Different doses of bevacizumab in combination with chemotherapy for advanced colorectal cancer: a meta-analysis and Bayesian analysis.

OBJECTIVE: The aim of the present study was to explore the incremental benefit of bevacizumab (Bev) in the treatment of advanced colorectal cancer (CRC) with different doses. METHODS: A literature search of eight electronic databases (China National Knowledge Infrastructure, Wanfang databases, Chinese Biomedical Database, VIP medicine information, Cochrane Library, MEDLINE, PubMed, and EMBASE) was conducted from database creation to December 2022. Randomized controlled trials (RCTs) that compared Bev at various dosages + chemotherapy (CT) versus placebo (or blank control) + CT were selected. The overall survival (OS), progression-free survival (PFS), overall response rate (ORR; complete response [CR] + partial response [PR]), and grade ≥ 3 adverse events (AEs) were integrated first by pooled analysis. The likelihood of ideal dosage of Bev was then ranked using random effects within Bayesian analysis. RESULTS: Twenty-six RCTs involving 18,261 patients met the inclusion criteria. OS increased significantly after using 5 mg (HR: 0.87, 95% CI 0.75 to 1.00) and 10 mg dosages of Bev (HR: 0.75, 95% CI 0.66 to 0.85) with CT, but statistical significance was not attained for the 7.5 mg dose (HR: 0.95, 95% CI 0.83 to 1.08). A significantly increased in PFS with doses of 5 mg (HR: 0.69, 95% CI 0.58 to 0.83), 7.5 mg (HR: 0.81, 95% CI 0.66 to 1.00), and 10 mg (HR: 0.60, 95% CI 0.53 to 0.68). ORR distinctly increased after 5 mg (RR: 1.34, 95% CI 1.15 to 1.55), 7.5 mg (RR: 1.25, 95% CI 1.05 to 1.50), and10 mg (RR: 2.27, 95% CI 1.82 to 2.84) doses were administered. Grade ≥ 3 AEs increased clearly in 5 mg (RR: 1.11, 95% CI 1.04 to 1.20) compared to 7.5 mg (RR: 1.05, 95% CI 0.82 to 1.35) and 10 mg (RR: 1.15, 95% CI 0.98 to 1.36). Bayesian analysis demonstrated that 10 mg Bev obtained the maximum time of OS (HR: 0.75, 95% CrI 0.58 to 0.97; probability rank = 0.05) indirectly compared to 5 mg and 7.5 mg Bev. Compared with 5 mg and 7.5 mg Bev, 10 mg Bev also holds the longest duration for PFS (HR: 0.59, 95% CrI 0.43 to 0.82; probability rank = 0.00). In terms of ORR, 10 mg Bev holds the maximum frequency (RR: 2.02, 95% CrI 1.52 to 2.66; probability rank = 0.98) in comparison to 5 mg and 7.5 mg Bev clearly. For grade ≥ 3 AEs, 10 mg Bev has the maximum incidence (RR: 1.15, 95% CrI 0.95 to 1.40, probability rank = 0.67) in comparison to other doses of Bev. CONCLUSION: The study suggests that 10 mg dose Bev could be more effective in treating advanced CRC in efficacy, but 5 mg Bev could be more safer in terms of safety.

Construction of an individualized brain metabolic network in patients with advanced non-small cell lung cancer by the Kullback-Leibler divergence-based similarity method: A study based on 18F-fluorodeoxyglucose positron emission tomography.

Background: Lung cancer has one of the highest mortality rates of all cancers, and non-small cell lung cancer (NSCLC) accounts for the vast majority (about 85%) of lung cancers. Psychological and cognitive abnormalities are common in cancer patients, and cancer information can affect brain function and structure through various pathways. To observe abnormal brain function in NSCLC patients, the main purpose of this study was to construct an individualized metabolic brain network of patients with advanced NSCLC using the Kullback-Leibler divergence-based similarity (KLS) method. Methods: This study included 78 patients with pathologically proven advanced NSCLC and 60 healthy individuals, brain 18F-FDG PET images of these individuals were collected and all patients with advanced NSCLC were followed up (>1 year) to confirm their overall survival. FDG-PET images were subjected to individual KLS metabolic network construction and Graph theoretical analysis. According to the analysis results, a predictive model was constructed by machine learning to predict the overall survival of NSLCL patients, and the correlation with the real survival was calculated. Results: Significant differences in the degree and betweenness distributions of brain network nodes between the NSCLC and control groups (p<0.05) were found. Compared to the normal group, patients with advanced NSCLC showed abnormal brain network connections and nodes in the temporal lobe, frontal lobe, and limbic system. The prediction model constructed using the abnormal brain network as a feature predicted the overall survival time and the actual survival time fitting with statistical significance (r=0.42, p=0.012). Conclusions: An individualized brain metabolic network of patients with NSCLC was constructed using the KLS method, thereby providing more clinical information to guide further clinical treatment.