Cognitive enhancing effect of rTMS combined with tDCS in patients with major depressive disorder: a double-blind, randomized, sham-controlled study.
Cognitive dysfunction is one of the common symptoms in patients with major depressive disorder (MDD). Repetitive transcranial magnetic stimulation (rTMS) and transcranial direct current stimulation (tDCS) have been studied separately in the treatment of cognitive dysfunction in MDD patients. We aimed to investigate the effectiveness and safety of rTMS combined with tDCS as a new therapy to improve neurocognitive impairment in MDD patients.
In this brief 2-week, double-blind, randomized, and sham-controlled trial, a total of 550 patients were screened, and 240 MDD inpatients were randomized into four groups (active rTMS + active tDCS, active rTMS + sham tDCS, sham rTMS + active tDCS, sham rTMS + sham tDCS). Finally, 203 patients completed the study and received 10 treatment sessions over a 2-week period. The Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) was performed to assess patients' cognitive function at baseline and week 2. Also, we applied the 24-item Hamilton Depression Rating Scale (HDRS-24) to assess patients' depressive symptoms at baseline and week 2.
After 10 sessions of treatment, the rTMS combined with the tDCS group showed more significant improvements in the RBANS total score, immediate memory, and visuospatial/constructional index score (all p < 0.05). Moreover, post hoc tests revealed a significant increase in the RBANS total score and Visuospatial/Constructional in the combined treatment group compared to the other three groups but in the immediate memory, the combined treatment group only showed a better improvement than the sham group. The results also showed the RBANS total score increased significantly higher in the active rTMS group compared with the sham group. However, rTMS or tDCS alone was not superior to the sham group in terms of other cognitive performance. In addition, the rTMS combined with the tDCS group showed a greater reduction in HDRS-24 total score and a better depression response rate than the other three groups.
rTMS combined with tDCS treatment is more effective than any single intervention in treating cognitive dysfunction and depressive symptoms in MDD patients.
Chinese Clinical Trial Registry (ChiCTR2100052122).
Li X
，Liu J
，Wei S
，Yu C
，Wang D
，Li Y
，Li J
，Zhuang W
，Luo RC
，Li Y
，Liu Z
，Su Y
，Liu J
，Xu Y
，Fan J
，Zhu G
，Xu W
，Tang Y
，Yan H
，Cho RY
，Kosten TR
，Zhou D
，Zhang X
... -
《BMC Medicine》
Repetitive transcranial magnetic stimulation for post-traumatic stress disorder in adults.
The estimated lifetime prevalence of post-traumatic stress disorder (PTSD) in adults worldwide has been estimated at 3.9%. PTSD appears to contribute to alterations in neuronal network connectivity patterns. Current pharmacological and psychotherapeutic treatments for PTSD are associated with inadequate symptom improvement and high dropout rates. Repetitive transcranial magnetic stimulation (rTMS), a non-invasive therapy involving induction of electrical currents in cortical brain tissue, may be an important treatment option for PTSD to improve remission rates and for people who cannot tolerate existing treatments.
To assess the effects of repetitive transcranial magnetic stimulation (rTMS) on post-traumatic stress disorder (PTSD) in adults.
We searched the Cochrane Common Mental Disorders Controlled Trials Register, CENTRAL, MEDLINE, Embase, three other databases, and two clinical trials registers. We checked reference lists of relevant articles. The most recent search was January 2023.
We included randomized controlled trials (RCTs) assessing the efficacy and safety of rTMS versus sham rTMS for PTSD in adults from any treatment setting, including veterans. Eligible trials employed at least five rTMS treatment sessions with both active and sham conditions. We included trials with combination interventions, where a pharmacological agent or psychotherapy was combined with rTMS for both intervention and control groups. We included studies meeting the above criteria regardless of whether they reported any of our outcomes of interest.
Two review authors independently extracted data and assessed the risk of bias in accordance with Cochrane standards. Primary outcomes were PTSD severity immediately after treatment and serious adverse events during active treatment. Secondary outcomes were PTSD remission, PTSD response, PTSD severity at two follow-up time points after treatment, dropouts, and depression and anxiety severity immediately after treatment.
We included 13 RCTs in the review (12 published; 1 unpublished dissertation), with 577 participants. Eight studies included stand-alone rTMS treatment, four combined rTMS with an evidence-based psychotherapeutic treatment, and one investigated rTMS as an adjunctive to treatment-as-usual. Five studies were conducted in the USA, and some predominantly included white, male veterans. Active rTMS probably makes little to no difference to PTSD severity immediately following treatment (standardized mean difference (SMD) -0.14, 95% confidence interval (CI) -0.54 to 0.27; 3 studies, 99 participants; moderate-certainty evidence). We downgraded the certainty of evidence by one level for imprecision (sample size insufficient to detect a difference of medium effect size). We deemed one study as having a low risk of bias and the remaining two as having 'some concerns' for risk of bias. A sensitivity analysis of change-from-baseline scores enabled inclusion of a greater number of studies (6 studies, 252 participants). This analysis yielded a similar outcome to our main analysis but also indicated significant heterogeneity in efficacy across studies, including two studies with a high risk of bias. Reported rates of serious adverse events were low, with seven reported (active rTMS: 6; sham rTMS: 1). The evidence is very uncertain about the effect of active rTMS on serious adverse events (odds ratio (OR) 5.26, 95% CI 0.26 to 107.81; 5 studies, 251 participants; very low-certainty evidence [Active rTMS: 23/1000, sham rTMS: 4/1000]). We downgraded the evidence by one level for risk of bias and two levels for imprecision. We rated four of five studies as having a high risk of bias, and the fifth as 'some concerns' for bias. We were unable to assess PTSD remission immediately after treatment as none of the included studies reported this outcome.
Based on moderate-certainty evidence, our review suggests that active rTMS probably makes little to no difference to PTSD severity immediately following treatment compared to sham stimulation. However, significant heterogeneity in efficacy was detected when we included a larger number of studies in sensitivity analysis. We observed considerable variety in participant and protocol characteristics across studies included in this review. For example, studies tended to be weighted towards inclusion of either male veterans or female civilians. Studies varied greatly in terms of the proportion of the sample with comorbid depression. Study protocols differed in treatment design and stimulation parameters (e.g. session number/duration, treatment course length, stimulation intensity/frequency, location of stimulation). These differences may affect efficacy, particularly when considering interactions with participant factors. Reported rates of serious adverse events were very low (< 1%) across active and sham conditions. It is uncertain whether rTMS increases the risk of serious adverse event occurrence, as our certainty of evidence was very low. Studies frequently lacked clear definitions for serious adverse events, as well as detail on tracking/assessment of data and information on the safety population. Increased reporting on these elements would likely aid the advancement of both research and clinical recommendations of rTMS for PTSD. Currently, there is insufficient evidence to meta-analyze PTSD remission, PTSD treatment response, and PTSD severity at different periods post-treatment. Further research into these outcomes could inform the clinical use of rTMS. Additionally, the relatively large contribution of data from trials that focused on white male veterans may limit the generalizability of our conclusions. This could be addressed by prioritizing recruitment of more diverse participant samples.
Brown R
，Cherian K
，Jones K
，Wickham R
，Gomez R
，Sahlem G
... -
《Cochrane Database of Systematic Reviews》
Comparison of Two Modern Survival Prediction Tools, SORG-MLA and METSSS, in Patients With Symptomatic Long-bone Metastases Who Underwent Local Treatment With Surgery Followed by Radiotherapy and With Radiotherapy Alone.
Survival estimation for patients with symptomatic skeletal metastases ideally should be made before a type of local treatment has already been determined. Currently available survival prediction tools, however, were generated using data from patients treated either operatively or with local radiation alone, raising concerns about whether they would generalize well to all patients presenting for assessment. The Skeletal Oncology Research Group machine-learning algorithm (SORG-MLA), trained with institution-based data of surgically treated patients, and the Metastases location, Elderly, Tumor primary, Sex, Sickness/comorbidity, and Site of radiotherapy model (METSSS), trained with registry-based data of patients treated with radiotherapy alone, are two of the most recently developed survival prediction models, but they have not been tested on patients whose local treatment strategy is not yet decided.
(1) Which of these two survival prediction models performed better in a mixed cohort made up both of patients who received local treatment with surgery followed by radiotherapy and who had radiation alone for symptomatic bone metastases? (2) Which model performed better among patients whose local treatment consisted of only palliative radiotherapy? (3) Are laboratory values used by SORG-MLA, which are not included in METSSS, independently associated with survival after controlling for predictions made by METSSS?
Between 2010 and 2018, we provided local treatment for 2113 adult patients with skeletal metastases in the extremities at an urban tertiary referral academic medical center using one of two strategies: (1) surgery followed by postoperative radiotherapy or (2) palliative radiotherapy alone. Every patient's survivorship status was ascertained either by their medical records or the national death registry from the Taiwanese National Health Insurance Administration. After applying a priori designated exclusion criteria, 91% (1920) were analyzed here. Among them, 48% (920) of the patients were female, and the median (IQR) age was 62 years (53 to 70 years). Lung was the most common primary tumor site (41% [782]), and 59% (1128) of patients had other skeletal metastases in addition to the treated lesion(s). In general, the indications for surgery were the presence of a complete pathologic fracture or an impending pathologic fracture, defined as having a Mirels score of ≥ 9, in patients with an American Society of Anesthesiologists (ASA) classification of less than or equal to IV and who were considered fit for surgery. The indications for radiotherapy were relief of pain, local tumor control, prevention of skeletal-related events, and any combination of the above. In all, 84% (1610) of the patients received palliative radiotherapy alone as local treatment for the target lesion(s), and 16% (310) underwent surgery followed by postoperative radiotherapy. Neither METSSS nor SORG-MLA was used at the point of care to aid clinical decision-making during the treatment period. Survival was retrospectively estimated by these two models to test their potential for providing survival probabilities. We first compared SORG to METSSS in the entire population. Then, we repeated the comparison in patients who received local treatment with palliative radiation alone. We assessed model performance by area under the receiver operating characteristic curve (AUROC), calibration analysis, Brier score, and decision curve analysis (DCA). The AUROC measures discrimination, which is the ability to distinguish patients with the event of interest (such as death at a particular time point) from those without. AUROC typically ranges from 0.5 to 1.0, with 0.5 indicating random guessing and 1.0 a perfect prediction, and in general, an AUROC of ≥ 0.7 indicates adequate discrimination for clinical use. Calibration refers to the agreement between the predicted outcomes (in this case, survival probabilities) and the actual outcomes, with a perfect calibration curve having an intercept of 0 and a slope of 1. A positive intercept indicates that the actual survival is generally underestimated by the prediction model, and a negative intercept suggests the opposite (overestimation). When comparing models, an intercept closer to 0 typically indicates better calibration. Calibration can also be summarized as log(O:E), the logarithm scale of the ratio of observed (O) to expected (E) survivors. A log(O:E) > 0 signals an underestimation (the observed survival is greater than the predicted survival); and a log(O:E) < 0 indicates the opposite (the observed survival is lower than the predicted survival). A model with a log(O:E) closer to 0 is generally considered better calibrated. The Brier score is the mean squared difference between the model predictions and the observed outcomes, and it ranges from 0 (best prediction) to 1 (worst prediction). The Brier score captures both discrimination and calibration, and it is considered a measure of overall model performance. In Brier score analysis, the "null model" assigns a predicted probability equal to the prevalence of the outcome and represents a model that adds no new information. A prediction model should achieve a Brier score at least lower than the null-model Brier score to be considered as useful. The DCA was developed as a method to determine whether using a model to inform treatment decisions would do more good than harm. It plots the net benefit of making decisions based on the model's predictions across all possible risk thresholds (or cost-to-benefit ratios) in relation to the two default strategies of treating all or no patients. The care provider can decide on an acceptable risk threshold for the proposed treatment in an individual and assess the corresponding net benefit to determine whether consulting with the model is superior to adopting the default strategies. Finally, we examined whether laboratory data, which were not included in the METSSS model, would have been independently associated with survival after controlling for the METSSS model's predictions by using the multivariable logistic and Cox proportional hazards regression analyses.
Between the two models, only SORG-MLA achieved adequate discrimination (an AUROC of > 0.7) in the entire cohort (of patients treated operatively or with radiation alone) and in the subgroup of patients treated with palliative radiotherapy alone. SORG-MLA outperformed METSSS by a wide margin on discrimination, calibration, and Brier score analyses in not only the entire cohort but also the subgroup of patients whose local treatment consisted of radiotherapy alone. In both the entire cohort and the subgroup, DCA demonstrated that SORG-MLA provided more net benefit compared with the two default strategies (of treating all or no patients) and compared with METSSS when risk thresholds ranged from 0.2 to 0.9 at both 90 days and 1 year, indicating that using SORG-MLA as a decision-making aid was beneficial when a patient's individualized risk threshold for opting for treatment was 0.2 to 0.9. Higher albumin, lower alkaline phosphatase, lower calcium, higher hemoglobin, lower international normalized ratio, higher lymphocytes, lower neutrophils, lower neutrophil-to-lymphocyte ratio, lower platelet-to-lymphocyte ratio, higher sodium, and lower white blood cells were independently associated with better 1-year and overall survival after adjusting for the predictions made by METSSS.
Based on these discoveries, clinicians might choose to consult SORG-MLA instead of METSSS for survival estimation in patients with long-bone metastases presenting for evaluation of local treatment. Basing a treatment decision on the predictions of SORG-MLA could be beneficial when a patient's individualized risk threshold for opting to undergo a particular treatment strategy ranged from 0.2 to 0.9. Future studies might investigate relevant laboratory items when constructing or refining a survival estimation model because these data demonstrated prognostic value independent of the predictions of the METSSS model, and future studies might also seek to keep these models up to date using data from diverse, contemporary patients undergoing both modern operative and nonoperative treatments.
Level III, diagnostic study.
Lee CC
，Chen CW
，Yen HK
，Lin YP
，Lai CY
，Wang JL
，Groot OQ
，Janssen SJ
，Schwab JH
，Hsu FM
，Lin WH
... -
《-》
ResearchGate
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钛学术
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