Making Meta-Analyses More Replicable
[From the article “Automatic extraction of quantitative data from ClinicalTrials.gov to conduct meta-analyses” by Richeek Pradhan et al., published in the Journal of Clinical Epidemiology]
“Systematic reviews and meta-analyses are labor-intensive and time-consuming. Automated extraction of quantitative data from primary studies can accelerate this process.”
“ClinicalTrials.gov, launched in 2000, is the world’s largest trial repository of results data from clinical trials; it has been used as a source instead of journal articles. …We developed a Python-based software application (EXACT) that automatically extracts data required for meta-analysis from the ClinicalTrials.gov database in a spreadsheet format. We conﬁrmed the accuracy of the extracted data and then used those data to repeat meta-analyses in three published systematic reviews.”
“EXACT extracted data at ClincalTrials.gov with 100% accuracy, and it required 60% less time than the usual practice of manu-ally extracting data from journal articles. We found that 87% of the data elements extracted using EXACT matched those extracted manually from the journal articles. We were able to reproduce 24 of 28 outcomes using the journal article data. Of these 24 outcomes, we were able to reproduce 83.3% of the published estimates using data at ClinicalTrials.gov.”
To read the article, click here.