The safety and efficacy of bevacizumab in treatment of recurrent low-grade glioma: a systematic review and meta-analysis

BACKGROUND

Central nervous system (CNS) tumors are among the most common malignancies in various age ranges. Low-grade glioma (LGG) can account for nearly 30% of pediatric CNS malignancies. Progression or recurrence after the first-line treatments is common among these patients. Therefore, more treatments are required. Bevacizumab as an anti-VEGF antibody has come into the spotlight recently and is especially used in relapse or recurrence settings. This review aims to study the safety and efficacy of bevacizumab for patients with recurrent LGG.

METHODS

This study was conducted according to The Preferred Reporting Items for Systematic Reviews and Meta-Analyses. PubMed, Scopus, Web of Science, and Embase were comprehensively searched using the relevant key terms until 24th August 2023 to retrieve the studies that investigated clinical outcomes of bevacizumab in patients with recurrent LGG. All statistical analysis was performed by STATA v.17.

RESULTS

A total of 1306 papers were gathered, out of which 13 were incorporated in the meta-analysis. The pooled incidence rate of treatment according to the RANO scale was 70% (95% CI = 43-98%) for objective response rate, 26% (95% CI = 58-96%) for partial response, 21% (95% CI = 15-28%) for minor response, 14% (95% CI = 3-24%) for complete response, 48% (95% CI = 37-59%) for stable disease, and 8% (95% CI = 4-11%) for progressive disease. Furthermore, according to progressive survival after treatment, it was 4% (95% CI = -1 to 9%) for 6-month PFS, 41% (95% CI = 32-50%) for 2-year PFS, and 29% (95% CI = 22-35%) for 3-year PFS.

CONCLUSION

According to the RANO scale and PFS, clinicians should be aware that Bevacizumab could be a favorable alternative therapy for recurrent LGG. Furthermore, bevacizumab exhibits minimal toxicity and high tolerability in recurrent LGG.

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.

Woven endo bridge device for recurrent intracranial aneurysms: A systematic review and meta-analysis

BACKGROUND

Recurrent intracranial aneurysms present a significant clinical challenge, demanding innovative and effective treatment approaches. The Woven EndoBridge (WEB) device has emerged as a promising endovascular solution for managing these intricate cases. This study aims to assess the safety and efficacy of the WEB device in treating recurrent intracranial aneurysms.

METHODS

We conducted a comprehensive search across multiple databases, including PubMed, Scopus, Embase, and Web of Science, from inception to June 5, 2023. Eligible studies focused on evaluating WEB device performance and included a minimum of five patients with recurrent intracranial aneurysms. The complete and adequate occlusion rates, neck remnant rates, and periprocedural complication rates were pooled using SATA V.17.

RESULTS

Our analysis included five studies collectively enrolling 73 participants. Participant ages ranged from 52.9 to 65 years, with 64.4% being female. Aneurysms were wide-necked and predominantly located in the middle cerebral artery, basilar artery, and anterior cerebral artery. Previous treatments encompassed coiling, clipping, and the use of WEB devices. Our study found an overall adequate occlusion rate of 0.80 (95% CI 0.71-0.89), a complete occlusion rate of 0.39 (95% CI 0.28-0.50), and a neck remnant rate of 0.38 (95% CI 0.27-0.48). Periprocedural complications were reported at a rate of 0%, although heterogeneity was observed in this data. Notably, evidence of publication bias was identified in the reporting of periprocedural complication rates.

CONCLUSION

Our findings suggest that the WEB device is associated with favorable outcomes for treating recurrent wide-neck intracranial aneurysms.

Determination of the pesticide naptalam and its degradation products by positive and negative ion mass spectrometry

N-1-Naphthylphtalamic acid (naptalam) and its degradation products, 1-naphthylamine and N-(1-naphthyl) phthalimide were simultaneously determined in river water by two independent mass spectrometric (MS) methods. These were negative ion MS (NIMS) and programmable temperature vaporizer gas chromatography mass spectrometry (PTV-GC MS) with electron impact ionization (positive ions). Prior to the NIMS analysis, the samples were preconcentrated by solid phase extraction (SPE) of C18 membrane discs. The PTV-GC MS studies were performed without any preconcentration procedure. Selected ion monitoring (SIM) and internal standardization with naphthalene were applied in both methods. The limits of determination (LOD) of NIMS studies were 230, 270 and 260 ng L-1 for naptalam, 1-naphthylamine and N-(1-naphthyl) phthalimide, respectively, with relative standard deviation (RSD) < 1% (n = 5) and of PTV-GC MS 17, 11 and 15 ng L-1 (RSD < 0.7%, n = 5). The LOD, linearity, RSD and time required for these methods are far better than for HPLC analyses.