Aim: To evaluate changes in colorectal cancer (CRC) survival over the last 20 years.
Methods: We compared two groups of consecutive CRC patients that were prospectively recruited: Group I included 1990 patients diagnosed between 1980 and 1994. Group II included 871 patients diagnosed in 2001.
Results: The average follow up time was 21 mo (1-229) for Group I and 50 mo (1-73.4) for Group II. Overall median survival was significantly longer in Group II than in Group I (73 mo vs 25 mo, P < 0.001) and the difference was significant for all tumor stages. Post surgical mortality was 8% for Group Iand 2% for Group II (P < 0.001). Only 17% of GroupI patients received chemotherapy compared with 50% of Group II patients (P < 0.001).
Conclusion: Survival in colorectal cancer patients has doubled over the past 20 years. This increase seems to be partly due to the generalization in the administration of chemotherapy and to the decrease of post surgical mortality.
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http://dx.doi.org/10.3748/wjg.v16.i7.862 | DOI Listing |
Mol Cancer
December 2024
Department of Interventional Radiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, 450052, China.
Cancer-associated fibroblasts (CAFs) exert multiple tumor-promoting functions and are key contributors to drug resistance. The mechanisms by which specific subsets of CAFs facilitate oxaliplatin resistance in colorectal cancer (CRC) have not been fully explored. This study found that THBS2 is positively associated with CAF activation, epithelial-mesenchymal transition (EMT), and chemoresistance at the pan-cancer level.
View Article and Find Full Text PDFCancer Cell Int
December 2024
State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China.
Trends Cancer
December 2024
Charité - Universitätsmedizin Berlin, Institute of Pathology, Berlin, Germany; German Cancer Consortium (DKTK), Partner Site Berlin, German Cancer Research Center (DKFZ), Heidelberg, Germany; Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA; Department of Pharmacology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA. Electronic address:
In 1982, the RAS genes HRAS and KRAS were discovered as the first human cancer genes, with KRAS later identified as one of the most frequently mutated oncogenes. Yet, it took nearly 40 years to develop clinically effective inhibitors for RAS-mutant cancers. The discovery in 2013 by Shokat and colleagues of a druggable pocket in KRAS paved the way to FDA approval of the first covalently binding KRAS inhibitors, sotorasib and adagrasib, in 2021 and 2022, respectively.
View Article and Find Full Text PDFSurgery
December 2024
Department of Colorectal Surgery, Digestive Disease & Surgery Institute, Cleveland Clinic, Cleveland, OH. Electronic address:
Background: Endoscopic submucosal dissection is increasingly used to treat early-stage colorectal cancer. This study evaluated the feasibility of endoscopic submucosal dissection in this setting and the determinants of lymph node metastasis.
Methods: We reviewed patients who underwent colorectal endoscopic submucosal dissection for early-stage colorectal cancer at a tertiary center between 2011 and 2023.
Int J Med Inform
December 2024
Chongqing Cancer Multiomics Big Data Application Engineering Research Center, Chongqing University Cancer Hospital, Chongqing 400030, China. Electronic address:
Background: With advancements in healthcare, traditional VTE risk assessment tools are increasingly insufficient to meet the demands of high-quality care, underscoring the need for innovative and specialized assessment methods.
Objective: Owing to the remarkable success of machine learning in supervised learning and disease prediction, our objective is to develop a reliable and efficient model for assessing VTE risk by leveraging the fundamental data and clinical characteristics of colorectal cancer patients within our medical facility.
Methods: Six commonly used machine learning algorithms were utilized in our study to predict the occurrence of VTE in patients with rectal cancer.
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