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Competing-Risk Nomogram for Predicting Cancer-Specific Survival in Multiple Primary Colorectal Cancer Patients after Surgery
Published on: September 27, 2024
Prognostic Scoring System for Pulmonary Metastasectomy in Colorectal Cancer: External Validation and Clinical
Hikaru Takahashi1, Yoshikane Yamauchi1, Tomoki Nishida1
1Department of Surgery, Teikyo University School of Medicine, Tokyo 173-8605, Japan.
Abstract:
Background: Predicting long-term outcomes after pulmonary metastasectomy for colorectal cancer remains challenging because existing prognostic methods lack precision. We developed and validated a prognostic scoring system derived from a major international meta-analysis to improve risk stratification and to evaluate the benefit of adjuvant chemotherapy across risk groups. Methods: Using a Japanese registry of 819 patients who underwent lung resection between 2010 and 2019, we constructed a 0-13-point score based on eight variables including tumor size, number, biological markers, and intrathoracic lymph node status, which may require intraoperative or pathological confirmation. Granular data on chemotherapy regimens, timing, and duration were unavailable. Patients were classified as low, intermediate, or high risk. The primary analysis used inverse probability of treatment weighting to adjust for baseline imbalances; however, only 819 of 1657 patients (49.4%) had complete prognostic data, introducing potential selection bias. Results: The score separated patients into three groups with distinct five-year survival rates: 81.1% (low), 67.8% (intermediate), and 59.1% (high). In high-risk patients, chemotherapy was associated with improved overall survival but did not delay recurrence. In low-risk patients, chemotherapy correlated with reduced recurrence-free survival, a finding that persisted after adjustment. Conclusions: This validated scoring system aids individualized surgical decision making by identifying patients unlikely to benefit from routine postoperative chemotherapy. Observed survival advantages in high-risk patients may reflect selection of fitter individuals rather than direct treatment effects, underscoring the need to address selection bias in future trials.