98%
921
2 minutes
20
Background: Obesity has been proposed as a potential protective factor against lung cancer. We examined the association between BMI and lung cancer risk in a pooled analysis based on nested case-control studies from four cohort studies.
Methods: A case-control study was nested within four cohorts in USA, Europe, China and Singapore that included 4172 cases and 8471 control subjects. BMI at baseline was calculated as weight in kilograms divided by height in meters squared (kg/m), and classified into 4 categories: underweight (BMI < 18.5), normal weight (18.5 ≤ BMI < 25), overweight (25 ≤ BMI < 30) and obese (≥30). Odds ratios (ORs) and 95% confidence intervals (CIs) for BMI-lung cancer associations were estimated using unconditional logistic regression, adjusting for potential confounders.
Results: Considering all participants, and using normal weight as the reference group, a decreased risk of lung cancer was observed for those who were overweight (OR 0.77, 95% CI: 0.68-0.86) and obese (OR 0.69, 95% CI: 0.59-0.82). In the stratified analysis by smoking status, the decreased risk for lung cancer was observed among current, former and never smokers (P for interaction 0.002). The adjusted ORs for overweight and obese groups were 0.79 (95% CI: 0.68-0.92) and 0.75 (95% CI: 0.60-0.93) for current smokers, 0.70 (95% CI: 0.53-0.93) and 0.55 (95% CI: 0.37-0.80) for former smokers, 0.77 (95% CI: 0.59-0.99), and 0.71 (95% CI: 0.44-1.14) for never smokers, respectively. While no statistically significant association was observed for underweight subjects who were current smokers (OR 1.24, 95% CI: 0.98-1.58), former smokers (OR 0.27, 95% CI: 0.12-0.61) and never smokers (OR 0.83, 95% CI: 0.5.-1.28).
Conclusion: The results of this study provide additional evidence that obesity is associated with a decreased risk of lung cancer. Further biological studies are needed to address this association.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5824613 | PMC |
http://dx.doi.org/10.1186/s12885-018-4124-0 | DOI Listing |
Lung Cancer
August 2025
The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China; National Center for Respiratory Medicine, National Clinical Research Center for Respiratory Disease, State Key Laboratory of Respiratory Disease, Guangzhou, China; Guangzhou Institute of Respiratory Health, Guangzhou, C
Background: Large cell neuroendocrine carcinoma (LCNEC) represents a rare and unique type of lung tumor with an unfavorable prognosis. It is essential to summarize the treatment modalities and prognosis for inoperable stage III and IV LCNEC, explore the role of frontline immunotherapy, and examine the stratification role of the Lung Immune Prognostic Index (LIPI) and its relationship with the tumor microenvironment (TME).
Methods: This study retrospectively analyzed 160 patients with inoperable lung LCNEC (L-LCNEC) admitted to three hospitals from December 2012 to November 2023.
J Surg Res
September 2025
Department of Surgery, Keck School of Medicine of USC, Los Angeles, California. Electronic address:
Introduction: Psychiatric comorbidities are increasingly recognized in patients with thoracic malignancies. We undertook this scoping review to characterize the management of thoracic malignancies in patients with psychiatric illness and uncover any disparities in operative treatment or perioperative outcomes.
Methods: We conducted a scoping review following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines.
Comput Biol Chem
September 2025
Faculty of Health Sciences, University of Macau, Avenida de Universidade, Taipa, Macao Special Administrative Region of China. Electronic address:
With the advancements of next-generation sequencing, publicly available pharmacogenomic datasets from cancer cell lines provide a handle for developing predictive models of drug responses and identifying associated biomarkers. However, many currently available predictive models are often just used as black boxes, lacking meaningful biological interpretations. In this study, we made use of open-source drug response data from cancer cell lines, in conjunction with KEGG pathway information, to develop sparse neural networks, K-net, enabling the prediction of drug response in EGFR signaling pathways and the identification of key biomarkers.
View Article and Find Full Text PDFJpn J Clin Oncol
September 2025
Department of Hematology and Oncology, Nagoya City University Graduate School of Medical Sciences, Nagoya, Japan.
Background: Amrubicin monotherapy has been used in Japan for patients with refractory, relapsed, small cell lung cancer (SCLC). However, the clinical guidelines do not specify a recommended initial dose for elderly patients. This retrospective study aimed to explore the appropriate initial dose of amrubicin for elderly patients with refractory, relapsed SCLC.
View Article and Find Full Text PDFMikrochim Acta
September 2025
The Third Affiliated Hospital of Anhui Medical University, The First People's Hospital of Hefei, Binhu Hospital of Hefei, Hefei, 230061, P. R. China.
Lung cancer, as one of the cancers with the highest morbidity and mortality rates in the world, requires accurate detection of its vital serum marker, neuron-specific enolase (NSE), which is a key challenge for early detection of lung cancer. However, traditional chemiluminescence immunoassay (CLIA) methods rely on labeled antibodies (Abs) and suffer from complex operations and high costs. In this work, a label-free CLIA based on CL-functionalized mesoporous magnetic nanoparticles (CuFeO@mSiO-Cys-Luminol-Au NPs) is developed for the rapid and sensitive detection of NSE.
View Article and Find Full Text PDF