Introduction: To shorten the time for diagnosis of suspected colorectal cancer (CRC), a standardized colorectal cancer referral pathway (CCRP) was introduced in Sweden in September 2016. However, the effects of the CCRP are still uncertain, and CRC is also found in patients undergoing a routine colonoscopy.
Objective: To identify all CRC-cases in the Region Örebro County and to investigate which diagnostic pathway they were diagnosed. Furthermore, to investigate the reasons for and possible effect of not being included in the CCRP for cases found colonoscopy.
Methods: Review of medical records of patients with CRC referred to the department of surgery in the Region Örebro County in 2016-2018 ( = 459).
Results: In CRC-cases found through colonoscopy ( = 347), 37.5% were diagnosed a routine waiting list and 62.5% within the CCRP. No difference in tumor stage or tumor grade was found between the two groups. The non-CCRP showed a longer time to diagnosis than the CCRP group (21.5 days, IQR 7-43 vs. 13 days, IQR 8-17 ( < .001), respectively). Non-rectal cancer was more common in the non-CCRP group (81.5% vs. 57.6%, < .001). The non-CCRP group had lower median Hb-value (106, IQR 87-129 vs. 117, IQR 101-136, = .001). 85% of the non-CCRP group was found to meet one or more CCRP referral criteria, with bleeding anemia being the dominant criterion to meet.
Conclusion: The CCRP did not appear to improve prognostic outcomes for CRC-patients. NCT04585516.
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http://dx.doi.org/10.1080/00365521.2021.1899276 | DOI Listing |
BMC Cancer
January 2025
Department of Gastrointestinal Surgery I Section, Renmin Hospital of Wuhan University, Wuhan, 430060, China.
Background: Gastric cancer peritoneal metastasis lacks effective predictive indices. This article retrospectively explored predictive values of DNA ploidy, stroma, and nucleotyping in gastric cancer peritoneal metastasis.
Methods: A comprehensive analysis was conducted on specimens obtained from 80 gastric cancer patients who underwent gastric resection at the Department of Gastrointestinal Surgery of Wuhan University Renmin Hospital.
Ann Surg Oncol
January 2025
Division of Colorectal Surgery, Changzheng Hospital, Navy Medical University, Shanghai, China.
Nat Med
January 2025
Vall d'Hebron Hospital Campus and Vall d'Hebron Institute of Oncology (VHIO), University of Vic - Central University of Catalonia, Barcelona, Spain.
Encorafenib + cetuximab (EC) is approved for previously treated BRAF V600E-mutant metastatic colorectal cancer (mCRC) based on the BEACON phase 3 study. Historically, first-line treatment of BRAF V600E-mutant mCRC with chemotherapy regimens has had limited efficacy. The phase 3 BREAKWATER study investigated EC+mFOLFOX6 versus standard of care (SOC) in patients with previously untreated BRAF V600E mCRC.
View Article and Find Full Text PDFInt J Colorectal Dis
January 2025
Hereditary Digestive Tract Tumors Unit, Fondazione IRCCS Istituto Nazionale Dei Tumori, Via Giacomo Venezian 1, 20133, Milan, Italy.
Purpose: In this study, we investigated the progression of high-grade dysplasia (HGD)/CRC in patients with hereditary colorectal cancer syndromes (HCSS) and concomitant inflammatory bowel diseases (IBDs).
Methods: We described the natural history of a series of patients with confirmed diagnosis of hereditary colorectal cancer syndromes (HCCSs) and concomitant IBDs who were referred to the Hereditary Digestive Tumors Registry at the Fondazione IRCCS Istituto Nazionale dei Tumori of Milan.
Results: Between January 1989 and April 2024, among 450 patients with APC-associated polyposis and 1050 patients with Lynch syndrome (LS), we identified six patients with IBDs (five with UC, one with ileal penetrating CD) and concomitant HCCSs (five with LS, one with APC-associated polyposis).
Sci Rep
January 2025
Ministry of Higher Education, Mataria Technical College, Cairo, 11718, Egypt.
The current work introduces the hybrid ensemble framework for the detection and segmentation of colorectal cancer. This framework will incorporate both supervised classification and unsupervised clustering methods to present more understandable and accurate diagnostic results. The method entails several steps with CNN models: ADa-22 and AD-22, transformer networks, and an SVM classifier, all inbuilt.
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