Background: Lung cancer is one of the most commonly diagnosed cancers and the leading cause of cancer-related death worldwide. Although smoking is the primary cause of the cancer, lung cancer is also commonly diagnosed in people who have never smoked. Currently, the proportion of people who have never smoked diagnosed with lung cancer is increasing. Despite this alarming trend, this population is ineligible for lung screening. With the increasing proportion of people who have never smoked among lung cancer cases, there is a pressing need to develop prediction models to identify high-risk people who have never smoked and include them in lung cancer screening programs. Thus, our systematic review is intended to provide a comprehensive summary of the evidence on existing risk prediction models for lung cancer in people who have never smoked.
Methods: Electronic searches will be conducted in MEDLINE (Ovid), Embase (Ovid), Web of Science Core Collection (Clarivate Analytics), Scopus, and Europe PMC and Open-Access Theses and Dissertations databases. Two reviewers will independently perform title and abstract screening, full-text review, and data extraction using the Covidence review platform. Data extraction will be performed based on the Checklist for Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modeling Studies (CHARMS). The risk of bias will be evaluated independently by two reviewers using the Prediction model Risk-of-Bias Assessment Tool (PROBAST) tool. If a sufficient number of studies are identified to have externally validated the same prediction model, we will combine model performance measures to evaluate the model's average predictive accuracy (e.g., calibration, discrimination) across diverse settings and populations and explore sources of heterogeneity.
Discussion: The results of the review will identify risk prediction models for lung cancer in people who have never smoked. These will be useful for researchers planning to develop novel prediction models, and for clinical practitioners and policy makers seeking guidance for clinical decision-making and the formulation of future lung cancer screening strategies for people who have never smoked.
Systematic Review Registration: This protocol has been registered in PROSPERO under the registration number CRD42023483824.
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http://dx.doi.org/10.1186/s41512-024-00166-4 | DOI Listing |
Discov Oncol
January 2025
Department of Cardiothoracic Surgery, The First Affiliated Hospital of Chongqing Medical University, No.1, Youyi Road, Yuzhong District, Chongqing, 400010, China.
Purpose: Nano-drug delivery systems (NDDS) have become a promising alternative and adjunctive strategy for lung cancer (LC) treatment. However, comprehensive bibliometric analyses examining global research efforts on NDDS in LC are scarce. This study aims to fill this gap by identifying key research trends, emerging hotspots, and collaboration networks within the field of NDDS and LC.
View Article and Find Full Text PDFClin Exp Med
January 2025
Pathology Department, Faculty of Medicine, Ain Shams University, Cairo, Egypt.
Lung cancer is one of the major causes of cancer morbidity and mortality. Subtyping of non-small cell lung cancer is necessary owing to different treatment options. This study is to evaluate the value of immunohistochemical expression of glypican-1 in the diagnosis of lung squamous cell carcinoma (SCC).
View Article and Find Full Text PDFClin Transl Oncol
January 2025
Federal University of Pará, Belém, Pará, 66073-005, Brazil.
Background: The benefit of treatment with tyrosine kinase inhibitors targeting the epidermal growth factor receptor (EGFR-TKI) for lung adenocarcinoma (ADC), stratified by ethnicity, has not yet been fully elucidated.
Methods: We searched PubMed, Embase, and Cochrane databases for studies that investigated EGFR-TKI for lung ADC. We computed hazard ratios (HRs) or risk ratios (RRs) for binary endpoints, with 95% confidence intervals (CIs).
Ophthalmol Retina
January 2025
Department of Ophthalmology and Visual Sciences, University of Alberta, Edmonton, Alberta, Canada.
Ann Thorac Surg
January 2025
Thoracic Surgery Service, Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, New York.
Background: The use of local consolidative therapy (LCT) in patients with oligometastatic non-small cell lung cancer (NSCLC) is rapidly evolving, with a preponderance of data supporting the benefits of such therapeutic approaches incorporating pulmonary resection for appropriately selected candidates. However, practices vary widely institutionally and regionally, and evidence-based guidelines are lacking.
Methods: The Society of Thoracic Surgeons assembled a panel of thoracic surgical oncologists to evaluate and synthesize the available evidence regarding the role of pulmonary resection as LCT.
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