Login / Signup

EGFR Mutation Detection in Brazilian Patients With Non-Small-Cell Lung Cancer: Lessons From Real-World Data Scenario of Molecular Testing.

Tatiane MontellaMariano ZalisMauro ZukinVladmir Cláudio Cordeiro de LimaClarissa Seródio BaldottoPedro De MarchiPaulo Guilherme de Oliveira SallesClarissa MathiasCarlos Henrique BarriosCarolina KawamuraAknar CalabrichLuiz Henrique AraujoGilberto de Castro JuniorCarolina BustamanteAndré Santa MariaMarcelo Martins ReisCarlos Gil Ferreira
Published in: JCO global oncology (2023)
This study examined the prevalence of EGFR mutations in Brazilian patients with NSCLC using different technologies, suggesting that the type of method used, directed or nondirected against specific mutations, influences the analysis, particularly for uncommon mutations, which will be missed by mutation-specific approaches such as cobas testing. Our estimates are the largest in Latin America and are consistent with previous reports from other parts of the world. Besides the variability in methods described here as technology incorporation advances in a nonhomogeneous manner, it is probably like the real-world clinical setting Brazilian oncologists face in their daily practice.
Keyphrases
  • small cell lung cancer
  • epidermal growth factor receptor
  • tyrosine kinase
  • healthcare
  • physical activity
  • brain metastases
  • machine learning
  • palliative care
  • quality improvement
  • artificial intelligence
  • data analysis