Introduction: Local ablative treatment (LAT) improves outcome in lung cancer with oligometastatic disease (OMD) and potentially leads to long term survival. The aim of this retrospective study was to evaluate and quantify the additional benefit of LAT in synchronous OMD and to further identify prognostic factors for survival.
Patients And Methods: A propensity score-matched pairs analysis was performed on a set of patient and disease variables in 180 patients, treated for synchronous single organ OMD including non small-cell and neuroendocrine lung cancer with ≤4 metastases between 2000 and 2016 in 3 lung cancer centers in Berlin, Germany. Patients either received LAT for all sites of disease (intervention group) by means of surgery or stereotactic radiotherapy, or standard chemotherapy, if necessary combined with a local treatment with palliative intent (control group).
Results: Median follow-up time was 32.2 and 18.8 months for the intervention and control group, respectively. Substantial benefits in median progression-free survival (PFS, 25.1 vs. 8.2 months; HR, 0.30; 95% CI, 0.21-0.43; p < 0.001) and overall survival (OS, 60.4 vs. 22.5 months; HR, 0.42; 95% CI, 0.28-0.62; p < 0.001) were associated with LAT. Histology of adenocarcinoma and T1a primaries also predicted a favorable prognosis concerning PFS and OS. More favorable nodal stage (N0-2 vs. 3) and solitary metastases were associated with an extended PFS, whereas initial ECOG-PS (0-1 vs. 2) predicted OS.
Conclusions: LAT was the strongest predictor for PFS and OS in OMD with ≤4 metastases. Survival in the control group identifies OMD as a subset of lung cancer with a generally more favorable prognosis.
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http://dx.doi.org/10.1016/j.lungcan.2018.09.021 | DOI Listing |
Lung Cancer
January 2025
Dept. of Medical Oncology, Princess Margaret Cancer Center, Toronto, ON, Canada.
Background: Manual extraction of real-world clinical data for research can be time-consuming and prone to error. We assessed the feasibility of using natural language processing (NLP), an AI technique, to automate data extraction for patients with advanced lung cancer (aLC). We assessed the external validity of our NLP-extracted data by comparing our findings to those reported in the literature.
View Article and Find Full Text PDFLung Cancer
January 2025
Internal Medicine III, Wakayama Medical University, Wakayama, Japan.
Objectives: The lack of definitive biomarkers presents a significant challenge for chemo-immunotherapy in extensive-stage small-cell lung cancer (ES-SCLC). We aimed to identify key genes associated with chemo-immunotherapy efficacy in ES-SCLC through comprehensive gene expression analysis using machine learning (ML).
Methods: A prospective multicenter cohort of patients with ES-SCLC who received first-line chemo-immunotherapy was analyzed.
Clin Nucl Med
December 2024
From the Department of Nuclear Medicine, Affiliated Cancer Hospital & Institute of Guangzhou Medical University, Guangzhou, Guangdong, China.
A 53-year-old woman was found to have a soft tissue mass in the right lower lung lobe on chest CT, raising suspicion of lung cancer. For staging, 18F-FDG PET/CT was performed, which demonstrated intense tracer uptake in the mass (SUVmax, 14.6).
View Article and Find Full Text PDFChin Med J (Engl)
December 2024
Department of Anesthesiology, The Affiliated Hospital, Southwest Medical University, Luzhou, Sichuan 646000, China.
PLoS One
January 2025
Department of Oncology, Peking University First Hospital, Taiyuan Hospital, Taiyuan, Shanxi, China.
This work established the cytotoxic, antioxidant and anticancer effects of copper nanoparticles (CuNPs) manufactured with fennel extract, especially on non-small cell lung cancer (NSCLC) as well. CuNPs caused cytotoxicity in a dose-dependent manner for two NSCLC cell lines, A549 and H1650. At 100 μg/ml, CuNPs reduced cell viability to 70% in A549 cells and 65% in H1650 cells.
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