BACKGROUND Colorectal cancer is the third most common malignancy and the fourth leading cause of cancer-related deaths worldwide.Several studies have shown an association between gut microbiota and colorectal cancer.G...BACKGROUND Colorectal cancer is the third most common malignancy and the fourth leading cause of cancer-related deaths worldwide.Several studies have shown an association between gut microbiota and colorectal cancer.Gut microbiota is unique and can be influenced by geographic factors and habits.This study aimed to determine the diversity and composition of colonic mucosal microbiota in patients with and without colorectal cancer.AIM To determine the diversity and composition of colonic mucosal microbiota in patients with and without colorectal cancer in Indonesia.METHODS This case-control study included 59 subjects(35 colorectal cancer patients and 24 non-colorectal cancer patients indicated for colonoscopy at Dr.Cipto Mangunkusumo Gastrointestinal Endoscopy Center and Fatmawati Hospital.Microbiota examination was performed using 16S rRNA sequencing.Bioinformatics analysis was performed using the wf-metagenomics pipeline from EPI2Me-Labs(Oxford Nanopore Technologies platform).RESULTS Patients with colorectal cancer had a higher median index value on the Shannon index(3.28 vs 2.82,P>0.05)and a lower value on the Simpson index(0.050 vs 0.060,P>0.05).Significant differences in beta diversity were observed at the genus(P=0.002)and species levels(P=0.001).Firmicutes,Proteobacteria,Bacteroidetes,and Fusobacteria were the dominant phyla.The genera Bacteroides,Campylobacter,Peptostreptococcus,and Parvimonas were found more frequently in colorectal cancer,while Faecalibacterium,Haemophilus,and Phocaeicola were more frequently found in non-colorectal cancer.The relative abundance of Fusobacterium nucleatum,Bacteroides fragilis,Enterococcus faecalis,Campylobacter hominis,and Enterococcus faecalis species was significantly elevated in patients with colorectal cancer.Meanwhile,Faecalibacterium prausnitzii,Faecalibacterium duncaniae,and Prevotella copri were more commonly found in non-colorectal cancer.CONCLUSION Patients with colorectal cancer exhibit distinct differences in the composition and diversity of their colonic mucosal microbiota compared to those with non-colorectal cancer.This study was reviewed and approved by the Ethics Committee of Faculty of Medicine,Universitas Indonesia(No.KET-1517/UN2.F1/ETIK/PPM.00.02/2023).展开更多
BACKGROUND The gold standard for colorectal polyp screening is currently colonoscopy,but the miss rate is still high and the adenoma detection rate and polyp detection rate are still low.The risk factors include the p...BACKGROUND The gold standard for colorectal polyp screening is currently colonoscopy,but the miss rate is still high and the adenoma detection rate and polyp detection rate are still low.The risk factors include the patient,operators,and the tools used.The use of artificial intelligence(AI)in colonoscopy has gained popularity by assisting endoscopists in the detection and characterization of polyps.AIM To evaluate the diagnostic performance of AI-assisted colonoscopy[computer assisted diagnosis(CAD)eye function]for colorectal polyp characterization.METHODS This study used a cross-sectional design conducted at the Gastrointestinal Endoscopy Center of Dr.Cipto Mangunkusumo Hospital in January-May 2024 on adult patients with suspected colorectal polyps.RESULTS A total of 60 patients with 100 polyps were involved in this study.Based on the results of the examination,it was found that the AI CAD eye function examination had a sensitivity of 79.17%,specificity of 75.00%,positive predictive value(PPV)of 89.06%,negative predictive value(NPV)of 58.33%,and accuracy of 78.00%.In polyps with diminutive size,sensitivity was 86.27%,specificity was 60.00%,PPV was 95.65%,NPV was 30.00%,and accuracy was 83.93%.Meanwhile,in polyps with non-diminutive size,sensitivity was 61.90%,specificity was 78.26%,PPV was 72.22%,NPV was 69.23%,and accuracy was 70.45%.In polyps on the left side of the colon,sensitivity was 78.85%,specificity was 81.25%,PPV was 93.18%,NPV was 54.17%,and accuracy was 79.41%.Meanwhile,in rightsided polyps the sensitivity was 80.00%,specificity was 66.67%,PPV was 80.00%,NPV was 66.67%,and accuracy was 75.00%.In sessile polyps the sensitivity was 81.54%,specificity was 50.00%,PPV was 91.38%,NPV was 29.41%,and accuracy was 77.33%.Meanwhile,in non-sessile polyps,the sensitivity was 57.14%,specificity was 88.89%,PPV was 66.67%,NPV was 84.21%,and accuracy was 80.00%.CONCLUSION AI CAD eye function examination had a high sensitivity value in diminutive,sessile polyps and right-sided polyps and a high specificity in non-diminutive,non-sessile polyps and left-sided polyps.展开更多
文摘BACKGROUND Colorectal cancer is the third most common malignancy and the fourth leading cause of cancer-related deaths worldwide.Several studies have shown an association between gut microbiota and colorectal cancer.Gut microbiota is unique and can be influenced by geographic factors and habits.This study aimed to determine the diversity and composition of colonic mucosal microbiota in patients with and without colorectal cancer.AIM To determine the diversity and composition of colonic mucosal microbiota in patients with and without colorectal cancer in Indonesia.METHODS This case-control study included 59 subjects(35 colorectal cancer patients and 24 non-colorectal cancer patients indicated for colonoscopy at Dr.Cipto Mangunkusumo Gastrointestinal Endoscopy Center and Fatmawati Hospital.Microbiota examination was performed using 16S rRNA sequencing.Bioinformatics analysis was performed using the wf-metagenomics pipeline from EPI2Me-Labs(Oxford Nanopore Technologies platform).RESULTS Patients with colorectal cancer had a higher median index value on the Shannon index(3.28 vs 2.82,P>0.05)and a lower value on the Simpson index(0.050 vs 0.060,P>0.05).Significant differences in beta diversity were observed at the genus(P=0.002)and species levels(P=0.001).Firmicutes,Proteobacteria,Bacteroidetes,and Fusobacteria were the dominant phyla.The genera Bacteroides,Campylobacter,Peptostreptococcus,and Parvimonas were found more frequently in colorectal cancer,while Faecalibacterium,Haemophilus,and Phocaeicola were more frequently found in non-colorectal cancer.The relative abundance of Fusobacterium nucleatum,Bacteroides fragilis,Enterococcus faecalis,Campylobacter hominis,and Enterococcus faecalis species was significantly elevated in patients with colorectal cancer.Meanwhile,Faecalibacterium prausnitzii,Faecalibacterium duncaniae,and Prevotella copri were more commonly found in non-colorectal cancer.CONCLUSION Patients with colorectal cancer exhibit distinct differences in the composition and diversity of their colonic mucosal microbiota compared to those with non-colorectal cancer.This study was reviewed and approved by the Ethics Committee of Faculty of Medicine,Universitas Indonesia(No.KET-1517/UN2.F1/ETIK/PPM.00.02/2023).
文摘BACKGROUND The gold standard for colorectal polyp screening is currently colonoscopy,but the miss rate is still high and the adenoma detection rate and polyp detection rate are still low.The risk factors include the patient,operators,and the tools used.The use of artificial intelligence(AI)in colonoscopy has gained popularity by assisting endoscopists in the detection and characterization of polyps.AIM To evaluate the diagnostic performance of AI-assisted colonoscopy[computer assisted diagnosis(CAD)eye function]for colorectal polyp characterization.METHODS This study used a cross-sectional design conducted at the Gastrointestinal Endoscopy Center of Dr.Cipto Mangunkusumo Hospital in January-May 2024 on adult patients with suspected colorectal polyps.RESULTS A total of 60 patients with 100 polyps were involved in this study.Based on the results of the examination,it was found that the AI CAD eye function examination had a sensitivity of 79.17%,specificity of 75.00%,positive predictive value(PPV)of 89.06%,negative predictive value(NPV)of 58.33%,and accuracy of 78.00%.In polyps with diminutive size,sensitivity was 86.27%,specificity was 60.00%,PPV was 95.65%,NPV was 30.00%,and accuracy was 83.93%.Meanwhile,in polyps with non-diminutive size,sensitivity was 61.90%,specificity was 78.26%,PPV was 72.22%,NPV was 69.23%,and accuracy was 70.45%.In polyps on the left side of the colon,sensitivity was 78.85%,specificity was 81.25%,PPV was 93.18%,NPV was 54.17%,and accuracy was 79.41%.Meanwhile,in rightsided polyps the sensitivity was 80.00%,specificity was 66.67%,PPV was 80.00%,NPV was 66.67%,and accuracy was 75.00%.In sessile polyps the sensitivity was 81.54%,specificity was 50.00%,PPV was 91.38%,NPV was 29.41%,and accuracy was 77.33%.Meanwhile,in non-sessile polyps,the sensitivity was 57.14%,specificity was 88.89%,PPV was 66.67%,NPV was 84.21%,and accuracy was 80.00%.CONCLUSION AI CAD eye function examination had a high sensitivity value in diminutive,sessile polyps and right-sided polyps and a high specificity in non-diminutive,non-sessile polyps and left-sided polyps.
