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  • br Contents lists available at ScienceDirect br Lung Cancer

    2019-10-09


    Contents lists available at ScienceDirect
    Lung Cancer
    journal homepage: www.elsevier.com/locate/lungcan
    A molecular graded prognostic assessment (molGPA) model specific for T
    estimating survival in lung cancer patients with leptomeningeal metastases
    Kai Yin1, Yang-Si Li1, Mei-Mei Zheng1, Ben-Yuan Jiang, Wen-Feng Li, Jin-Ji Yang, Hai-Yan Tu, Qing Zhou, Wen-Zhao Zhong, Xue-Ning Yang, Hua-Jun Chen, Hong-Hong Yan, Lin-Lin Li, Yi-Long Wu , Xu-Chao Zhang
    Guangdong Lung Cancer Institute, Guangdong Provincial Key Laboratory of Translational Medicine in Lung Cancer, Medical Research Center, Guangdong Provincial People's Hospital & Guangdong Academy of Medical Sciences, Guangzhou 510080, China
    Keywords:
    Lung cancer
    Leptomeningeal metastases
    molGPA model
    Overall survival 
    Objectives: Leptomeningeal metastases (LM) had increased in advanced non-small-cell lung cancer (NSCLC) over the last 10 years. The survival outcome remained overall poor, heterogeneous and was reported in association with genotypes in lung cancer patients with LM. Graded prognostic assessment model integrated with molecular alterations (molGPA) might be accurate for outcome prediction of LM patients, but needs to be established. Materials and methods: We retrospectively screened 8921 consecutive lung cancer patients from January 2011 to March 2018. A total of 301 patients diagnosed as LM were enrolled, and randomly divided into training and validation sets after stratified by gender and age. A molGPA score for each patient was calculated based on the weighted significant parameters including gene mutations.
    Conclusion: The LM molGPA model with Dorsomorphin of gene status, KPS and ECM can accurately classify lung cancer patients with LM into diverse prognosis.
    1. Introduction
    Leptomeningeal metastases (LM) are a severe complication of sys-temic cancer usually occurring in advanced stages which affect ap-proximately 1–10% of patients with solid tumors. [1–6] The incidence of LM (3–5%) in advanced NSCLC has increased over the last 10 years, especially in subgroups of patients with targetable mutations [6–8]. Although therapies such as molecular targeted treatments and im-munotherapies have been described, standard treatment for LM is yet to be established [6,8–13].The median OS of lung cancer patients with LM is poor though with improvement from a historical 1–3 months to 3–11
    months by modern systemic therapies [6,7,9]. This trend suggests that there will be an increase in the prevalence of lung cancer patients with LM in the coming years. Accurate prognosis model for these hetero-geneous patients is warranted to appropriately manage patients in the clinical practice.
    There were already two classical models used for predicting out-comes in patients with LM of solid tumors. Mostly based on the clinical manifestations like Karnofsky performance score (KPS), extracranial metastasis (ECM) and symptoms, the US National Comprehensive Cancer Network (NCCN) guidelines (version 1, 2018) for patients with LM of solid tumors divided them into two categories: good risk and poor
    Corresponding authors at: Guangdong Lung Cancer Institute, Guangdong Provincial Key Laboratory of Translational Medicine in Lung Cancer, Medical Research Center, Guangdong Provincial People's Hospital & Guangdong Academy of Medical Sciences, 106 Zhongshan Er Rd, Guangzhou 510080, China. E-mail addresses: [email protected] (Y.-L. Wu), zhxuchao3000[email protected] (X.-C. Zhang).
    1 The first three authors contributed equally to this work.
    risk. [7,14] Good risk patients have a better chance of achieving higher response rate or even longer survival [9]. According to the results of cerebrospinal fluid (CSF) cytology test and brain Magnetic Resonance Imaging (MRI), leptomeningeal tumor spread can be distinguished to diffuse type and nodular type. Moreover, the first is always referred to a good prognosis [1,9].