Background/Objectives: Until now, no meta-analysis has been published to evaluate the diagnostic performance of next-generation sequencing (NGS) panel using circulating tumor (ctDNA) in patients with advanced non-small cell lung cancer (aNSCLC). The aim of the study was to carry out a systematic review and a meta-analysis in order to determine the accuracy of NGS of ctDNA to detect six oncogenic driver alterations: epidermal growth factor receptor (EGFR); anaplastic lymphoma kinase (ALK); ROS proto-oncogene 1, receptor tyrosine kinase (ROS-1); serine/threonine-protein kinase B-RAF (BRAF); RET proto-oncogene (RET); and MET proto-oncogene, receptor tyrosine kinase (MET) exon 14 in patients with aNSCLC.
Methods: MEDLINE/PubMed, Cochrane Library, Latin American and Caribbean Health Sciences Literature (LILACS), and Centre for Reviews and Dissemination databases and articles obtained from other sources were searched for relevant studies that evaluate the accuracy (sensitivity and specificity) of NGS using ctDNA in patients with aNSCLC. The studies were eligible when NGS of ctDNA was compared with tissue tests to detect at least one of the six oncogenic driver alterations. Diagnostic measures (sensitivity and specificity) were pooled with a bivariate diagnostic random effect. All statistical analyses were performed with software R, v.4.0.0.
Results: Ten studies were eligible for data extraction. The overall pooled estimates of sensitivity and specificity were 0.766 (95% CI: 0.678-0.835); 0.999 (95% CI: 0.990-1.000), respectively.
Conclusions: The analysis has demonstrated that the NGS panel using ctDNA has a high accuracy to identify the six actionable oncogenic driver alterations in patients with aNSCLC. Therefore, it can be considered a reliable alternative to guide the patients with aNSCLC to the right treatment who cannot undergo an invasive procedure or have insufficient tissue material for molecular tests.
was English language peer-reviewed PE studies describing scoring tools to evaluate methodological quality. Results: A total of 23 pharmacoeconomic scoring tools met the inclusion criteria. Findings revealed that although checklists and recommendations exist for evaluating the HC-PE literature, quantitative approaches are lacking. The checklists number of items ranged from 8-40 and focused on assessing risk of bias, study quality, and reporting standards. The checklists were useful in assessing the quality and methodology of PE studies, however, only one tool assigned points to each item. There were two tools that categorized each domain into qualitative grades, while the others did not assign scores. Conclusions: Appraising the quality of HC-PE literature has become increasingly important for decision makers and those conducting systematic reviews. There is a lack of validation and variability in the criteria which is not weighted. The performance of an effective assessment requires qualitative as well as quantitative aspects. Future research will include the development of such tool.
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