Purpose: This study was performed to predict individualized treatment strategies in ruptured abdominal aortic aneurysm (rAAA) by estimating the survival benefit of endovascular aneurysm repair (EVAR) and open surgical repair (OSR) based on anatomical and physiological features using a causal inference model. Methods: This retrospective study included 45 patients with de novo rAAA who underwent EVAR or OSR between 2012 and 2024. Thirty-three variables were analyzed. The model estimated individualized treatment effects (ITE) for 30-day survival.Model interpretability was assessed using Shapley Additive Explanations (SHAP) analysis. Five-fold cross-validation, receiver operating characteristic (ROC) analysis, and calibration plots were used for model evaluation. A clinical decision tree was developed to derive simplified decision rules. Results: The mean ITE was 0.22 ± 0.42, with 33% of patients classified as OSR-benefit candidates. SHAP analysis revealed that suprarenal angle, infrarenal angle, iliac anatomy, and proximal neck characteristics strongly influenced treatment effects. However, some predictors, such as low hemoglobin and systolic blood pressure favoring OSR, conflicted with clinical intuition. ROC analysis showed an area under the curve of 1.00, but calibration suggested overfitting due to a small sample size. Treatment-matched patients had a higher 30-day mortality rate than mismatched patients, suggesting potential bias or unmeasured confounding. The decision tree identified clinically relevant features but displayed structural inconsistencies and impractical cutoff values due to the limited sample size. Conclusion The X-learner model demonstrated the feasibility of individualized treatment prediction in rAAA but suffered from overfitting and limited generalizability. Validation with larger multicenter cohorts is necessary to confirm clinical applicability.

Purpose: To develop the 2025 update to the Korean colorectal cancer (CRC) screening guidelines by systematically evaluating recent evidence, integrating domestic data, and addressing changes since the 2015 guideline revision, thereby providing an evidence-based standard for clinicians and policymakers. Methods: A multidisciplinary committee developed the guidelines using the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) methodology. The process included formulation of three key questions addressing screening efficacy, diagnostic accuracy, and optimal screening age and interval. A systematic review of international guidelines and primary literature was conducted, yielding 327 eligible studies. In addition, a utility-based analysis using a Markov model was performed to determine optimal screening ages and intervals. Results: The evidence synthesis identified high-certainty evidence supporting the use of the fecal immunochemical test (FIT) for reducing CRC mortality and moderate-certainty evidence for colonoscopy. Evidence for computed tomographic colonography (CTC) and stool DNA testing was rated as very low certainty. Based on the evidence review and cost-utility analysis, the committee conditionally recommends CRC screening for asymptomatic, average-risk adults aged 45–74 years using either colonoscopy every 10 years or FIT every 1–2 years. CTC and stool DNA testing were not recommended owing to insufficient evidence. Conclusion The 2025 Korean Guidelines for Colorectal Cancer Screening present updated, evidence-based recommendations tailored to the domestic healthcare context. By conditionally endorsing both colonoscopy and FIT for individuals aged 45–74 years, these guidelines aim to improve population-level screening effectiveness and reduce the burden of CRC in South Korea.