ObjectiveThis study aims to conduct a bibliometric analysis of the dataset obtained from a systematic review of Model-Based Meta-Analysis (MBMA) studies to uncover research trends in MBMA. MethodsWe conducted a systematic search across databases including Embase, MEDLINE, Cochrane Library, Web of Science, CNKI, VIP, WanFang Data, and Sinomed. Relevant literature pertaining to MBMA was screened and included. Qualitative and quantitative analyses were performed to assess author contributions, temporal trends, national distribution, and disease prevalence. ResultsA total of 129 articles were included in the analysis, most published in being China (n=48), the United States (n=47), and the United Kingdom (n=7). The time span covered by these articles ranged from 2005 to 2023. A total of 531 researchers contributed to the included studies, with first authors from 15 different countries. The compilation encompassed 402 keywords, with the three most frequently used being “Meta-analysis” (n=28), “Model-based meta-analysis” (n=27), and “Pharmacokinetics” (n=14). The study covered 16 distinct disease categories, with the top three neoplasms (n=16), neurological disorders (n=14), and endocrine and metabolic diseases (n=13). ConclusionBibliometric analysis showed that the number of MBMA studies has increased significantly over the past three years, using a variety of key diseases as carriers. However, this new type of quantitative research has not yet attracted sufficient attention, and the research power is still concentrated in China and the United States; Moreover, a core group of authors has not yet been formed, it is necessary for scholars from various countries to strengthen multidisciplinary cooperation and communication to promote the production and translation of high-quality evidence.
ObjectivesTo evaluate the improvement of symptoms in patients with moderate to severe asthma aged 5-18 years treated with GINA (Global Initiative for Asthma) guidelines by network meta-analysis. Methods Randomized controlled trials (RCTs) about asthma patients aged 5 to 18 years with reported asthma symptom scores were collected from PubMed, Embase, Cochrane Library, CNKI, WanFang Data, VIP, SinoMed and clinical trial registry platform (ClinicalTrials.gov). The search time limit was from the inception to August 26, 2023. After two researchers independently screened literature, extracted data and evaluated the risk of bias of included studies, Stata 15.0 software was used for network meta-analysis. ResultsA total of 23 studies were included, 23 of which reported daytime asthma symptom scores. Compared with symptom scores in the low-dose ICS group, there was a statistically significant difference in improvement of daytime symptoms between low-dose ICS+LABA+LTRA (SMD=−1.4, 95%CI −1.99 to −0.81) and low-dose ICS+LABA+SABA (SMD=−1.43, 95%CI −2.48 to −0.39). Symptom scores for nighttime asthma were reported in 20 RCTs, and there was a statistically significant difference in symptom scores for low-dose ICS+LABA+LTRA (SMD=−1.20, 95%CI −2.20 to −0.21) compared with the low-dose ICS group. After the ranking of efficacy, the number one asthma symptom score in both daytime and nighttime was low-dose ICS+LABA+LTRA group. ConclusionLow dose ICS+LABA+LTRA has the best efficacy in improving daytime and nighttime asthma symptom scores.