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Diagnostic accuracy of next-generation sequencing (NGS) for identifying actionable mutations in advanced non-small cell lung cancer: Systematic Review and Meta-Analysis

Research output: Contribution to journalArticlepeer-review

Abstract

Purpose
To evaluate the diagnostic accuracy and clinical performance of next-generation sequencing (NGS) compared to conventional techniques for detecting actionable mutations using tissue or liquid biopsy samples in patients with advanced non-small cell lung cancer.

Methods
A systematic review and meta-analysis of diagnostic test studies (PROSPERO: CRD42023450465) were conducted. We included studies with sufficient comparative data, using a t test to analyze turnaround time differences and hypothesis testing for valid result proportions (p < 0.05). The meta-analysis, performed in Stata 17®, pooled sensitivities and specificities by mutation and evaluation technique. The QUADAS-2 tool assessed study quality.

Results
A total of 56 studies involving 7143 patients were analyzed. No significant differences were found in valid result percentages between standard tests and NGS in tissue (85.57% vs. 85.78%; p = 0.99) and liquid biopsy (81.50% vs. 91.72%; p = 0.277). Liquid biopsy had a significantly shorter turnaround time (8.18 vs. 19.75 days; p < 0.001). NGS demonstrated high accuracy in tissue for EGFR (sensitivity: 93%, specificity: 97%) and ALK rearrangements (sensitivity: 99%, specificity: 98%). In liquid biopsy, NGS was effective for EGFR, BRAF V600E, KRAS G12C, and HER2 (sensitivity: 80%, specificity: 99%) but had limited sensitivity for ALK, ROS1, RET, and NTRK rearrangements.

Conclusions
NGS enables comprehensive mutation analysis, particularly for point mutations. Further validation is required to improve the detection of gene rearrangements.
Translated title of the contributionPrecisión diagnóstica de la secuenciación de próxima generación (NGS) para identificar mutaciones accionables en el cáncer de pulmón de células no pequeñas avanzado: Revisión sistemática y metanálisis
Original languageEnglish
Pages (from-to)1-11
Number of pages11
JournalClinical and Translational Oncology
DOIs
StatePublished - 13 Sep 2025

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • Carcinoma non-small-cell lung
  • Next-generation sequencing (NGS)
  • Diagnostic accuracy
  • Actionable mutations
  • Non-small cell lung cancer (NSCLC)
  • Metanalysis and systematic review

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