Article type
Abstract
"Background Systematic review of disease burden is helpful for scientific decision-making, optimizing resource allocation, improving health intervention programs, and maximizing the efficiency of healthcare resources. In recent years, there has been a substantial increase in literature on this topic; however, the quality of research varies, and the results generally lack comparability.
Objective By analyzing the current research methods of systematic disease burden evaluation and exploring the limitations of existing research methods, this study aims
to enhance the scientific design of future research, improve research quality, and provide decision-makers with more scientific information.
Methods A computer search was conducted on PubMed for relevant studies on disease burden, with the search time frame spanning from database inception to November 2023. Two evaluators independently screened literature and extracted data. EndNote 20 was used to manage included literature, and Excel 2019 was utilized for data analysis.
Results A total of 220 articles were included, of which 187 (85.0%) were published in SCIE journals, and 49 (22.3%) originated from the United States. The main diseases covered included respiratory syncytial virus infection (3.6%, n=8), chronic obstructive pulmonary disease (3.2%, n=7), stroke (3.2%, n=7), influenza (3.2%, n=7). The most frequently searched databases for included studies were Embase (73.2%, n=161) and Pubmed (56.4%, n=124). Only 26 articles (11.8%) provided complete reporting of the study's inclusion/exclusion criteria using PICOS standards, while 5 articles (2.3%) used PECO standards. Biases in included studies were mainly assessed using multiple methods for different study types and single-checklist evaluation methods such as CHEERS checklist and JBI checklist. Due to significant heterogeneity in most included studies, quantitative synthesis was difficult, with qualitative analysis being predominant (81.4%, n=179).
Conclusion Current research on systematic evaluation of disease burden has significant room for improvement in describing search strategies and inclusion/exclusion criteria, with only a few studies providing sufficient detail. The lack of a unified method for evaluating study biases may affect the reliability of assessments. While descriptive analysis and meta-analysis are commonly used for result synthesis, there may be a need for greater methodological richness."
Objective By analyzing the current research methods of systematic disease burden evaluation and exploring the limitations of existing research methods, this study aims
to enhance the scientific design of future research, improve research quality, and provide decision-makers with more scientific information.
Methods A computer search was conducted on PubMed for relevant studies on disease burden, with the search time frame spanning from database inception to November 2023. Two evaluators independently screened literature and extracted data. EndNote 20 was used to manage included literature, and Excel 2019 was utilized for data analysis.
Results A total of 220 articles were included, of which 187 (85.0%) were published in SCIE journals, and 49 (22.3%) originated from the United States. The main diseases covered included respiratory syncytial virus infection (3.6%, n=8), chronic obstructive pulmonary disease (3.2%, n=7), stroke (3.2%, n=7), influenza (3.2%, n=7). The most frequently searched databases for included studies were Embase (73.2%, n=161) and Pubmed (56.4%, n=124). Only 26 articles (11.8%) provided complete reporting of the study's inclusion/exclusion criteria using PICOS standards, while 5 articles (2.3%) used PECO standards. Biases in included studies were mainly assessed using multiple methods for different study types and single-checklist evaluation methods such as CHEERS checklist and JBI checklist. Due to significant heterogeneity in most included studies, quantitative synthesis was difficult, with qualitative analysis being predominant (81.4%, n=179).
Conclusion Current research on systematic evaluation of disease burden has significant room for improvement in describing search strategies and inclusion/exclusion criteria, with only a few studies providing sufficient detail. The lack of a unified method for evaluating study biases may affect the reliability of assessments. While descriptive analysis and meta-analysis are commonly used for result synthesis, there may be a need for greater methodological richness."