The purpose of this study was to develop and validate a nomogram model for the prediction of survival outcome in rectal cancer patients who underwent surgical resection. A total of 9,919 consecutive patients were retrospectively identified using the Surveillance, Epidemiology, and End Results (SEER) database. Significant prognostic factors were determined by the univariate and multivariate Cox analysis. The nomogram model for the prediction of cancer-specific survival (CSS) in rectal cancer patients were developed based on these prognostic variables, and its predictive power was assessed by the concordance index (C-index). Calibration curves were plotted to evaluate the associations between predicted probabilities and actual observations. The internal and external cohort were used to further validate the predictive performance of the prognostic nomogram. All patients from the SEER database were randomly split into a training cohort ( = 6,944) and an internal validation cohort ( = 2,975). The baseline characteristics of two cohorts was comparable. Independent prognostic factors were identified as age, pT stage, lymph node metastasis, serum CEA level, tumor size, differentiation type, perineural invasion, circumferential resection margin involvement and inadequate lymph node yield. In the training cohort, the C-index of the nomogram was 0.719 (95% CI: 0.696-0.742), which was significantly higher than that of the TNM staging system (C-index: 0.606, 95% CI: 0.583-0.629). The nomogram had a C-index of 0.726 (95% CI: 0.691-0.761) for the internal validation cohort, indicating a good predictive power. In addition, an independent cohort composed of 202 rectal cancer patients from our institution were enrolled as the external validation. Compared with the TNM staging system (C-index: 0.573, 95% CI: 0.492-0.654), the prognostic nomogram still showed a better predictive performance, with the C-index of 0.704 (95% CI: 0.626-0.782). Calibration plots showed a good consistency between predicted probability and the actual observation in the training and two validation cohorts. The nomogram showed an excellent predictive ability for survival outcome of rectal cancer patients, and it might provide an accurate prognostic stratification and help clinicians determine individualized treatment strategies.
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http://dx.doi.org/10.3389/pore.2023.1611014 | DOI Listing |
World J Gastrointest Oncol
January 2025
Department of Hepatobiliary and Pancreaticosplenic Surgery, Jingzhou Hospital Affiliated to Yangtze University, Jingzhou 434100, Hubei Province, China.
Background: The liver, as the main target organ for hematogenous metastasis of colorectal cancer, early and accurate prediction of liver metastasis is crucial for the diagnosis and treatment of patients. Herein, this study aims to investigate the application value of a combined machine learning (ML) based model based on the multiparameter magnetic resonance imaging for prediction of rectal metachronous liver metastasis (MLM).
Aim: To investigate the efficacy of radiomics based on multiparametric magnetic resonance imaging images of preoperative first diagnosed rectal cancer in predicting MLM from rectal cancer.
Prostate Int
September 2024
Gazi University School of Medicine, Urology Department, Ankara, Turkey.
Aim: To investigate the predictive value of lesion length in multiparametric prostate magnetic resonance imaging with respect to prostate volume for clinically significant prostate cancer diagnosis in targeted biopsies.
Materials And Methods: The data of biopsy-naïve patients in the Turkish Urooncology Association Prostate Cancer Database who underwent targeted prostate biopsies were included in this study. Lesion density is calculated as the ratio of lesion length (mm) in MR to prostate volume (cc).
Prostate Int
September 2024
Departments of Urology, All India Institute of Medical Sciences, New Delhi, India.
Introduction: Up to 40% of patients with suspected prostate cancer (PCa) have a negative prebiopsy magnetic resonance imaging (nMRI), and up to 15% of them may have clinically significant PCa (csPCa). The ability to predict the presence of csPCa despite nMRI may help avoid unnecessary biopsies. We aimed to determine the negative predictive value (NPV) of mpMRI, the influence of MRI reporting patterns in clinical practice, and the factors that might predict csPCa among men with an nMRI.
View Article and Find Full Text PDFCase Rep Surg
January 2025
Department of General Surgery, University of Balamand, Beirut, Lebanon.
Iatrogenic urethral-rectal perforation represents a rare but severe complication arising from medical interventions, notably highlighted in the context of Foley catheter insertion. This case report outlines the presentation, diagnosis, management, and outcomes of a 71-year-old male patient who experienced iatrogenic rectal perforation during the routine insertion of a Foley catheter, against the backdrop of several predisposing factors, such as atrial fibrillation, valvular disease, benign prostatic hyperplasia, urethral stenosis, and colorectal cancer with liver metastasis. The inadvertent creation of a rectourethral fistula during the procedure led to an urgent multidisciplinary approach involving surgery and postoperative management, including fecal and urine diversion and antibiotic therapy.
View Article and Find Full Text PDFJ Gastrointest Oncol
December 2024
Medical Physics Unit, Department of Oncology, Faculty of Medicine, McGill University, Montreal, QC, Canada.
Background: Orthotopic models offer a more accurate representation of colorectal cancer (CRC) compared to subcutaneous models. Despite promising results from the reported intra-rectal models, establishing a standardized method for CRC research remains challenging due to model variability, hindering comprehensive studies on CRC pathogenesis and treatment modalities, such as brachytherapy. This study aimed to establish a standardized workflow for an orthotopic intra-rectal animal model to induce the growth of colorectal adenocarcinoma in male and female mice.
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