics may help identify patients most likely to benefit from DBS\u003csup\u003e26,27\u003c/sup\u003e. \u003c/p\u003e\n\u003cp\u003eFour prior meta-analyses have examined the effects of DBS on TRD, demonstrating promising pooled remission rates with larger treatment effects among open-label trials compared to RCTs\u003csup\u003e28-31\u003c/sup\u003e. Most recently, a 2024 meta-analysis reviewed 15 studies encompassing 275 participants, each with a minimum follow-up of one year. The study reported a 47% improvement in depressive symptoms from baseline to last follow up, with an average of 23 months required to achieve a 50% reduction in depression severity\u003csup\u003e31\u003c/sup\u003e.\u003c/p\u003e\n\n\u003cp\u003eThis meta-analysis builds on this foundation by including a larger and more temporally nuanced dataset, comprising 24 studies and 429 participants. We report outcomes at short-term (6-9 months), moderate-term (12-24 months) and long-term (\u0026gt;24 months) time-points, offering a comprehensive view of DBS efficacy over time. Beyond examining the influence of stimulation target and study design, we introduce a novel exploratory analysis assessing the impact of follow-up frequency on overall depression scores and the rate of symptom improvement. The findings from this study provide critical insights that can inform the design of future studies on DBS for depression and may help guide clinical strategies for optimizing DBS treatment in TRD.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003eData Sources and Search\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was preregistered in PROSPERO (CRD42024577570). Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines\u003csup\u003e32\u003c/sup\u003e, MEDLINE and Embase databases were searched on July 24 2024 using the MeSH terms \u0026ldquo;Deep brain stimulation\u0026rdquo;, and \u0026ldquo;Major Depressive Disorder\u0026rdquo; and a comprehensive list of search terms (Supp. Fig.1). Databases were monitored for new eligible studies until June 30 2025. Peer-reviewed studies on human subjects, published in English-language journals beginning in2005\u003cem\u003e \u003c/em\u003e(the first published series of DBS for TRD) were eligible. PICO criteria selection were as follows: population: adults with TRD; intervention: DBS to any intracranial target; comparison: pre-treatment depression scores; outcomes: Hamilton depression rating scale (HAMD) and the Montgomery-Asberg Depression Rating Scale (MADRS) with at least 6 months follow-up. \u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Extraction and Quality Assessment\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTwo independent reviewers (JE and FM) used Covidence\u003csup\u003e33\u003c/sup\u003eto independently screen study titles and abstracts, and then full-text, with any conflicts resolved by a third reviewer (BD). To ensure the integrity of the dataset, all full-texts were reviewed in detail, and clinical trial registration numbers were cross-referenced to verify that multiple publications did not originate from the same participant cohort. Data were extracted by two independent reviewers (FM \u0026amp; BD) and were cross-checked by two additional independent reviewers (AA \u0026amp; MP) using Excel. \u003c/p\u003e\n\u003cp\u003eThe extracted data from each study included study design, target, sample size, participant demographics, depression scores (MADRS, HAMD-17) at baseline and all available follow-up time points, response and remission rates, Hamilton Anxiety Rating Scale (HAM-A), quality of life measures, global assessment of functioning (GAF), DBS stimulation parameters, and adverse events.\u003c/p\u003e\n\u003cp\u003eHAMD-17 scores were converted to MADRS scores using the conversion method described by Leucht et al. (2018)\u003csup\u003e34\u003c/sup\u003e. Additionally, the two studies that reported percentage change scores were standardized to mean MADRS scores from baseline mean scores. All included studies defined response as a \u0026ge;50% reduction in depression scores. Definitions of remission varied slightly across studies: ten studies used HAMD-17 \u0026le;7\u003csup\u003e11,18-21,35-39\u003c/sup\u003e, one used HAMD-24 \u0026le;10\u003csup\u003e40\u003c/sup\u003e, one used HAMD-28 \u0026le;10\u003csup\u003e16\u003c/sup\u003e, five used MADRS \u0026le;10\u003csup\u003e12,15,41-43\u003c/sup\u003e, one study defined remission as MADRS \u0026le;8\u003csup\u003e44\u003c/sup\u003e, one study did not define remission scores\u003csup\u003e45\u003c/sup\u003e, and four studies did not assess remission\u003ca id=\"_anchor_1\" href=\"#_msocom_1\" language=\"JavaScript\" name=\"_msoanchor_1\"\u003e\u003c/a\u003e\u003csup\u003e13,14,17,46,47\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eGiven the variability in follow-up durations across studies, we included all reported time points \u0026ge;6-months and categorized them into short-term (6-9 months), moderate-term (12-months to 24-months), long-term (\u0026gt;24-months), and last follow-up (LFU) time-point clusters. When multiple time-points within a cluster were reported (i.e. both 6 and 9-months short-term data), the later time point was used. For studies that reported results in graphs, we extracted values from figures using Automeris.io (http://automeris.io/). For studies that included a randomized ON/OFF period of sham versus active stimulation for 6-months or greater, data from the sham group were only included once they transitioned into active stimulation. For example, if a study included 6-months of active versus sham stimulation, 12-month time-point data was labelled as 6-months for the sham group, and 12-months for the active group\u003csup\u003e12\u003c/sup\u003e. \u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAssessment of Risk of Bias\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe Cochrane Risk of Bias in Non-Randomized Studies (ROBINS-I) tool\u003csup\u003e48\u003c/sup\u003e was used to evaluate the bias (Supplemental Table S2) by two independent reviewers (FM \u0026amp; AA), with conflicts resolved by a third (BD). Visual and statistical assessment of publication bias was performed using funnel plots with Egger\u0026rsquo;s test. \u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eStatistical analyses were conducted in RStudio (v4.4.3) using the metafor, metaviz, and dplyr packages. Random-effects meta-analyses were used to estimate effect sizes and account for between-study heterogeneity. For MADRS outcomes, Hedges\u0026rsquo; \u003cem\u003eg\u003c/em\u003e was calculated as the difference between baseline and follow-up scores (baseline minus follow-up), with positive values indicating improvement. Meta-regressions were performed across all time-point clusters using DBS stimulation target and study design as moderators. Heterogeneity was assessed using the I\u0026sup2; statistic, between-study variance with \u0026tau;\u0026sup2; , and the proportion of variance explained by moderators with R\u0026sup2;. Statistical significance was set at p\u0026lt;0.05. Means were reported alongside standard deviations. A leave-one-out sensitivity analysis was performed across all timepoints to identify influential studies. Secondary analyses of anxiety symptoms and global functioning were performed.\u003c/p\u003e\n\u003cp\u003eAs an exploratory assessment of the relationship between follow-up frequency and clinical improvement, we conducted both linear regression and Spearman correlation analyses using GraphPad-Prism 10. Follow-up visit frequency was extracted from each study and used to calculate a visit rate over a standardized 6\u0026ndash;24 month period, excluding two studies with exceptionally long follow-up durations to minimize skew.\u003ca id=\"_anchor_4\" href=\"#_msocom_4\" language=\"JavaScript\" name=\"_msoanchor_4\"\u003e\u003c/a\u003e The corresponding MADRS score reported at the same follow-up time point was used as the outcome measure. These variables were then plotted and analyzed to explore potential associations.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eStudy Selection\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe search yielded 2472 articles across both databases and after duplicates and pre-2005 studies were removed, 1782 articles remained for screening. 24 studies met final inclusion , consisting of 7 RCT\u0026rsquo;s \u003csup\u003e12,15,21,38,40,42,47\u003c/sup\u003e and 17 open-label studies\u003csup\u003e8,11,13,16-18,20,35-37,39,41,43-46\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eParticipants\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA total of 429 unique adult participants with a mean age of 46.90 years (SD=9.18) were included. The mean age at disease onset was 26.96 years (SD=8.62), and 51% of the participants were female. Participants had moderate depression at baseline (MADRS score of 33.55 (SD=4.35)). The average sample size across studies was 16.5 participants (range: 4 to 90), with a mean follow-up duration of 30.93 months (SD=36.61).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStimulation target and outcome measures\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe most common targets for DBS stimulation included the SCC (11 studies, n=224), Vc/Vs (5 studies, n=91), slMFB (3 studies, n=33), and BNST (1 study, n=5). Four studies (n=41) compared effects of stimulation on multiple targets\u003csup\u003e21,37,39,44\u003c/sup\u003e. \u0026nbsp;All included studies reported either MADRS (n=13) or HAMD-17 (n=11) scores (see Figure 2 for MADRS/MADRS-converted scores in all studies).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e19 studies (n=243) reported short-term results. MADRS scores improved by 41.7% +/- 16.5, with a significant and large effect size (Hedges\u0026rsquo; \u003cem\u003eg\u003c/em\u003e = 2.40, p\u0026lt;0.01, 95% CI: 1.80\u0026ndash;3.00). Heterogeneity was high (I\u0026sup2;=83.89%, Q(df=18)=98.09, p\u0026lt;0.01), indicating substantial variability in effect sizes (H\u0026sup2;=6.21, \u0026tau;\u0026sup2;=1.36). \u0026nbsp;Leave-one-out sensitivity analysis revealed that no single study contributed significantly to the overall heterogeneity and did not influence the pooled effect size (range: 2.24-2.50) ( I\u0026sup2;= 79.3% to 85.2%).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eA moderate follow-up timepoint was reported by 19 studies (n=329). MADRS scores improved 48.04% +/-\u003ca id=\"_anchor_1\" href=\"#_msocom_1\" language=\"JavaScript\" name=\"_msoanchor_1\"\u003e\u003c/a\u003e13.72%, with a large effect size (Hedges\u0026rsquo; \u003cem\u003eg\u003c/em\u003e=2.83, p\u0026lt;0.01, 95% CI, 2.04, 3.61). Heterogeneity was significant (I\u0026sup2;=92.33%, Q (df=18)=166.78, p \u0026lt; 0.01), indicating substantial variability in effect sizes (Tau\u0026sup2;=2.71, H\u0026sup2;=13.04). Leave-one-out sensitivity analysis revealed that no individual study contributed significantly to the overall heterogeneity (I\u0026sup2;=85.99% to 92.99%) and did not influence the overall effect size (range: 2.53-2.95)\u003c/p\u003e\n\u003cp\u003eLong-term follow-up data ranged from 3 to 7 years and consisted of 88 participants across five studies. MADRS scores at long-term follow-up improved 64.11% +/-15.58% compared to baseline. Analysis of these studies revealed a significant positive effect (Hedges\u0026apos; \u003cem\u003eg\u003c/em\u003e=4.33, p=0.01, 95% CI: 1.76-6.89). Heterogeneity was significant (I\u0026sup2;=96.38%, Q(df=4)=53.15, p \u0026lt; 0.01), indicating substantial variability between studies (H\u0026sup2;=27.60, \u0026tau;\u0026sup2;=7.98). The leave-one-out sensitivity analysis revealed no single study significantly contributed to the overall heterogeneity (Hedges\u0026rsquo; \u003cem\u003eg\u003c/em\u003e=3.12-5.05;\u0026nbsp;I\u0026sup2;=88.1% to 97.6%).\u003c/p\u003e\n\u003cp\u003eThe LFU time\u003ca id=\"_anchor_2\" href=\"#_msocom_2\" language=\"JavaScript\" name=\"_msoanchor_2\"\u003e\u003c/a\u003e point was analyzed for all 24 studies (n=393), revealing a 50.38% +/- 15.98 improvement in MADRS scores. The average duration of follow-up at LFU was 22.5 months. Meta-analysis revealed a large and statistically significant effect of DBS on MADRS scores (Hedges\u0026rsquo; \u003cem\u003eg\u003c/em\u003e=2.88, p\u0026lt;0.01, 95% CI, 2.16 to 3.60). Heterogeneity was high (I\u0026sup2;=92.56%, Q(df=25)=188.22, p\u0026lt;0.01), with substantial variability between studies (H\u0026sup2;=13.44 \u0026tau;\u0026sup2;=3.09). At LFU, the mean response rate (\u0026gt;50% reduction in HAMD17/MADRS) was 53.36%. The mean remission rate at LFU was 41.5% (reported in 21 studies). Leave-one-out sensitivity analysis revealed that no individual study contributed significantly to the overall heterogeneity (I\u0026sup2;=88.83% to 93.08%) or influenced pooled effect sizes (range: 2.65-2.97)\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTarget Site\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDBS target did not significantly influence outcomes at short-term, moderate-term, long-term, and LFU respectively (QM(df=5)=2.49, p= 0.78;\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eQM(df=5)=2.67, p=0.75;\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eQM(df=2)=1.30, p=0.52\u003cstrong\u003e;\u003c/strong\u003e QM(df=7)=2.19, p=0.95). \u0026nbsp;Residual heterogeneity remained high across time-points ( I\u0026sup2;\u0026gt;87%), with target site accounting for 0% of the variability across short, moderate and LFU and 6.26% of the observed variability at long-term follow-up. Pooled effects for each stimulation target, revealed strong effect sizes across all targets at all time-points. The SCC demonstrated the most robust effects across all time-points (Short-term Hedges\u0026rsquo; \u003cem\u003eg\u003c/em\u003e=2.82, 95% CI: 1.82-3.81; Moderate-term: Hedges\u0026rsquo; \u003cem\u003eg\u003c/em\u003e=3.59, 95% CI: 2.10-5.09; Long-term: Hedges\u0026rsquo; \u003cem\u003eg\u003c/em\u003e=5.68, 95% CI: 1.92-9.45; LFU: Hedges\u0026rsquo; \u003cem\u003eg\u003c/em\u003e=3.55, 95% CI: 2.10-4.99).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStudy Design\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eStudy design (RCT vs. open-label) was not a significant moderator of effect size at any time-point (short-term: QM(df=1)=0.01, p=0.91; moderate-term: QM(df=1)=0.03, p=0.86, long-term: (QM(df=1)=0.13, p=0.71), LFU: (QM(df=1)=0.09, p=0.76. Heterogeneity was high across time-points (I\u0026sup2;\u0026gt;83.77%), with 0% variance explained by study design at short-, moderate-, long-term follow up and LFU. There was no significant difference in the proportion of RCT\u0026rsquo;s and open-label studies representing\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eeach target site (p=0.96, Fisher\u0026rsquo;s exact test).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBaseline Depression Severity\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBaseline heterogeneity was assessed by comparing average baseline MADRS scores across stimulation targets (SCC, Vc/Vs, MFB) and study designs (RCTs vs. open-label) (Figure 5; Supplemental Figures A2.A\u0026ndash;B). \u0026nbsp;No significant differences were observed, suggesting that initial depression severity and episode duration are unlikely to confound outcomes. (Supplemental Figure A1).\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSecondary outcome measures\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eGAF scores at the short-term timepoint were available from 5 studies (n=129), demonstrating a 30.96% \u0026plusmn; 3.01% improvement from baseline. The overall effect size was very large (Hedges\u0026rsquo; \u003cem\u003eg\u003c/em\u003e=1.98, 95% CI: 1.17 to 2.80, p \u0026lt; 0.01). At the moderate-term follow-up, data from 6 studies (n=124) showed a 44.27% \u0026plusmn; 3.06% improvement (Hedges\u0026rsquo; \u003cem\u003eg\u003c/em\u003e=2.22, 95% CI: 1.53 to 2.90, p\u0026lt;0.01). GAF scores at long-term follow-up were available for 8 studies (n=162), demonstrating a 43.03% \u0026plusmn; 3.59% improvement from baseline (Hedges\u0026rsquo; \u003cem\u003eg\u003c/em\u003e=1.94, 95% CI: 1.44 to 2.43, p\u0026lt;0.01). Heterogeneity was high across all time-points (I\u0026sup2;\u0026gt;66%)\u003c/p\u003e\n\u003cp\u003eHAM-A scores were available for 7 studies (n=77). The overall effect size at LFU was significant (Hedges\u0026rsquo; \u003cem\u003eg\u003c/em\u003e=1.58, 95% CI: 1.22 to 1.93, p \u0026lt; 0.01). Heterogeneity was not significant (Q=3.78, p=0.81), indicating similar effect sizes between studies.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFrequency of Follow-Up Visits and MADRS Score\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe examined whether the frequency of follow-up visits after DBS was associated with clinical improvement. Follow-up rate (visits per month) was plotted against percent reduction in MADRS score at each timepoint (Figure 6A). Follow-up visits included all documented clinical encounters, including those involving stimulation adjustments. Linear regression revealed no significant relationship between follow-up rate and MADRS reduction (R\u0026sup2;=0.12, \u003cem\u003ep\u003c/em\u003e=0.14), and Spearman correlation similarly showed no significant association (\u0026rho;=0.24, \u003cem\u003ep\u003c/em\u003e=0.32).\u003c/p\u003e\n\u003cp\u003eTo assess not just \u003cem\u003ehow much\u003c/em\u003e patients improved but \u003cem\u003ehow quickly\u003c/em\u003e they improved, we also examined the relationship between follow-up rate and the rate of MADRS score improvement (i.e., percent reduction per month; Figure 6B). In this analysis, linear regression showed a significant positive association (R\u0026sup2;=0.28, \u003cem\u003ep\u003c/em\u003e=0.02), and Spearman correlation confirmed a similar result (p=0.50, \u003cem\u003ep\u003c/em\u003e=0.03). These findings suggest that more frequent follow-up is associated with faster symptom improvement over time, though not necessarily with greater overall improvement at any given time-point.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eAssessment of Bias\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA moderate risk of bias was found in 67% of studies due primarily to concerns related to confounding, missing data, measurement of outcomes, and selection of reported results (Table S2). A low risk of bias was found in 29% of studies, with a general low concern for bias with respect to selection of participants, classification of interventions, and deviations from intended interventions. Serious risk of bias was identified across 6 of 7 domains in one open-label study evaluating VC/VS stimulation. RCTs accounted for 3 of 7 low-risk studies and were not more likely than open-label studies to have low overall RoB (p=0.37, Fisher\u0026rsquo;s exact test).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;A funnel-plot and Egger\u0026rsquo;s test revealed significant asymmetry (z=2.91, p\u0026lt;0.01) and a limit estimate of (b=0.35, CI: -1.42 to 2.12), suggesting that smaller studies with non-significant results may be underrepresented in the analysis (Figure 7).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis meta-analysis provides an uptodate evaluation of the available evidence for DBS in the treatment of TRD. Our analysis revealed very large and significant effect sizes at all timepoints, with the greatest effect at long-term follow-up (Hedges\u0026rsquo; \u003cem\u003eg\u003c/em\u003e=). This is consistent with the overall trend in previously published cohort studies and meta-analyses, which show gradual symptom improvement over years across study types and stimulation targets\u003csup\u003e28-31\u003c/sup\u003e\u003ca id=\"_anchor_1\" href=\"#_msocom_1\" language=\"JavaScript\" name=\"_msoanchor_1\"\u003e\u003c/a\u003e. While previous meta-analyses have primarily explored outcomes at single time-points, this study provides a temporal perspective by demonstrating that the antidepressant effect of DBS is maintained from short to long-term time-points.\u003c/p\u003e\n\n\u003cp\u003eThe present meta-analysis includes the longest pooled follow-up data on depression outcomes after DBS to date. These sustained effects are particularly noteworthy given the high relapse rates associated with other treatments for TRD, including electroconvulsive therapy (ECT).\u003ca id=\"_anchor_2\" href=\"#_msocom_2\" language=\"JavaScript\" name=\"_msoanchor_2\"\u003e\u003c/a\u003e While effect sizes were consistently large across all time points and aligned with prior meta-analyses\u003csup\u003e29,49\u003c/sup\u003e, the average clinical response\u0026mdash;defined as a \u0026ge;50% reduction in depression severity\u0026mdash;was not reached until beyond 24-months of follow-up. This delay underscores a critical point: patients undergoing DBS for TRD may not achieve conventional responder status until more than two years post-implantation. A prior meta-analysis similarly found an average time to response of 23 months, reinforcing this observation\u003csup\u003e31\u003c/sup\u003e. These findings have important implications for future trial design, suggesting that studies may need extended durations to fully capture treatment effects. Alternatively, they raise the question of whether the conventional 50% reduction threshold is appropriate for DBS. For example, Holtzheimer et al. (2017) used a 40% reduction criterion, which may better reflect meaningful clinical improvement in this context\u003csup\u003e12\u003c/sup\u003e.Substantial heterogeneity was observed across timepoints, consistent with prior meta-analyses\u003csup\u003e30,31\u003c/sup\u003e . While meta-regression did not identify stimulation target or study design as significant moderators of effect size, a previous meta-analysis attributed a considerable proportion of heterogeneity to these factors\u0026mdash;particularly greater treatment effects in open-label trials. Differences in analytic approach, timepoint selection, and sample composition may explain the discrepancy. Unmeasured variables, such as stimulation parameters or clinical heterogeneity across cohorts, likely contributed as well. Clarifying these sources will require harmonized reporting standards and access to individual patient-level data.\u003c/p\u003e\n\n\u003cp\u003e\u003cem\u003eStimulation Target\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eIdentifying the optimal target site remains an unresolved question. Our meta-regression of all 24 selected studies revealed that stimulation target did not influence treatment outcomes across time-points. This is generally in agreement with two prior meta-analyses investigating stimulation site differences in MDD outcomes. Hitti et al. (2020) found that stimulation site, including the SCC, internal capsule, slMFB and inferior thalamic peduncle, did not influence depression score outcomes\u003csup\u003e29\u003c/sup\u003e.\u003csup\u003e \u003c/sup\u003e Further, a more recent meta-analysis demonstrated no statistical difference between stimulation targets\u003csup\u003e31\u003c/sup\u003e, however it found that 40% of the observed heterogeneity was due to stimulation site, favouring the MFB and Vc/Vs. A small number of trials have addressed this question directly. For example, a comparison of SCC vs. Vc/NAc stimulation revealed no significant difference in therapeutic effect\u003csup\u003e44\u003c/sup\u003e. Similarly, Raymaekers et al. (2017) did not detect a statistical difference between the anterior limb of the internal capsule/BNST and inferior thalamic peduncle stimulation, though they reported a trend possibly favouring the former. More recently, Wang et al. (2024) provided correlational evidence that the BNST may be a more effective target than the NAc\u003csup\u003e39\u003c/sup\u003e. While our analysis did not identify a significant difference between targets, we found that the strongest antidepressant effects were observed in studies targeting the SCC across all time-points. We also addressed the possibility that heterogeneity in baseline MADRS scores among the stimulation site sub-groups may have confounded our meta-regression. Reassuringly, we found no significant differences in baseline symptom severity between patients receiving SCC, Vc/Vs, or MFB stimulation. \u003c/p\u003e\n\n\u003cp\u003eOverall, the small number of available trials with head-to-head comparisons and heterogeneity of targets limits our understanding of the impact of this variable. Future studies carrying out systematic comparisons may help clarify this question. Insights into the circuit dynamics underlying depression have led to the notion that the optimal target may differ according to the symptom cluster being treated\u003csup\u003e50\u003c/sup\u003e.\u003ca id=\"_anchor_3\" href=\"#_msocom_3\" language=\"JavaScript\" name=\"_msoanchor_3\"\u003e\u003c/a\u003e Considering the lack of consistent evidence favoring one target, identifying a single \u0026ldquo;best\u0026rdquo; stimulation site may be less relevant. Rather, it is possible that stimulating regions broadly implicated in MDD may be sufficient to produce clinical benefit. Moving forward, the field may need to shift focus toward developing a more nuanced understanding of how target selection should be tailored and adjusted based on patient presentation. \u003c/p\u003e\n\n\u003cp\u003e\u003cem\u003eStudy type\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eWe did not observe a significant difference between outcomes from RCTs vs. open-label trials at any of the main follow-up time points analyzed, with study type explaining little to none of the variance. This is in contrast to previous meta-analyses which have generally found better outcomes in open-label studies. The recent report by Reddy et al. showed a 20% greater improvement in depression scores in open-label studies compared to RCTs, citing differences in average sample size or baseline patient characteristics as possible factors\u003csup\u003e31\u003c/sup\u003e. Our study found no difference in baseline MADRS scores between patients from RCTs and those from open-label studies, suggesting that our analysis of study type as a moderator of outcomes was not confounded by baseline symptom severity differences. However, prior meta-analyses which have exclusively evaluated blinded studies have reported significant effects of active stimulation over sham\u003csup\u003e29\u003c/sup\u003e, therefore more work is needed to clarify this discrepancy. One important factor to reconcile is timeframe, since existing meta-analyses range from those focused on earlier phases\u003csup\u003e29\u003c/sup\u003e to those like ours which examine outcomes at later timepoints when all studies are in the open-label phase.\u003c/p\u003e\n\n\u003cp\u003e\u003cem\u003eNumber of follow-up time-points\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eTo better understand factors contributing to our observed outcomes, we examined whether the frequency of clinic visits including parameter adjustments, impacted treatment outcomes. Interestingly, we found a significant linear relationship between the rate of follow up visits after study initiation and the rate of symptom improvement. In contrast, there was no such relationship for the rate of follow-up on the absolute improvement in depressive symptoms. While exploratory in nature, these findings are similar to psychotherapy studies which found that increased session frequency was associated with more rapid symptom reduction\u003csup\u003e51\u003c/sup\u003e. These findings may hold important clinical relevance, as faster symptom relief is associated with greater retention and adherence to therapies to treat depression\u003csup\u003e52\u003c/sup\u003e. These insights may inform future study design by emphasizing the value of frequent follow-up visits with participants, particularly in earlier stages of treatment. \u003c/p\u003e\n\u003cp\u003e\u003cem\u003eSecondary outcomes \u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eFunctional improvement and anxiety symptoms following DBS were evaluated. Eight studies included GAF outcomes, which demonstrated significant and sustained improvements across time-points indicating that DBS improves social, psychological and occupational functioning. Considering that MDD significantly impacts functioning and quality of life, future research might benefit from incorporating functional outcome measures that may identify improvements in burden of disease\u003csup\u003e53\u003c/sup\u003e. Furthermore, quality of life was not consistently assessed across studies, and the variability in measurement tools limited our ability to analyze these outcomes. Future research should consider incorporating standardized quality of life measures to provide a more comprehensive evaluation of treatment effects beyond symptom reduction alone.\u003c/p\u003e\n\n\u003cp\u003eAnxiety outcomes significantly improved following DBS. Heterogeneity was low across studies, indicating that the observed anxiolytic effects were consistent and reliable across studies. This is notable as depression and anxiety frequently coexist\u003csup\u003e54\u003c/sup\u003e . An alternative explanation for the low heterogeneity observed could reflect heightened preoperative anxiety, commonly seen in patients undergoing surgical procedures, which diminish gradually following successful recovery. Nevertheless, the consistent improvement across studies suggests that DBS may directly contribute to alleviating both depressive and anxiety symptoms along with improving functional outcomes, supporting its potential for broader therapeutic effects beyond mood symptomatology alone. \u003c/p\u003e\n\n\n\u003cp\u003e\u003cem\u003eLimitations\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eWhile this study expands on existing meta-analytical evidence for DBS in the treatment of MDD, it faced limitations through small sample sizes, particularly the low number of RCT\u0026rsquo;s compared to open-label studies along with the wide spread of stimulated targets with small sample sizes for certain targets. Short blinding periods in RCT\u0026rsquo;s may have impacted the internal validity, limiting conclusions about the efficacy of active vs. Sham stimulation and optimal targets. High cross study variance remained unexplained despite subgroup analyses and variability may have been introduced by converting HAMD-17 scores into MADRS scores. Lastly, many studies did not report adverse events in sufficient detail, limiting our ability to accurately and confidently assess the safety profile of DBS treatment.\u003c/p\u003e\n"},{"header":"Conclusion","content":"\u003cp\u003eThe present meta-analysis represents the most comprehensive evaluation to date of the efficacy of DBS in the treatment of MDD. Our findings indicate that DBS significantly reduces depressive symptoms across short-, moderate- and long-term follow-up, with the most pronounced effects observed at long-term follow-up. Notably, treatment outcomes did not vary significantly by stimulation target or study design. 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H.\u003cem\u003e et al.\u003c/em\u003e Deep brain stimulation to the medial forebrain bundle for depression- long-term outcomes and a novel data analysis strategy. \u003cem\u003eBrain Stimul\u003c/em\u003e \u003cstrong\u003e10\u003c/strong\u003e, 664-671, doi:10.1016/j.brs.2017.01.581 (2017).\u003c/li\u003e\n\u003cli\u003eCoenen, V. A.\u003cem\u003e et al.\u003c/em\u003e Superolateral medial forebrain bundle deep brain stimulation in major depression: a gateway trial. \u003cem\u003eNeuropsychopharmacology\u003c/em\u003e \u003cstrong\u003e44\u003c/strong\u003e, 1224-1232, doi:10.1038/s41386-019-0369-9 (2019).\u003c/li\u003e\n\u003cli\u003eMalone, D. A., Jr.\u003cem\u003e et al.\u003c/em\u003e Deep brain stimulation of the ventral capsule/ventral striatum for treatment-resistant depression. \u003cem\u003eBiol Psychiatry\u003c/em\u003e \u003cstrong\u003e65\u003c/strong\u003e, 267-275, doi:10.1016/j.biopsych.2008.08.029 (2009).\u003c/li\u003e\n\u003cli\u003eConen, S., Matthews, J. C., Patel, N. K., Anton-Rodriguez, J. \u0026amp; Talbot, P. S. Acute and chronic changes in brain activity with deep brain stimulation for refractory depression. \u003cem\u003eJ Psychopharmacol\u003c/em\u003e \u003cstrong\u003e32\u003c/strong\u003e, 430-440, doi:10.1177/0269881117742668 (2018).\u003c/li\u003e\n\u003cli\u003eFitzgerald, P. B.\u003cem\u003e et al.\u003c/em\u003e A pilot study of bed nucleus of the stria terminalis deep brain stimulation in treatment-resistant depression. \u003cem\u003eBrain Stimul\u003c/em\u003e \u003cstrong\u003e11\u003c/strong\u003e, 921-928, doi:10.1016/j.brs.2018.04.013 (2018).\u003c/li\u003e\n\u003cli\u003eRamasubbu, R., Vecchiarelli, H. A., Hill, M. N. \u0026amp; Kiss, Z. H. Brain-derived neurotrophic factor and subcallosal deep brain stimulation for refractory depression. \u003cem\u003eWorld J Biol Psychiatry\u003c/em\u003e \u003cstrong\u003e16\u003c/strong\u003e, 135-138, doi:10.3109/15622975.2014.952775 (2015).\u003c/li\u003e\n\u003cli\u003eGiacobbe, P., Rizvi, S., Centini, A., Tomlinson, G., Elias, G., Germann, J., Styra, R., Lozano, A., Kennedy, S. . Deep Brain Stimulation to the Subgenual Cingulate Gyrus for Treatment-Resistant Depression: A Randomized Controlled Trial and 2-Year Long-Term Follow-Up. \u003cem\u003eCanadian Journal of Psychiatry\u003c/em\u003e (2025).\u003c/li\u003e\n\u003cli\u003eSterne, J. 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H.\u003cem\u003e et al.\u003c/em\u003e Distinct Symptom-Specific Treatment Targets for Circuit-Based Neuromodulation. \u003cem\u003eAm J Psychiatry\u003c/em\u003e \u003cstrong\u003e177\u003c/strong\u003e, 435-446, doi:10.1176/appi.ajp.2019.19090915 (2020).\u003c/li\u003e\n\u003cli\u003eTiemens, B.\u003cem\u003e et al.\u003c/em\u003e Lower versus higher frequency of sessions in starting outpatient mental health care and the risk of a chronic course; a naturalistic cohort study. \u003cem\u003eBMC Psychiatry\u003c/em\u003e \u003cstrong\u003e19\u003c/strong\u003e, 228, doi:10.1186/s12888-019-2214-4 (2019).\u003c/li\u003e\n\u003cli\u003eKraus, C., Kadriu, B., Lanzenberger, R., Zarate Jr, C. A. \u0026amp; Kasper, S. Prognosis and improved outcomes in major depression: a review. \u003cem\u003eTranslational Psychiatry\u003c/em\u003e \u003cstrong\u003e9\u003c/strong\u003e, 127, doi:10.1038/s41398-019-0460-3 (2019).\u003c/li\u003e\n\u003cli\u003eLanglieb, A. M. \u0026amp; Guico-Pabia, C. J. Beyond symptomatic improvement:assessing real-world outcomes in patients with major depressive disorder. \u003cem\u003ePrim Care Companion J Clin Psychiatry\u003c/em\u003e \u003cstrong\u003e12\u003c/strong\u003e, doi:10.4088/PCC.09r00826blu (2010).\u003c/li\u003e\n\u003cli\u003eHopwood, M. Anxiety Symptoms in Patients with Major Depressive Disorder: Commentary on Prevalence and Clinical Implications. \u003cem\u003eNeurol Ther\u003c/em\u003e \u003cstrong\u003e12\u003c/strong\u003e, 5-12, doi:10.1007/s40120-023-00469-6 (2023).\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Table 1","content":"\u003cp\u003e\u003cstrong\u003eTable 1. Overview of included studies\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"682\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eStudy\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTarget\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 51px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDesign\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber of patients\u0026dagger;\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(b, s, m, l)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePercent female\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBaseline MADRS\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFollow-up duration (years)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFitzgerald, 2018\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e(Australia)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003eBNST\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 51px;\"\u003e\n \u003cp\u003eOpen label\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e5, 5, 5, -\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e44.6 (12.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e38.6 (1.98)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003e1.5-2\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWang, 2024\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e(China)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003eBNST/NAc\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 51px;\"\u003e\n \u003cp\u003eOpen label\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e23, -, 21, -\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e32.6 (9.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e31.3 (6.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003e2\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRaymaekers, 2017\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e(Belgium)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003eVc/BNST, ITP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 51px;\"\u003e\n \u003cp\u003eRCT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e7, -, -, 7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e50 (5.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e38.1 (7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003e5.25\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBewernick, 2017\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e(Germany)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003eslMFB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 51px;\"\u003e\n \u003cp\u003eOpen label\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e8, 8, 8, -\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e41.9 (8.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e37.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e30 (7.39)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003e4\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCoenen, 2019\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e(Germany)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003eslMFB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 51px;\"\u003e\n \u003cp\u003eRCT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e16 (8 active, 8 sham), -, 14, -\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e51.6 (10.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e37.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e29.6 (4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFenoy, 2022\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e(USA)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003eslMFB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 51px;\"\u003e\n \u003cp\u003eOpen label\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e9, -, 9, -\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e50.4 (7.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e33.56 (5.39)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMillet, 2014\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e(France)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003eNAc, caudate nucleus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 51px;\"\u003e\n \u003cp\u003eOpen label\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e4, 4, 4, -\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e52 (8.28)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e32.5 (3.88)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003e1.25\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRizvi, Giacobbe, 2025\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e(Canada)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003eSCC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 51px;\"\u003e\n \u003cp\u003eRCT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e35, 35, 29, 26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e44.96 (9.33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e55.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e33.1 (2.81)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAlagapan, 2023\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e(USA)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003eSCC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 51px;\"\u003e\n \u003cp\u003eOpen label\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e10, 10, -, -\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e49.4 (11.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e28.3 (2.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAlemany, 2023\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e(Spain)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003eSCC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 51px;\"\u003e\n \u003cp\u003eOpen label\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e16, -, 16, 16\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e48.6 (9.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e27.1 (3.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003e11\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eConroy, 2021\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e(USA)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003eSCC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 51px;\"\u003e\n \u003cp\u003eOpen label\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e5, 5, -, -\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e45 (5.33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e28.5 (2.51)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003e0.75\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCrowell, 2019\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e(USA)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003eSCC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 51px;\"\u003e\n \u003cp\u003eOpen label\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e28, -, 27 ,26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e44.9 (9.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e29.5 (3.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003e8\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHoltzheimer, 2017\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e(USA, Canada,UK)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003eSCC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 51px;\"\u003e\n \u003cp\u003eRCT\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e90 (60 active, 30 sham), 80, 68, -\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003eActive - 50.53 (9.73); sham - 48.7 (0.56)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003eActive - 50; sham - 57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003eActive \u0026ndash; 33.8 (4.5); sham \u0026ndash; 37.3 (3.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003e2.5\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eKennedy, 2011\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e(Canada)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003eSCC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 51px;\"\u003e\n \u003cp\u003eOpen label\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e20, -, 16, 14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e47.4 (10.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e31.4 (4.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003e6\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLozano, 2012\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e(Canada)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003eSCC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 51px;\"\u003e\n \u003cp\u003eOpen label\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e21, -, 20, -\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e47.3 (6.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e61.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e47.4 (5.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMerkl, 2018\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e(Germany)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003eSCC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 51px;\"\u003e\n \u003cp\u003eRCT\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e8, 8, 4, -\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e48.25 (12.89)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e35 (3.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRamasubbu, 2015\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e(Canada)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003eSCC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 51px;\"\u003e\n \u003cp\u003eOpen label\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e4, 4, -, -\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e50.25 (4.19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e39.75 (3.71)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003e0.75\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRamasubbu, 2020\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e(Canada)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003eSCC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 51px;\"\u003e\n \u003cp\u003eRCT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e22 (10 LPW, 12 SPW), 22, 22, -\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e46.31 (14.35)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003eLPW - 45.5; SPW - 45.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003eLPW - 30.45 (2.7); SPW \u0026ndash; 30 (1.2)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eConen, 2018\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e(UK)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003eSCC, Vc/NAc\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 51px;\"\u003e\n \u003cp\u003eOpen label\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e7, 7, 7, -\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e48.6 (11.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e39.51 (7.48)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003e3.75\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBergfeld, 2022\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e(Netherlands)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003eVc/Vs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 51px;\"\u003e\n \u003cp\u003eOpen label\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e25, -, -, 25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e53.2 (8.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e34 (5.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003e6\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBewernick, 2012\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e(Germany)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003eNAc\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 51px;\"\u003e\n \u003cp\u003eOpen label\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e11, 11, 11, 5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e48.46 (11.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e32.3 (3.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003e2.08\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDougherty, 2015\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e(USA)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003eVc/Vs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 51px;\"\u003e\n \u003cp\u003eRCT\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e30 (16 active, 14 sham), -, 26, -\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e47.4 (12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e36.7 (4.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLai, 2023\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e(China)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003eVc/Vs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 51px;\"\u003e\n \u003cp\u003eOpen label\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e10, 10, -, -\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e33.9 (9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e29.2 (6.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003e7.4\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMalone, 2009\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e(USA)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003eVc/Vs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 51px;\"\u003e\n \u003cp\u003eOpen label\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e15, 15, 11, -\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e46.3 (10.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e73.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e34.8 (7.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber of studies (pts)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003eslMFB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 51px;\"\u003e\n \u003cp\u003eVc/Vs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003eBNST\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003eMultiple targets\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003eRCT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003eOpen label\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e3 (33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 51px;\"\u003e\n \u003cp\u003e5 (91)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e1 (5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e4 (41)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e7 (208)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e17 (221)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003e24 (429)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eSCC = subcallosal cingulate; Vc/Vs = ventral capsule/ventral striatum; BNST = bed nucleus of the stria terminalis; NAc = nucleus accumbens; slMFB = superolateral medial forebrain bundle; MADRS = Montgomery\u0026ndash;\u0026Aring;sberg Depression Rating Scale\u003c/p\u003e\n\u003cp\u003e\u0026dagger; Numbers represent N at baseline (b), short-term follow-up (s), moderate follow-up (m), and long-term follow-up (l), or \u0026ldquo;-\u0026ldquo; if not applicable\u0026nbsp;\u003c/p\u003e\n"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"nature-portfolio","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"","title":"Nature Portfolio","twitterHandle":"","acdcEnabled":false,"dfaEnabled":false,"editorialSystem":"ejp","reportingPortfolio":"","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-7238063/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7238063/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"A significant proportion of patients with major depressive disorder (MDD) experience treatment-resistant depression (TRD). Deep brain stimulation (DBS) is a surgical intervention under investigation for TRD which has shown promise in some settings but inconsistent outcomes overall. We conducted a random-effects meta-analysis of open-label and randomized controlled trials to provide an up-to-date assessment of DBS efficacy in TRD. Depressive symptoms improved across short-term (6–9 months), moderate-term (12–24 months), and long-term (\u003e24 months) time points after DBS initiation, with effect sizes (Hedges’ g) of 2.40, 2.83, and 4.33, respectively. Neither study design nor stimulation target significantly influenced outcomes, although subcallosal cingulate stimulation was generally associated with more pronounced effects. Furthermore, higher follow-up frequency correlated positively with rate of symptom improvement. Our findings support that DBS can exert sustained antidepressant effects, and provide insights that can be used to better establish its efficacy vs. placebo and optimize its clinical implementation.","manuscriptTitle":"Deep brain stimulation for major depressive disorder: A Systematic Review and Meta-Analysis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-27 07:43:39","doi":"10.21203/rs.3.rs-7238063/v1","editorialEvents":[],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"nature-mental-health","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"natmentalhealth","sideBox":"Learn more about [Nature Mental Health](https://www.nature.com/natmentalhealth/)","snPcode":"44220","submissionUrl":"https://mts-natmentalhealth.nature.com/cgi-bin/main.plex","title":"Nature Mental Health","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature Research","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"686789c9-4dda-403e-9c03-11836dddf14b","owner":[],"postedDate":"August 27th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":53577588,"name":"Biological sciences/Neuroscience/Cognitive neuroscience"},{"id":53577589,"name":"Biological sciences/Neuroscience/Emotion"},{"id":53577590,"name":"Health sciences/Diseases/Psychiatric disorders/Depression"}],"tags":[],"updatedAt":"2026-05-06T12:35:58+00:00","versionOfRecord":[],"versionCreatedAt":"2025-08-27 07:43:39","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7238063","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7238063","identity":"rs-7238063","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}