Real-world prevalence of actionable genomic alterations detected by next-generation sequencing in non-small cell lung cancer: a systematic review and meta-analysis.

Authors

Manuel Pérez-Pérez, Carmen García de Sola-Llamas, María Del Carmen Aranda-Pérez, Laura Macías-García

Published in

Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico. Jun 25, 2026. Epub Jun 25, 2026.

Abstract

Next-generation sequencing (NGS) has become central to molecular profiling in non-small cell lung cancer (NSCLC), enabling the detection of both common and low-frequency actionable genomic alterations. However, the real-world prevalence of rare actionable drivers remains uncertain due to heterogeneity in cohort selection and testing strategies.
We conducted a systematic review and meta-analysis of clinical NSCLC cohorts assessed by NGS, focusing on non-enriched populations to better reflect routine practice. The primary outcomes were MET exon 14 skipping, RET fusions, and ROS1 fusions. Secondary outcomes included EGFR uncommon mutations, EGFR exon 20 insertions, HER2/ERBB2 exon 20 insertions, and NTRK fusions. Pooled prevalence estimates were calculated using random-effects models with restricted maximum likelihood.
Twenty-seven studies were retained in the reconstructed dataset, including 22 non-enriched studies for the primary analysis and 5 sensitivity studies. In the primary non-enriched analysis, pooled prevalence estimates were 1.99% (95% CI 1.46-2.70) for MET exon 14 skipping, 1.34% (95% CI 0.88-2.04) for RET fusions, and 1.45% (95% CI 0.86-2.45) for ROS1 fusions. Estimates were generally stable across prespecified restriction and sensitivity analyses. Secondary alterations showed lower prevalence and greater uncertainty, particularly for sparse outcomes.
Rare actionable genomic alterations are recurrently identified in NGS-assessed NSCLC cohorts. These findings support the clinical value of broad genomic profiling, provide realistic expectations for diagnostic yield in routine practice, and may inform precision oncology implementation, molecular-testing pathways, and resource allocation.

PMID:
42348103
Bibliographic data and abstract were imported from PubMed on 25 Jun 2026.

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