Applicability of the lung-molGPA index in non-small cell lung cancer patients with different gene alterations and brain metastases. (November 2018)

• Record Type: Journal Article
• Authors: Chen, Kaiyan; Yu, Xiaoqing; Zhang, Fanrong; Xu, Yanjun; Zhang, Peng; Huang, Zhiyu; Fan, Yun
• Is Part Of: Lung cancer. Volume 125(2018)
• Page Start: 8
• Page End: 13
• Publication Date: 2018-11
• Subjects: Non-small cell lung cancer -- Brain metastases -- DS-GPA -- Lung-molGPA -- Prediction; Lungs -- Cancer -- Periodicals; Lung Neoplasms -- Abstracts; Lung Neoplasms -- Periodicals; Poumons -- Cancer -- Périodiques; Lungs -- Cancer; Periodicals; Electronic journals; Electronic journals; 616.99424
• DOI: 10.1016/j.lungcan.2018.08.023
• Languages: English
• ISSNs: 0169-5002

Abstract

Highlights: DS-GPA and Lung-molGPA could predict outcomes of NSCLC patients with brain metastases. Lung-molGPA demonstrated discriminatory capability in patients with gene variations. A modified Lung-molGPA index was developed. Abstract: Objectives: The Lung-molGPA index is based on the original diagnosis-specific graded prognostic assessment (DS-GPA) and incorporates recently reported gene alteration data, predicting the outcomes of non-small cell lung cancer (NSCLC) patients with brain metastases (BM). However, the prognostic values of both DS-GPA and Lung-molGPA remain undetermined, especially for patients with different molecular types. Materials and Methods: A total of 1184 NSCLC patients with BM were analyzed for clinical factors and outcomes at Zhejiang Cancer Hospital, China. All prognostic factors were weighted for significance by hazard ratios. The applicability of DS-GPA and Lung-molGPA were reappraised in NSCLC patients with BM and various genetic profiles. Additionally, a modified Lung-molGPA was newly developed for NSCLC patients with gene variations. Results: NSCLC patients in the present study had a median survival time of 14.0 months from BM diagnosis. Both the DS-GPA and Lung-molGPA models could effectively predict the outcomes of NSCLC patients with BM (P < 0.001), and the Lung-molGPA model appeared to deliver more accurate predictions. Furthermore, Lung-molGPA scores demonstrated discriminatory capability in patients with gene variations (P < 0.001), and no significant difference was reached in wild-type patients (P = 0.133). Regarding oncogene-positive NSCLC patients with BM, a modified Lung-molGPA index was established based on the prognostic factors with a C-index of 0.73 (95% CI: 0.68-0.80) to accurately calculate survival probability (P < 0.001). Conclusions: In the era of precision medicine, Lung-molGPA accurately predicted the prognosis of NSCLC patients with mutant genotypes and BM, although it did not perform well in wild-type patients. Thus, it is worthwhile to explore the prognostic model for patients with positive driving genes.