Publications by authors named "L Fjellbirkeland"
Background: Based on favourable results from clinical trials, immune checkpoint inhibitors (ICI) have become the standard first line (1 L) systemic anticancer treatment (SACT) for advanced stage non-small cell lung cancer (NSCLC) without targetable mutations. We evaluate whether these results are generalizable to everyday clinical practice and compare overall survival (OS) of patients treated with ICI to a historical cohort of patients treated with chemotherapy and results from clinical trials.
Methods: Our study comprised all advanced NSCLC patients initiating SACT in 2012-21 in Norway.
Background: Whether sex is an independent prognostic factor in lung cancer survival is the subject of ongoing debate. Both large national registries and single hospital studies have shown conflicting findings. In this study, we explore the impact of sex on lung-cancer-specific survival in an unselected population that is well-characterized with respect to stage and other covariates.
View Article and Find Full Text PDFIntroduction/background: There has been a marked survival improvement for patients with non-small-cell lung cancer. We describe the national trends in characteristics and survival, and geographical differences in diagnostic workup, treatment, and survival for patients with small-cell lung cancer (SCLC).
Materials And Methods: Patients registered with SCLC at the Cancer Registry of Norway in 2002 to 2022 were included.
Background: The main focus on the characteristics of malignant lung tumours has been the size, position within the lobe, and infiltration into neighbouring structures. The aim of this study was to investigate the distribution and characteristics of malignant tumours between the lung lobes and whether the diagnosis, treatment, and outcome differed based on location.
Methods: This study is based on 10,849 lung cancer patients diagnosed in 2018-2022 with complete data on the location and characteristics of the tumours.
Background: We aim to implement an immune cell score model in routine clinical practice for resected non-small-cell lung cancer (NSCLC) patients (NCT03299478). Molecular and genomic features associated with immune phenotypes in NSCLC have not been explored in detail.
Patients And Methods: We developed a machine learning (ML)-based model to classify tumors into one of three categories: inflamed, altered, and desert, based on the spatial distribution of CD8+ T cells in two prospective (n = 453; TNM-I trial) and retrospective (n = 481) stage I-IIIA NSCLC surgical cohorts.