Nomogram model for predicting cancer-specific mortality in patients with early-onset colorectal cancer: a competing risk analysis insight from the SEER database and an external validation cohort.

Background: Early-onset colorectal cancer (EOCRC) is increasing in incidence and poses a growing threat. Urgent research is needed, especially in survival analysis, to enhance comprehension and treatment strategies. This study aimed to explore the risk factors associated with cancer-specific mortality (CSM) and other-cause mortality (OCM) in patients with EOCRC. Additionally, the study aimed to develop a nomogram predicting CSM using a competitive risk model and validate its accuracy through the use of training, using internal and external cohorts. Methods: Data from EOCRC patients were collected from the Surveillance, Epidemiology, and End Results (SEER) database (2008-2017). EOCRC patients who were treated at a tertiary hospital in northeast China between 2014 and 2020 were also included in the study. The SEER data were divided into the training and validation sets at a 7:3 ratio. A univariate Cox regression model was employed to identify prognostic factors. Subsequently, multivariate Cox regression models were applied to ascertain the presence of independent risk factors. A nomogram was generated to visualize the results, which were evaluated using the concordance index (C-index), area under the curve (AUC), and calibration curves. The clinical utility was assessed via decision curve analysis (DCA). Results: Multivariable Cox regression analysis demonstrated that factors such as race, tumor differentiation, levels of carcinoembryonic antigen (CEA), marital status, histological type, American Joint Committee on Cancer (AJCC) stage, and surgical status were independent risk factors for CSM in EOCRC patients. In addition, age, gender, chemotherapy details, CEA levels, marital status, and AJCC stage were established as independent risk factors for OCM in individuals diagnosed with EOCRC. A nomogram was developed using the identified independent risk factors, demonstrating excellent performance with a C-index of 0.806, 0.801, and 0.810 for the training, internal validation, and external validation cohorts, respectively. The calibration curves and AUC further confirmed the accuracy and discriminative ability of the nomogram. Furthermore, the DCA results indicated that the model had good clinical value. Conclusions: In this study, a competing risk model for CSM was developed in EOCRC patients. The model demonstrates a high level of predictive accuracy, providing valuable insights into the treatment decision-making process.

A brief overview of single-port laparoscopic appendectomy as an optimal surgical procedure for patients with acute appendicitis: still a long way to go.

Single-port laparoscopic appendectomy (SPLA) has become a good alternative to the traditional surgical treatment of acute appendicitis, due to its advantages of small incision, mild postoperative pain, short hospital stay, and good cosmetic effect. However, the further application of SPLA has been restricted by its relatively long operating time, high level of operating difficulty, and increased equipment and technical requirements. Clinical teams worldwide have attempted to improve and optimize SPLA technical protocols and equipment to maintain stable intraoperative pneumoperitoneal pressure, improve the 'triangle relationship' of operating angles, and develop new surgical procedures with less trauma and higher cost-effectiveness. Here, new SPLA techniques reported over the past decade are reviewed and compared, with the aim of providing new insights into technical improvements, equipment upgrades and clinical studies in the coming years.

Nomogram for predicting prolonged postoperative ileus in colorectal cancer based on age and inflammatory markers.

Aim: To explore the relationship between inflammatory markers and prolonged postoperative ileus (PPOI), and to establish a nomogram for predicting PPOI. Patients & methods: The data of 229 patients were analyzed retrospectively. Univariate and multivariate logistic regression analysis were used to analyze the risk factors affecting the occurrence of PPOI. The predictive model of PPOI was established and verified internally. Results: Postoperative PPOI occurred in 87 (38.0%) of all 229 patients. Our study showed that age, preoperative neutrophil-lymphocyte ratio and changes in neutrophil-lymphocyte ratio were independent risk factors for PPOI. Conclusion: The nomograms established based on these independent risk factors have good predictive efficacy and may be able to guide clinicians to individualize the diagnosis and treatment.