Literature DB >> 31892595

Application of Cluster Analysis to Distant Metastases from Lung Cancer.

Hiroko Watanabe1, Shinichiro Okauchi2, Hideyasu Yamada3, Shinya Sato4, Kunihiko Miyazaki4, Takahide Kodama4, Hiroaki Satoh5, Nobuyuki Hizawa6.   

Abstract

BACKGROUND/AIM: In patients with lung cancer, there has been no study that treated 'distant metastases' as 'metastatic patterns'. This study aimed to evaluate if specific 'metastatic patterns' exist in lung cancer patients. PATIENTS AND METHODS: Data were collected from lung cancer patients between 2009 and 2018. Metastatic patterns were analyzed using cluster analysis in patients with epidermal growth factor receptor (EGFR) mutation-positive lung adenocarcinoma, those with small cell lung cancer (SCLC), and those with squamous cell lung cancer (SqCLC).
RESULTS: In 313 patients (127 patients with EGFR mutation, 87 patients with SCLC, and 99 patients with SqCLC), metastatic patterns existed in each of the three subset groups, and metastatic patterns of these groups were statistically different.
CONCLUSION: The knowledge of the metastatic patterns might be useful for clinical practice in the foreseeable future, as it enables a more efficient detection of metastatic disease through imaging, and a more effective treatment at predicted metastatic sites. Copyright
© 2020, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.

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Keywords:  Lung cancer; cluster analysis; metastasis; metastatic pattern

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Year:  2020        PMID: 31892595     DOI: 10.21873/anticanres.13968

Source DB:  PubMed          Journal:  Anticancer Res        ISSN: 0250-7005            Impact factor:   2.480


  1 in total

1.  Cluster analysis of deterioration sites after first-line epidermal growth factor receptor-tyrosine kinase inhibitor in epidermal growth factor receptor mutated non-small cell lung cancer.

Authors:  Shinichiro Okauchi; Kunihiko Miyazaki; Hiroaki Satoh
Journal:  Contemp Oncol (Pozn)       Date:  2022-06-30
  1 in total

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