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迈向盆腔癌的个性化放疗:晚期放射毒性的患者相关风险因素

Towards Personalized Radiotherapy in Pelvic Cancer: Patient-Related Risk Factors for Late Radiation Toxicity.

作者信息

Nuijens Anna C, Oei Arlene L, Franken Nicolaas A P, Rasch Coen R N, Stalpers Lukas J A

机构信息

Department of Radiation Oncology, Amsterdam UMC Location University of Amsterdam, Meibergdreef, 1105 AZ Amsterdam, The Netherlands.

Laboratory for Experimental Oncology and Radiobiology (LEXOR), Center for Experimental and Molecular Medicine (CEMM), Amsterdam UMC Location University of Amsterdam, Meibergdreef, 1105 AZ Amsterdam, The Netherlands.

出版信息

Curr Oncol. 2025 Jan 17;32(1):47. doi: 10.3390/curroncol32010047.

Abstract

Normal tissue reactions vary significantly among patients receiving the same radiation treatment regimen, reflecting the multifactorial etiology of late radiation toxicity. Predicting late radiation toxicity is crucial, as it aids in the initial decision-making process regarding the treatment modalities. For patients undergoing radiotherapy, anticipating late toxicity allows for planning adjustments to optimize individualized care. Various dosimetric parameters have been shown to influence the incidence of late toxicity, and the literature available on this topic is extensive. This narrative review examines patient-related determinants of late toxicity following external beam radiotherapy for pelvic tumors, with a focus on prostate and cervical cancer patients. In Part I, we address various methods for quantifying radiation toxicity, providing context for interpreting toxicity data. Part II examines the current insights into the clinical risk factors for late toxicity. While certain factors-such as previous abdominal surgery, smoking behavior, and severe acute toxicity-have consistently been reported, most of the others show inconsistent associations. In Part III, we explore the influence of genetic factors and discuss promising predictive assays. Single-nucleotide polymorphisms (SNPs) likely elevate the risk in specific combinations. Advances in artificial intelligence now allow for the identification of SNP patterns from large datasets, supporting the development of polygenic risk scores. These innovations hold promise for improving personalized treatment strategies and reducing the burden of late toxicity in cancer survivors.

摘要

接受相同放疗方案的患者,其正常组织反应差异显著,这反映了晚期放射毒性的多因素病因。预测晚期放射毒性至关重要,因为它有助于在治疗方式的初始决策过程中提供帮助。对于接受放疗的患者,提前预估晚期毒性有助于进行治疗方案调整,以优化个体化护理。各种剂量学参数已被证明会影响晚期毒性的发生率,关于这一主题的文献也很丰富。这篇叙述性综述探讨了盆腔肿瘤外照射放疗后晚期毒性的患者相关决定因素,重点关注前列腺癌和宫颈癌患者。在第一部分,我们阐述了量化放射毒性的各种方法,为解读毒性数据提供背景。第二部分研究了目前对晚期毒性临床风险因素的见解。虽然某些因素,如既往腹部手术、吸烟行为和严重急性毒性,一直被报道,但其他大多数因素的关联并不一致。在第三部分,我们探讨遗传因素的影响并讨论有前景的预测检测方法。单核苷酸多态性(SNP)可能在特定组合中增加风险。人工智能的进展现在允许从大型数据集中识别SNP模式,支持多基因风险评分的开发。这些创新有望改善个性化治疗策略并减轻癌症幸存者晚期毒性的负担。

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