ABSTRACT
Background/Aims@#Using a nationwide cohort, we investigated the cancer risk in Korean patients with gout. @*Methods@#Data were obtained from the Korean National Health Insurance Service Database. Patients with gout were defined as those aged ≥ 20 years who were diagnosed with gout and received anti-gout medication (allopurinol, colchicine, and benzbromarone) between 2008 and 2010. Patients with nail disorders were randomly assigned to a control group (1:1 ratio) after frequency matching for age and sex. Cancer incidence was then investigated between 2012 and 2018. Cox proportional hazard regression analysis was used to investigate the association between gout and cancer after adjusting for concomitant diseases. @*Results@#This study included 179,930 patients with gout and an equal number of matched controls. The incidence of overall cancer was higher in patients with gout than in controls (incidence rate ratio, 1.08). Cox proportional hazards regression analysis showed that gout was associated with a hazard ratio of 1.053 (95% confidence interval ,1.031 to 1.077) after adjusting for concomitant diseases. @*Conclusions@#Gout was associated with a significantly high risk of cancer, especially esophageal, stomach, colon, liver, pancreatic, lung, ovarian, renal, and bladder cancers.
ABSTRACT
Background@#Although patients with chronic obstructive pulmonary disease (COPD) experience high morbidity and mortality worldwide, few biomarkers are available for COPD.Here, we analyzed potential biomarkers for the diagnosis of COPD by using word embedding. @*Methods@#To determine which biomarkers are likely to be associated with COPD, we selected respiratory disease-related biomarkers. Degrees of similarity between the 26 selected biomarkers and COPD were measured by word embedding. And we infer the similarity with COPD through the word embedding model trained in the large-capacity medical corpus, and search for biomarkers with high similarity among them. We used Word2Vec, Canonical Correlation Analysis, and Global Vector for word embedding. We evaluated the associations of selected biomarkers with COPD parameters in a cohort of patients with COPD. @*Results@#Cytokeratin 19 fragment (Cyfra 21-1) was selected because of its high similarity and its significant correlation with the COPD phenotype. Serum Cyfra 21-1 levels were determined in patients with COPD and controls (4.3 ± 5.9 vs. 3.9 ± 3.6 ng/mL, P = 0.611). The emphysema index was significantly correlated with the serum Cyfra 21-1 level (correlation coefficient = 0.219,P = 0.015). @*Conclusion@#Word embedding may be used for the discovery of biomarkers for COPD and Cyfra 21-1 may be used as a biomarker for emphysema. Additional studies are needed to validate Cyfra 21-1 as a biomarker for COPD.
ABSTRACT
Background@#Although patients with chronic obstructive pulmonary disease (COPD) experience high morbidity and mortality worldwide, few biomarkers are available for COPD.Here, we analyzed potential biomarkers for the diagnosis of COPD by using word embedding. @*Methods@#To determine which biomarkers are likely to be associated with COPD, we selected respiratory disease-related biomarkers. Degrees of similarity between the 26 selected biomarkers and COPD were measured by word embedding. And we infer the similarity with COPD through the word embedding model trained in the large-capacity medical corpus, and search for biomarkers with high similarity among them. We used Word2Vec, Canonical Correlation Analysis, and Global Vector for word embedding. We evaluated the associations of selected biomarkers with COPD parameters in a cohort of patients with COPD. @*Results@#Cytokeratin 19 fragment (Cyfra 21-1) was selected because of its high similarity and its significant correlation with the COPD phenotype. Serum Cyfra 21-1 levels were determined in patients with COPD and controls (4.3 ± 5.9 vs. 3.9 ± 3.6 ng/mL, P = 0.611). The emphysema index was significantly correlated with the serum Cyfra 21-1 level (correlation coefficient = 0.219,P = 0.015). @*Conclusion@#Word embedding may be used for the discovery of biomarkers for COPD and Cyfra 21-1 may be used as a biomarker for emphysema. Additional studies are needed to validate Cyfra 21-1 as a biomarker for COPD.
ABSTRACT
BACKGROUND: Lung cancer is the most common cause of cancer-related mortality worldwide. We previously reported the identification of a new genetic marker, cellular retinoic acid binding protein 2 (CRABP2), in lung cancer tissues. The aim of this study was to assess plasma levels of CRABP2 from patients with non-small cell lung cancer (NSCLC). METHODS: Blood samples that were collected from 122 patients with NSCLC between September 2009 and September 2013 were selected for the analysis, along with samples from age- (± 5 years), sex-, and cigarette smoking history (± 10 pack-years [PY])-matched controls from the Korea Biobank Network. The control specimens were from patients who were without malignancies or pulmonary diseases. We measured plasma levels of CRABP2 using commercially available enzyme-linked immunosorbent assay kits. RESULTS: The mean age of the NSCLC patients was 71.8 ± 8.9 years, and the median cigarette smoking history was 32 PY (range, 0–150 PY). Plasma CRABP2 levels were significantly higher in patients with NSCLC than in the matched controls (37.63 ± 28.71 ng/mL vs. 24.09 ± 21.09 ng/mL, P < 0.001). Higher plasma CRABP2 levels were also correlated with lower survival rates in NSCLC patients (P = 0.014). CONCLUSION: Plasma CRABP2 levels might be a novel diagnostic and prognostic marker in NSCLC.