Background: Old age at diagnosis is associated with poor survival in colorectal cancer (CRC) for unknown reasons. Recent data show that colonoscopy is efficient in preventing left-sided cancers only. We examine the association of Tumor Node Metastasis (TNM) classes with diagnostic age and patient characteristics.
Methods: The Swedish Family-Cancer Database has data on TNM classes on 6,105 CRC adenocarcinoma patients. Ordinal logistic regression analysis was performed to model tumor characteristics according to age at diagnosis, tumor localization, gender, socioeconomic status, medical region and family history. The results were compared to results from survival analysis.
Results: The only parameters systematically associated with TNM classes were age and tumor localization. Young age at diagnosis was a risk factor for aggressive CRC, according to stage, N and M with odds ratios (ORs) ranging from 1.80 to 1.93 for diagnosis before age 50 years compared to diagnosis at 80+ years. All tumor characteristics, particularly T, were worse for colon compared to rectal tumors. Right-sided tumors showed worse characteristics for all classifiers but M. The survival analysis on patients diagnosed since 2000 showed a hazard ratio of 0.55 for diagnosis before age 50 years compared to diagnosis at over 80 years and a modestly better prognosis for left-sided compared to right-sided tumors.
Conclusions: The results showed systematically more aggressive tumors in young compared to old patients. The poorer survival of old patients in colon cancer was not related to the available tumor characteristics. However, these partially agreed with the limited colonoscopic success with right-sided tumors.
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http://dx.doi.org/10.1186/1471-2407-10-688 | DOI Listing |
Sci Rep
December 2024
Department of Biology, School of Medicine, University of Zagreb, Salata 3, 10000, Zagreb, Croatia.
Retinoblastoma, a rare childhood eye cancer, has hereditary and non-hereditary forms. While TNM classification helps in prognosis, understanding molecular mechanisms is vital for the clinical behavior of retinoblastoma prediction. Our study aimed to analyze the expression levels of key Wnt pathway proteins, GSK3β, LEF1, β-catenin, and DVL1, and associate them to non-phosphorylated active form (pRb) and the phosphorylated inactive form (ppRb) and N-myc expression, in retinoblastoma cells and healthy retinal cells, in order to elucidate their roles in retinoblastoma and identify potential targets that could help to improve diagnostic and therapy.
View Article and Find Full Text PDFBackground: Hepatocellular carcinoma (HCC) is the most common cause of cancer-related death in Saudi Arabia. Our study aimed to investigate the patterns of HCC and the effect of TNM staging, Alfa-fetoprotein (AFP), and Child-Turcotte Pugh (CTP) on patients' overall survival (OS).
Methods: A retrospective analysis was conducted on 43 HCC patients at a single oncology center in Saudi Arabia from 2015 to 2020.
Cancers (Basel)
December 2024
Pathology Unit, Department of Surgical Sciences and Integrated Diagnostics (DISC), University of Genoa, 16132 Genoa, Italy.
The Esophageal Adenocarcinoma Study Group Europe (EACSGE) recently proposed a granular histologic classification of esophageal-esophago-gastric junctional adenocarcinomas (EA-EGJAs) based on the study of naïve surgically resected specimens that, when combined with the pTNM stage, is an efficient indicator of prognosis, molecular events, and response to treatment. In this study, we compared histologic classes of endoscopic biopsies taken before surgical resection with those of the surgical specimen, to evaluate the potential of the EACSGE classification at the initial diagnostic workup. A total of 106 EA-EGJA cases with available endoscopic biopsies and matched surgical resection specimens were retrieved from five Italian institutions.
View Article and Find Full Text PDFSurgery
February 2025
American College of Surgeons Cancer Programs, Chicago, IL; Department of Surgery, Mayo Clinic, Rochester, MN. Electronic address:
Background: Although cancer prognosis is most commonly estimated by tumor stage, survival is multifactorial. Our objective was to develop an American College of Surgeons "Biliary Tract Cancer Survival Calculator" prototype using machine learning to generate personalized survival estimates based on patient, tumor, and treatment factors.
Methods: The National Cancer Database was used to identify all patients with biliary tract malignancies between 2010 and 2017 including intrahepatic bile duct, extrahepatic bile duct, and gallbladder cancers.
Clin Epidemiol
October 2024
Biomedical Center, Faculty of Medicine, Charles University, Pilsen, Czech Republic.
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