Purpose: Adequate lymphadenectomy is critical for accurate nodal staging and planning adjuvant therapy in colon cancer. However, the optimal lymph node (LN) yield for stage II right-sided colon cancer (RSCC) is still unclear. This population-based study aimed to determine the optimal LN yield associated with survival and LN positivity in patients with stage II RSCC.
Methods: All patients with stage II-III RSCC were identified from the Surveillance, Epidemiology, and End Results database over a 10-year interval (2006-2015). The optimal threshold for LN yield was explored using an outcome-oriented approach based on survival and LN positivity.
Results: The median number of LNs examined for all 17,385 patients with stage II RSCC was 17 (IQR 12-23). Nineteen LNs were determined as the optimal cut-off point to maximize survival benefit from lymphadenectomy. Increased LN yield was associated with a gradual increase in the risk of node positivity, with no change after 19 nodes. Compared with patients with 19 or more LNs examined, the group with fewer LNs had a significantly poor cancer-specific survival (< 12 nodes: hazard ratio (HR) 2.26, P < 0.001; 12-18 nodes: HR 1.58, P < 0.001) and overall survival (< 12 nodes: HR 1.80, P < 0.001; 12-18 nodes: HR 1.31, P < 0.001). Similar survival results were found in the validation cohort. Patients with older age, small tumor size, and appendix and transverse colon cancer were more likely to receive inadequate LN harvest.
Conclusion: A minimum of 19 LNs is needed to be examined for optimal survival and adequate node staging in lymph node-negative RSCC.
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http://dx.doi.org/10.1007/s00384-019-03483-z | DOI Listing |
Ann Surg Oncol
January 2025
Department of Medical Oncology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, Fujian, China.
Background: Colon and rectum cancer (CRC) is a major health burden in China, with notable gender disparities. This study was designed to analyze trends in CRC incidence, prevalence, and mortality from 1990 to 2021 and to project future trends.
Methods: Using data from the Global Burden of Disease (GBD) Study 2021, we examined CRC burden in China, including incidence, prevalence, mortality, disability-adjusted life years (DALYs), years lived with disability (YLDs), and years of life lost (YLLs).
ACS Appl Bio Mater
January 2025
Department of Chemistry, Indian Institute of Technology Gandhinagar, Palaj, Gandhinagar, Gujarat 382355, India.
Golgi apparatus (GA) and endoplasmic reticulum (ER) are two of the interesting subcellular organelles that are critical for protein synthesis, folding, processing, post-translational modifications, and secretion. Consequently, dysregulation in GA and ER and cross-talk between them are implicated in numerous diseases including cancer. As a result, simultaneous visualization of the GA and ER in cancer cells is extremely crucial for developing cancer therapeutics.
View Article and Find Full Text PDFUnited European Gastroenterol J
January 2025
Department of General Surgery, Peking Union Medical College Hospital, Beijing, China.
RSC Adv
January 2025
Department of Pharmaceutical Sciences, Maharshi Dayanand University Rohtak 124001 India
Cancer is a major global concern. Despite considerable advancements in cancer therapy and control, there are still large gaps and requirements for development. In recent years, various naturally occurring anticancer drugs have been derived from natural resources, such as alkaloids, glycosides, terpenes, terpenoids, flavones, and polyphenols.
View Article and Find Full Text PDFFront Med (Lausanne)
January 2025
Department of General Surgery, Wuxi People's Hospital Affiliated to Nanjing Medical University, Wuxi, China.
Background: Gastroparesis following complete mesocolic excision (CME) can precipitate a cascade of severe complications, which may significantly hinder postoperative recovery and diminish the patient's quality of life. In the present study, four advanced machine learning algorithms-Extreme Gradient Boosting (XGBoost), Random Forest (RF), Support Vector Machine (SVM), and -nearest neighbor (KNN)-were employed to develop predictive models. The clinical data of critically ill patients transferred to the intensive care unit (ICU) post-CME were meticulously analyzed to identify key risk factors associated with the development of gastroparesis.
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