Radiation is often used as the primary treatment for a range of cancers. Nonetheless, its ability to trigger secondary tumors has emerged as a significant issue. Therefore, gaining insight into and predicting radiation-induced secondary cancers is essential for enhancing the long-term prognosis of cancer survivors. Background and Objectives: Previous studies have identified several factors; however, research on the use of serum-based inflammatory markers as prognostic tools for predicting radiation-induced secondary malignancies is limited. Investigating the potential of serum-based inflammation prognostic scores could provide a minimally invasive and affordable method for the early prediction of secondary malignancies. Methods: We retrospectively analyzed a patient cohort with radiation-induced secondary malignancy from the electronic database MIMIC-IV to investigate whether a serum-based inflammatory marker score can serve as a predictive tool. Results: This study seeks not only to assess the efficacy of the risk score, but also to develop a clinical utility tool nomogram for predicting the occurrence of radiation-induced secondary cancers. A RISM of 4.28% was observed in a cohort from the MIMIC-IV database using SIRI-RT as a risk index, with the Charlson comorbidity index, chemotherapy, and creatinine levels as significant confounding risk factors. Conclusions: Our study suggests that elevated serum-based inflammation prognostic scores and the nomogram developed herein can be used to predict a greater likelihood of developing secondary malignancies following radiation therapy.
放射治疗常作为多种癌症的主要治疗手段,但其诱发继发性肿瘤的风险已成为重要临床问题。因此,深入理解并预测放射治疗诱发的继发性肿瘤对于改善癌症幸存者的长期预后至关重要。研究背景与目的:既往研究已识别出若干风险因素,但基于血清炎症标志物预测放射诱发继发性恶性肿瘤的研究尚不充分。探索血清炎症预后评分的预测潜力,可为继发性恶性肿瘤的早期预测提供微创且经济有效的方法。研究方法:我们回顾性分析了MIMIC-IV电子数据库中放射诱发继发性恶性肿瘤患者队列,旨在验证血清炎症标志物评分能否作为有效预测工具。研究结果:本研究不仅评估了风险评分的预测效能,还构建了用于预测放射诱发继发性肿瘤发生风险的临床实用列线图模型。基于SIRI-RT风险指数对MIMIC-IV数据库队列的分析显示,放射诱发继发性恶性肿瘤发生率为4.28%,其中查尔森合并症指数、化疗史及肌酐水平是显著混杂风险因素。结论:本研究表明,升高的血清炎症预后评分及构建的列线图模型可用于预测放射治疗后发生继发性恶性肿瘤的较高风险。