Stereotactic body radiation therapy for early-stage non-small cell lung cancer: a single-institutional retrospective analysis of outcomes and prognostic factors.

IF 3.5 3区 医学 Q2 ONCOLOGY
Frontiers in Oncology Pub Date : 2025-09-16 eCollection Date: 2025-01-01 DOI:10.3389/fonc.2025.1591420
Chengrui Fu, Jigang Dong, Chunhui Li, Zhongtang Wang, Wei Huang, Chengxin Liu, Dan Han, Bin Zhang, Baosheng Li
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Abstract

Background: Stereotactic body radiotherapy (SBRT) is a definitive treatment for medically inoperable early-stage non-small cell lung cancer (NSCLC), yet optimal dose selection and prognostic factors in elderly, high-risk populations remain debated. This study evaluates long-term outcomes and predictors of survival in a real-world cohort.

Methods: We retrospectively analyzed 258 patients with T1-2N0M0 NSCLC treated with SBRT at Shandong Cancer Hospital (2017-2022). Inclusion criteria: tumors ≤5 cm, medically inoperable or surgery-refused. Survival outcomes (LC, PFS, CSS, OS) were estimated using Kaplan-Meier curves with log-rank tests. Competing risk regression (Fine-Gray model) was used for cancer-specific survival (CSS), with non-cancer deaths as competing events. Prognostic factors of OS via univariable and multivariable Cox regression. Dose fractionation was individualized (median BED10=100 Gy, range: 75-144 Gy), with strict adherence to RTOG 0236 constraints, using 4D-CT for motion management and daily CBCT for image guidance.

Results: The cohort comprised predominantly elderly patients (median age: 73 years; 41.5% ≥75 years, 21.3% ≥80 years). At a median follow-up of 38.8 months, 5-year OS, progression-free survival (PFS), local control (LC), and CSS rates were 74.2%, 71.9%, 83.8%, and 84.5% respectively. Competing risks analysis revealed cumulative 5-year cancer-specific mortality of 14.1% (7.6%-20.5%) versus non-cancer mortality of 11.6% (6.8%-16.4%). Multivariable analysis identified lower lobe lung cancer (HR = 2.218, p = 0.014), central tumor location (HR = 2.664, p = 0.003), the larger tumor length (HR = 1.415, p = 0.039), smoking history (HR = 2.328, p = 0.008) and medical inoperable (HR = 2.572, p = 0.007) as independent predictors of poor OS. Despite 21.3% central tumors, toxicity was minimal (grade 3 pneumonitis: 1.6%).

Conclusion: SBRT achieves durable survival in early-stage NSCLC at our center. Central/lower lobe tumors, bigger tumors, smoking history, and medical inoperable independently predict inferior survival, emphasizing the need for personalized dose escalation strategies or combined treatment modalities.

立体定向放射治疗早期非小细胞肺癌:结果和预后因素的单机构回顾性分析
背景:立体定向放射治疗(SBRT)是医学上不能手术的早期非小细胞肺癌(NSCLC)的一种确定治疗方法,但在老年人和高危人群中,最佳剂量选择和预后因素仍存在争议。这项研究评估了现实世界队列的长期结果和生存预测因素。方法:回顾性分析2017-2022年山东省肿瘤医院接受SBRT治疗的258例T1-2N0M0型非小细胞肺癌患者。纳入标准:肿瘤≤5cm,医学上不能手术或拒绝手术。生存结局(LC、PFS、CSS、OS)采用Kaplan-Meier曲线和log-rank检验进行估计。竞争风险回归(Fine-Gray模型)用于癌症特异性生存(CSS),非癌症死亡作为竞争事件。单变量和多变量Cox回归分析OS预后因素。剂量分级是个体化的(中位BED10=100 Gy,范围:75-144 Gy),严格遵守RTOG 0236的限制,使用4D-CT进行运动管理,每日CBCT进行图像引导。结果:该队列主要由老年患者组成(中位年龄:73岁;41.5%≥75岁,21.3%≥80岁)。在中位随访38.8个月时,5年OS、无进展生存期(PFS)、局部控制(LC)和CSS率分别为74.2%、71.9%、83.8%和84.5%。竞争风险分析显示,累积5年癌症特异性死亡率为14.1%(7.6%-20.5%),非癌症死亡率为11.6%(6.8%-16.4%)。多变量分析发现,下叶肺癌(HR = 2.218, p = 0.014)、肿瘤中心位置(HR = 2.664, p = 0.003)、肿瘤长度较大(HR = 1.415, p = 0.039)、吸烟史(HR = 2.328, p = 0.008)和内科不手术(HR = 2.572, p = 0.007)是不良OS的独立预测因素。尽管有21.3%的中心肿瘤,毒性很小(3级肺炎:1.6%)。结论:SBRT在我们中心的早期非小细胞肺癌患者中获得了持久的生存。中央/下叶肿瘤、较大肿瘤、吸烟史和医学上不能手术独立预测较差的生存期,强调需要个性化剂量递增策略或联合治疗方式。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Frontiers in Oncology
Frontiers in Oncology Biochemistry, Genetics and Molecular Biology-Cancer Research
CiteScore
6.20
自引率
10.60%
发文量
6641
审稿时长
14 weeks
期刊介绍: Cancer Imaging and Diagnosis is dedicated to the publication of results from clinical and research studies applied to cancer diagnosis and treatment. The section aims to publish studies from the entire field of cancer imaging: results from routine use of clinical imaging in both radiology and nuclear medicine, results from clinical trials, experimental molecular imaging in humans and small animals, research on new contrast agents in CT, MRI, ultrasound, publication of new technical applications and processing algorithms to improve the standardization of quantitative imaging and image guided interventions for the diagnosis and treatment of cancer.
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