Unlabelled: The aim of the study was to answer the question whether there are differences in the progression of the disease and its morphology, dependent of the patient's age, as well as show colorectal cancer differences between young and elderly patients.
Material And Methods: During the period between 2009 and 2011, 747 patients with rectal carcinoma, and 478 with colon cancer underwent surgery at the Department of General and Colorectal Surgery. The study group comprised patients under the age of 40 years (56 patients) and >80 years (90 patients). The following were subject to analysis: gender, tumor location, percentage of radical and palliative procedures, clinical and histopathological staging, as well the differences in the morphology of the tumor. The χ2 test and Yates' correction were used for statistical analysis. p<0.05 was considered as statistically significant.
Results: A higher incidence of rectal carcinoma was observed in younger patients (p=0.004). Amongst the younger patients 30.3% were diagnosed with stage III cancer, while 35.7% with stage IV. In case of elderly patients 30.6% were diagnosed with stage III cancer, while 30.7% with stage IV. In 53.3% of young patients, local lymph node metastases were observed, while in the elderly 41.8%. No statistically significant difference was observed, considering the total number of lymph nodes metastases. However, in case of stage N2, results were unfavorable for young patients 31.8% vs 17% in case of the elderly. Mucogenic adenocarcinoma incidence was similar in both groups. In case of patients< 40 years we observed a higher incidence of poorly differentiated tumors, as compared to the elderly patients (>80 years).
Conclusions: 1. It is necessary to create appropriate prevention programs for young community, and improvement of public awareness in this age group. 2. Colorectal cancer (CRC) in young patients is often recognized in advanced stage. 3. A high percentage of unresectable tumors in group of elderly patients shows that CRC is still diagnosed too late in Poland.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.2478/pjs-2013-0068 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
E. Coli cytotoxic necrotizing factor-1 promotes colorectal carcinogenesis by causing oxidative stress, DNA damage and intestinal permeability alteration.
J Exp Clin Cancer Res
January 2025
Department of Cardiovascular, Endocrine-Metabolic Diseases and Aging, Istituto Superiore di Sanità, Rome, Italy.
Background: Bacterial toxins are emerging as promising hallmarks of colorectal cancer (CRC) pathogenesis. In particular, Cytotoxic Necrotizing Factor 1 (CNF1) from E. coli deserves special consideration due to the significantly higher prevalence of this toxin gene in CRC patients with respect to healthy subjects, and to the numerous tumor-promoting effects that have been ascribed to the toxin in vitro.
View Article and Find Full Text PDFEfficacy and safety of neoadjuvant bevacizumab plus chemotherapy in locally advanced gastric cancer patients: a retrospective, comparative study.
World J Surg Oncol
January 2025
Colorectal Surgery Department, The Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University/ Hunan Cancer Hospital, No. 283 Tongzipo Road, Yuelu District, Changsha, Hunan, 410013, China.
Objective: The clinical benefits of neoadjuvant bevacizumab plus chemotherapy in locally advanced gastric cancer patients are controversial. This study intended to evaluate the efficacy and safety of neoadjuvant bevacizumab plus chemotherapy in these patients.
Methods: In this retrospective study, 71 locally advanced gastric cancer patients receiving neoadjuvant bevacizumab plus chemotherapy or neoadjuvant chemotherapy alone were divided into bevacizumab plus chemo group (N = 23) and chemo group (N = 48).
Prognostic models of immune-related cell death and stress unveil mechanisms driving macrophage phenotypic evolution in colorectal cancer.
J Transl Med
January 2025
Department of Gastrointestinal Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, Henan, China.
Background: Tumor microenvironment (TME), particularly immune cell infiltration, programmed cell death (PCD) and stress, has increasingly become a focal point in colorectal cancer (CRC) treatment. Uncovering the intricate crosstalk between these factors can enhance our understanding of CRC, guide therapeutic strategies, and improve patient prognosis.
Methods: We constructed an immune-related cell death and stress (ICDS) prognostic model utilizing machine learning methodologies.
Meta Analysis of Methylenetetrahydrofolate Reductase (MTHFR) C677T polymorphism and its association with folate and colorectal cancer.
BMC Cancer
January 2025
Department of Laboratory Medicine, Affiliated Gaozhou People's Hospital, Guangdong Medical University, Maoming, 525200, P.R. China.
Background: DNA hypomethylation and uracil misincorporation into DNA, both of which have a very important correlation with colorectal carcinogenesis. Folate plays a crucial role in DNA synthesis, acting as a coenzyme in one-carbon metabolism, which involves the synthesis of purines, pyrimidines, and methyl groups. MTHFR, a key enzyme in folate metabolism, has been widely studied in relation to neural tube defects and hypertension, but its role in colorectal cancer remains underexplored.
View Article and Find Full Text PDFArtificial intelligence methods applied to longitudinal data from electronic health records for prediction of cancer: a scoping review.
BMC Med Res Methodol
January 2025
Leeds Institute of Clinical Trials Research, University of Leeds, Clarendon Way, Leeds, LS2 9NL, UK.
Background: Early detection and diagnosis of cancer are vital to improving outcomes for patients. Artificial intelligence (AI) models have shown promise in the early detection and diagnosis of cancer, but there is limited evidence on methods that fully exploit the longitudinal data stored within electronic health records (EHRs). This review aims to summarise methods currently utilised for prediction of cancer from longitudinal data and provides recommendations on how such models should be developed.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!