The clinical utility of autologous tumor lysate-loaded dendritic cell vaccination for patients with glioma: A systematic review and meta-analysis.

BACKGROUND: Dendritic cell (DC) vaccines show promise for glioma treatment, but optimal use remains uncertain. This meta-analysis examined DC vaccine efficacy and safety for gliomas. METHODS: This systematic review and meta-analysis study was conducted using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses. From the date of inception to October 23, 2023, electronic databases PubMed, Embase, Web of Science, and Scopus have been thoroughly evaluated. RESULTS: A total of 12 studies with 998 patients and a mean age ranging from 40.2 to 56 years were included. Across 12 articles, DC vaccine 6-month overall survival (OS) was 100% [95% confidence interval {95%CI}: 100%-100%]. Respectively, 12-month OS reported 75% [95%CI: 65%-85%] but declined to 32% [95%CI: 20%-43%] for 24-month OS. 6- and 12-month progression-free survival reached 49% [95%CI: 21%-77%] and 19% [95%CI:8%-30%]. Studying radiological outcomes shows that complete response and partial response rates were 13% [95%CI: 17%-42%], and 26% [95%CI: 10%-42%], though stable disease reached 33% [95%CI: 15%-51%], suggesting predominant antineoplastic effects. The progressive disease rate also was 24% [95%CI: 9%-57%]. CONCLUSIONS: In gliomas, DC vaccinations show a temporary efficacy; stability is more prevalent than regression. Impacts favor decreased resistance to early disease. Enhancing efficacy remains critical. Early therapy can be enhanced by appropriate supplementary therapy integration.

Safety and efficacy of flow redirection endoluminal device (FRED) for treatment of intracranial aneurysm; A systematic review and meta-analysis.

BACKGROUND: Previous research has shown promising results for treating intracranial aneurysms (IAs) with a flow redirection endoluminal device (FRED). In this systematic review and meta-analysis, we aimed to assess the safety and efficacy of this device by providing pooled estimates using the data from previous studies. METHODS: A systematic literature search of Web of Sciences, PubMed, Scopus, and Embase was performed until October 8th, 2023. After selecting the final articles, relevant data were extracted. Parameters relating to safety and efficacy were pooled using STATA software. Heterogeneity was assessed using I-squared and Cochran's Q. Funnel plots and Egger's regression methods were used to evaluate publication bias. Sensitivity analysis was also performed using the leave-one-out method. RESULTS: The data of 37 studies were used for meta-analysis. The rates of immediate adequate occlusion and complete occlusion were 0.51 (95% CI: 0.31-0.71) and 0.34 (95% CI: 0.16-0.53), respectively, while the rates of the adequate and complete occlusion at the latest follow-up were 0.90 (95% CI: 0.84-0.94) and 0.75 (95% CI: 0.65-0.84), respectively. The periprocedural complications rate was 0.04 (95% CI: 0.03-0.06), and the overall complications rate was 0.12 (95% CI: 0.09-0.15). The rate of good functional outcome was 0.99 (95% CI: 0.99-1.00) and the successful implantation rate was 1.00 (95% CI: 1.00-1.00). There was substantial heterogeneity among the reports for most of the evaluated parameters. CONCLUSION: FRED had high safety and efficacy in treating IAs, as evidenced by its high occlusion and low complication rates.

Predicting telomerase reverse transcriptase promoter mutation in glioma: A systematic review and diagnostic meta-analysis on machine learning algorithms.

BACKGROUND: Glioma is one of the most common primary brain tumors. The presence of the telomerase reverse transcriptase promoter (pTERT) mutation is associated with a better prognosis. This study aims to investigate the TERT mutation in patients with glioma using machine learning (ML) algorithms on radiographic imaging. METHOD: This study was prepared according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The electronic databases of PubMed, Embase, Scopus, and Web of Science were searched from inception to August 1, 2023. The statistical analysis was performed using the MIDAS package of STATA v.17. RESULTS: A total of 22 studies involving 5371 patients were included for data extraction, with data synthesis based on 11 reports. The analysis revealed a pooled sensitivity of 0.86 (95% CI: 0.78-0.92) and a specificity of 0.80 (95% CI 0.72-0.86). The positive and negative likelihood ratios were 4.23 (95% CI: 2.99-5.99) and 0.18 (95% CI: 0.11-0.29), respectively. The pooled diagnostic score was 3.18 (95% CI: 2.45-3.91), with a diagnostic odds ratio 24.08 (95% CI: 11.63-49.87). The Summary Receiver Operating Characteristic (SROC) curve had an area under the curve (AUC) of 0.89 (95% CI: 0.86-0.91). CONCLUSION: The study suggests that ML can predict TERT mutation status in glioma patients. ML models showed high sensitivity (0.86) and moderate specificity (0.80), aiding disease prognosis and treatment planning. However, further development and improvement of ML models are necessary for better performance metrics and increased reliability in clinical practice.

Anti-PD-1/PD-L1 inhibitor therapy for melanoma brain metastases: a systematic review and meta-analysis.

Melanoma brain metastases present a major challenge in cancer treatment and reduce overall survival despite advances in managing primary melanoma. Immune checkpoint inhibitors (ICIs) that target PD-1/PD-L1 pathways have shown promise in treating advanced melanoma, but their efficacy for melanoma brain metastases is debated. This systematic review and meta-analysis summarize evidence on anti-PD-1/PD-L1 inhibitors for melanoma brain metastases. This systematic review and meta-analysis followed PRISMA guidelines. PICO criteria targeted melanoma brain metastasis patients treated with PD-1/PD-L1 inhibitors, assessing overall survival, progression-free survival, and complications. Inclusion criteria were English studies on humans using PD-1/PD-L1 inhibitors for melanoma brain metastases with > 10 patients. A total of 22 trials involving 1523 melanoma brain metastase patients treated with anti-PD-1/PD-L1 inhibitors were thoroughly analyzed. Our findings show the 6-month OS rate of 0.75 [95%CI:0.67-0.84], the 6-months PFS rate of 0.42 [95%CI:0.31-0.52], the 1-year OS rate of 0.63 [95%CI:0.52-0.74], the 1-year PFS rate was 0.45 [95%CI:0.32-0.58], the 18-months OS rate of 0.52 [95%CI:0.37-0.67], the 2-year OS rate of 50% [95% CI: (34%-65%)], the 2 year PFS rate of 0.36 (95%CI:0.23-0.50), the 3-year OS rate of 0.42 (95%CI:0.17-0.67), the 4-year PFS rate of 0.35 [95%CI:0.08-0.61], the 4-year OS rate of 0.29 [95%CI:0.01-0.56], the 5-year OS rate of 0.29 (95%CI:0.09-0.50), and the 5-year PFS rate of 0.11 (95%CI:0.03-0.19). The combined disease stability rate was 0.13 [95%CI:0.05-0.20], the progressive disease rate was 0.49 [95%CI:0.37-0.62], the partial response rate was 0.14 [95%CI:0.07-0.20], the object response rate was 0.35 [95%CI:0.24-0.46], and the complete response rate was 0.22 [95%CI:0.12-0.32]. In conclusion, our meta-analysis provides compelling evidence supporting the efficacy of PD-1/PD-L1 inhibitors in patients with melanoma brain tumors, as evidenced by favorable survival outcomes and disease control rates.

Stereotactic radiosurgery versus combined stereotactic radiosurgery and bevacizumab for recurrent glioblastoma; a systematic review and meta-analysis of survival.

Recurrent glioblastoma (rGBM) is a brain tumor that is resistant to standard treatments. Although stereotactic radiosurgery (SRS) is a non-invasive radiation technique, it cannot fully prevent tumor recurrence and progression. Bevacizumab blocks tumor blood supply and has been approved for rGBM. However, the best way to combine SRS and bevacizumab is still unclear. We did a systematic review and meta-analysis of studies comparing SRS alone and SRS plus bevacizumab for rGBM. We searched three databases for articles published until June 2023. All statistical analysis was performed by STATA v.17. Our meta-analysis included 20 studies with 926 patients. We found that the combination therapy had a significantly lower rate of overall survival (OS) than SRS alone at 6-month 0.77[95%CI:0.74-0.85] for SRS alone and (100%) for SRS plus bevacizumab. At 1-year OS, 0.39 [95%CI: 0.32-0.47] for SRS alone and 0.61 [95%CI:0.44-0.77] for SRS plus bevacizumab (P-value:0.02). However, this advantage was not seen in the long term (18 months and two years). Additionally, the combination therapy had lower chances of progression-free survival (PFS) than SRS alone at the 6-month and 1-year time points, but the differences were insignificant. Our study indicates that incorporating bevacizumab with SRS may lead to a short-term increase in OS for rGBM patients but not long-term. Additionally, the PFS rate did not show significant improvement in the group receiving combination therapy. Further clinical trials are necessary to validate the enhanced overall survival with combination therapy for rGBM.

Repeat single-session stereotactic radiosurgery for arteriovenous malformation: a systematic review and meta-analysis.

BACKGROUND: Stereotactic radiosurgery is the preferred option for treating brain arteriovenous malformation (AVM) when the risks associated with surgery outweigh the potential benefits. However, some patients require repeat radiosurgery due to residual AVM after the first procedure. This systematic review and meta-analysis aimed to investigate the safety and efficacy of repeated procedure of radiosurgery for AVM. METHOD: A systematic review was conducted according to the PRISMA guideline. The search was conducted on PubMed, Scopus, Embase, and Web of Science, using a pre-designed search string. Studies investigating the efficacy of repeat radiosurgery for residual AVM following initial single session radiosurgery were included. The risk of bias was assessed using the JBI tool. Meta-analysis and met-regression were performed to pool and inspect data. RESULTS: Our meta-analysis, with a mean follow-up of 45.57 months, reveals repeat radiosurgery as a viable option for arteriovenous malformations (AVMs), achieving a 60.82% obliteration rate with a mean time to obliteration of 33.18 months. Meta-regression identifies AVM volume and Spetzler-Martin (SM) grade as factors influencing obliteration, with smaller volume and lower SM grades associated with higher rates. Complications include 10.33% radiation-induced changes, 5.26% post-radiosurgery hemorrhage, 2.56% neurologic deficits, and 0.67% cyst formation. Heterogeneity in complications is primarily attributed to male proportion and SM grade, while factors influencing post-radiosurgery hemorrhage remain unclear. The type of radiosurgery, whether Gamma Knife Radiosurgery (GKRS) or LINAC, does not significantly impact outcomes. CONCLUSION: Repeat radiosurgery is a feasible, effective, and safe treatment for AVMs following failure of initial radiosurgery. When utilized in appropriate patient subgroups, it provides an acceptable risk-to-benefit profile. Feature studies are required to clarify its clear indications.

Prediction of the treatment response and local failure of patients with brain metastasis treated with stereotactic radiosurgery using machine learning: A systematic review and meta-analysis.

BACKGROUND: Stereotactic radiosurgery (SRS) effectively treats brain metastases. It can provide local control, symptom relief, and improved survival rates, but it poses challenges in selecting optimal candidates, determining dose and fractionation, monitoring for toxicity, and integrating with other modalities. Practical tools to predict patient outcomes are also needed. Machine learning (ML) is currently used to predict treatment outcomes. We aim to investigate the accuracy of ML in predicting treatment response and local failure of brain metastasis treated with SRS. METHODS: PubMed, Scopus, Web of Science (WoS), and Embase were searched until April 16th, which was repeated on October 17th, 2023 to find possible relevant papers. The study preparation adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guideline. The statistical analysis was performed by the MIDAS package of STATA v.17. RESULTS: A total of 17 articles were reviewed, of which seven and eleven were related to the clinical use of ML in predicting local failure and treatment response. The ML algorithms showed sensitivity and specificity of 0.89 (95% CI: 0.84-0.93) and 0.87 (95% CI: 0.81-0.92) for predicting treatment response. The positive likelihood ratio was 7.1 (95% CI: 4.5-11.1), the negative likelihood ratio was 0.13 (95% CI: 0.08-0.19), and the diagnostic odds ratio was 56 (95% CI: 25-125). Moreover, the pooled estimates for sensitivity and specificity of ML algorithms for predicting local failure were 0.93 (95% CI: 0.76-0.98) and 0.80 (95% CI: 0.53-0.94). The positive likelihood ratio was 4.7 (95% CI: 1.6-14.0), the negative likelihood ratio was 0.09 (95% CI: 0.02-0.39), and the diagnostic odds ratio was 53 (95% CI: 5-606). CONCLUSION: ML holds promise in predicting treatment response and local failure in brain metastasis patients receiving SRS. However, further studies and improvements in the treatment process can refine the models and effectively integrate them into clinical practice.

The safety and efficacy of dabrafenib and trametinib in patients with glioma: A systematic review and meta-analysis.

BACKGROUND: Dabrafenib and trametinib represent targeted therapy options under investigation for treatment of gliomas harboring BRAF V600 mutations. We systematically reviewed the literature and conducted meta-analyses to assess the efficacy and safety of these agents. METHODS: PubMed, Embase, and Scopus were searched from inception to September 2023 for studies examining dabrafenib and/or trametinib for gliomas. Outcomes included response rates (ORR, CR, PR), progression rates (PD), 6- and 12-month PFS, adverse events, and dosing modifications. Meta-analyses were conducted using random effect models. RESULTS: Nine studies met the inclusion criteria. Meta-analysis demonstrated overall response rates (ORR) of 50% (95% confidence interval (CI): 35-65%) for low-grade gliomas (LGG) and 40% (95% CI: 29-51%) for high-grade gliomas (HGG). Pooled ORR was 45% (95% CI: 36-54%) for both glioma grades. The complete response rate was 13% (95% CI: 05-27%) for HGG and 5% (95% CI: 1-10%) for both LGG and HGG. Six-month progression-free survival (PFS) rates reached 87% in LGG and 67% in HGG and a pooled 6-month PFS 78% (95% CI: 58-98%), declining at 12 months to 67% and 44%, respectively, with a pooled 12-month PFS 56% (95% CI: 34-79%). Grade 1-4 adverse events occurred in 100% of LGG and 63% of HGG patients. CONCLUSIONS: Dabrafenib and trametinib demonstrate promising anti-tumor efficacy in gliomas, particularly low-grade tumors, achieving durable disease stabilization in many patients. However, toxicity significantly limited tolerability. Additional research should further examine efficacy and refine safe administration protocols across glioma subtypes.

Prediction of cerebral aneurysm rupture risk by machine learning algorithms: a systematic review and meta-analysis of 18,670 participants.

It is possible to identify unruptured intracranial aneurysms (UIA) using machine learning (ML) algorithms, which can be a life-saving strategy, especially in high-risk populations. To better understand the importance and effectiveness of ML algorithms in practice, a systematic review and meta-analysis were conducted to predict cerebral aneurysm rupture risk. PubMed, Scopus, Web of Science, and Embase were searched without restrictions until March 20, 2023. Eligibility criteria included studies that used ML approaches in patients with cerebral aneurysms confirmed by DSA, CTA, or MRI. Out of 35 studies included, 33 were cohort, and 11 used digital subtraction angiography (DSA) as their reference imaging modality. Middle cerebral artery (MCA) and anterior cerebral artery (ACA) were the commonest locations of aneurysmal vascular involvement-51% and 40%, respectively. The aneurysm morphology was saccular in 48% of studies. Ten of 37 studies (27%) used deep learning techniques such as CNNs and ANNs. Meta-analysis was performed on 17 studies: sensitivity of 0.83 (95% confidence interval (CI), 0.77-0.88); specificity of 0.83 (95% CI, 0.75-0.88); positive DLR of 4.81 (95% CI, 3.29-7.02) and the negative DLR of 0.20 (95% CI, 0.14-0.29); a diagnostic score of 3.17 (95% CI, 2.55-3.78); odds ratio of 23.69 (95% CI, 12.75-44.01). ML algorithms can effectively predict the risk of rupture in cerebral aneurysms with good levels of accuracy, sensitivity, and specificity. However, further research is needed to enhance their diagnostic performance in predicting the rupture status of IA.

The performance of Machine Learning for prediction of H3K27M Mutation in Midline Gliomas; A Systematic Review and Meta-Analysis.

BACKGROUND: Diffuse midline gliomas (DMGs) encompass a set of tumors, and those tumors with H3K27M mutation carry a poor prognosis. In recent years, machine learning (ML)-based radiomics have shown promising results in predicting gene mutation status non-invasively. Therefore, this study aims to comprehensively evaluate the diagnostic performance of ML-based magnetic resonance imaging (MRI) radiomics in predicting H3K27M mutation status in DMG patients. METHODS: A systematic search was conducted using relevant keywords in PubMed/Medline, Scopus, Embase, and Web of Science from inception to May 2023. Original studies evaluating the diagnostic performance of ML models in predicting H3K27M mutation status in DMGs were enrolled. Quality assessment of the enrolled studies was conducted using QUADAS-2. Data were analyzed using STATA version 17.0 to calculate pooled sensitivity, specificity, positive (PLR) and negative likelihood ratio (NLR), diagnostic score, and diagnostic odds ratio (DOR). RESULTS: A total of 13 studies, including 12 retrospectives and one both retrospective and prospective study, enrolled 1510 (male=777) DMG patients. Six studies underwent meta-analysis which showed a pooled sensitivity, specificity, PLR, NLR, diagnostic score, and DOR of 0.91 (95% CI 0.77-0.97), 0.81 (95% CI 0.73-0.88), 4.86 (95% CI 3.25-7.24), 0.11 (95% CI 0.04-0.29), 3.75 (95% CI 2.62-4.88), and 42.61 (95% CI 13.77-131.87), respectively. CONCLUSION: Non-invasive prediction of H3K27M mutation status in patients with DMGs using MRI radiomics is a promising tool with good diagnostic performance. However, the pooled metrics had a wide confidence interval, which required further studies to enhance ML algorithms' accuracy and facilitate their integration into daily clinical practice.

The Safety and Efficacy of eCLIPs for Treatment of Wide-Necked Bifurcation Aneurysms: A Systematic Review and Meta-Analysis.

BACKGROUND: Wide-necked bifurcation aneurysms (WNBAs) are challenging intracranial aneurysms. Several device and treatment approaches have been proposed for the treatment of WNBAs. The endovascular clip system (eCLIPs) is a newly developed endovascular device with flow diverter and flow disruptor features. This study aims to investigate the safety and efficacy of the eCLIPs for treatment of patients with WNBAs. METHODS: This is a systematic review and meta-analysis study conducted in accordance with the PRISMA (preferred reporting items for systematic reviews and meta-analyses) guidelines. The electronic databases of PubMed, Embase, Scopus, and Web of Science were systematically reviewed from inception to June 19, 2023. The rate of complete and near-complete occlusion, successful device implantation, and serious adverse events were pooled using STATA, version 17. RESULTS: A total of 5 studies with 110 patients with WNBAs were systematically investigated. Our findings show that the immediate successful implantation rate of eCLIPs was 0.93 (95% confidence interval [CI], 0.88-0.97). Moreover, the immediate postoperative complete occlusion rate was 0.34 (95% CI, 0.10-0.58), and the immediate postoperative near-complete occlusion rate was 0.35 (95% CI, 0.24-0.45). Also, the near-complete occlusion rate at the latest follow-up was 0.3 (95% CI, 0.16-0.44). The serious adverse event rate was 0.14 (95% CI, 0.05-0.22). Stroke was also reported in 2 studies, with 1 study reporting 1 patient who experienced stroke within the first 24 hours and 1 study reporting no patients with stroke. CONCLUSIONS: Our findings document that the eCLIPs is a safe and effective device for treating patients with WNBAs and associated with favorable outcomes.