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Published on: August 11, 2017
Network meta-analyses for EGFR mutation-positive non-small-cell lung cancer: systematic review and overview of
Carl Samuelsen1, Ingolf Griebsch2
1Outcomes Analytica AS, Oslo, Norway.
Abstract:
Aim: To perform a review of network meta-analyses (NMAs) for the first-line treatment of EGFR mutation-positive non-small-cell lung cancer, and to provide an overview of methodological approaches and potential shortcomings. Materials & methods: We conducted a systematic review of NMAs and evaluated their methodologies, including inclusion/exclusion criteria, information sources, results and outcomes, and statistical methodologies. Results: We identified ten published NMAs using five archetypical network structures. Despite similar objectives, there was substantial variability in the number of trials included in each NMA and in the relative treatment efficacy of the tyrosine kinase inhibitors. Conclusion: We identified methodological issues to explain differences in the findings, criteria for inclusion in NMAs and the degree of lumping of treatments. These factors should be given particular consideration in future research.
Insights
This review of network meta-analyses (NMAs) for first-line EGFR-positive non-small cell lung cancer treatments found significant methodological variations. These differences in NMAs explain the variability in reported treatment efficacy for tyrosine kinase inhibitors.
Area of Science:
- Oncology
- Medical Statistics
- Clinical Research Methodology
Background:
- First-line treatment for EGFR mutation-positive non-small cell lung cancer (NSCLC) is critical.
- Network meta-analyses (NMAs) are increasingly used to compare multiple treatments.
- Understanding NMA methodologies is essential for interpreting results in NSCLC.
Purpose of the Study:
- To review existing NMAs for first-line treatment of EGFR-positive NSCLC.
- To analyze the methodological approaches and identify potential shortcomings in these NMAs.
- To provide an overview of the current NMA landscape for this indication.
Main Methods:
- Systematic review of published NMAs.
- Evaluation of NMA methodologies including inclusion/exclusion criteria, data sources, outcomes, and statistical methods.
- Analysis of network structures and treatment comparisons.
Main Results:
- Ten NMAs were identified, utilizing five distinct network structures.
- Substantial variability was observed in the number of included trials across NMAs.
- Significant differences were noted in the reported relative efficacy of tyrosine kinase inhibitors.
Conclusions:
- Methodological inconsistencies in NMAs contribute to differing findings.
- Variations in inclusion criteria and treatment 'lumping' require careful consideration.
- Future research should address these methodological issues for more reliable NMA results in EGFR-positive NSCLC.
