Long-term follow-up of a phase I/II trial of radiation dose escalation by simultaneous integrated boost for locally advanced esophageal squamous cell carcinoma.

RADIOTHERAPY AND ONCOLOGY(2021)

引用 3|浏览14
暂无评分
摘要
BACKGROUND:To observe the long-term survival and late adverse events in a phase Ⅰ/Ⅱ trial (NCT01843049) of dose escalation for thoracic esophageal squamous cell carcinoma (ESCC) with simultaneous integrated boost (SIB) technique. METHODS:Patients with ESCC were treated with escalating radiation dose of four predefined levels. Dose of 62.5-64 Gy/25-32 fractions was delivered to the gross tumor volume (GTV), with (Level 3&4) or without (Level 1&2) a SIB up to 70 Gy for pre-treatment 50% SUVmax area of GTV. Patients also received 2 cycles of chemotherapy of cisplatin and fluorouracil concurrently and 2 more cycles after radiotherapy. RESULTS:Median follow-up duration was 17.2 (2.5-83.4) months for all 44 patients and 47.2 (3.9-83.4) months for 25 survivors. The 3-year overall survival and progression-free survival rates were 57.6% and 41.0%, respectively. One, one, four and twelve severe (grade≥3) esophageal late adverse events (SEAE) occurred in patients of Level 1/2/3/4 (n = 5/10/16/13), with median occurrence time of 6.5 months. In univariable and multivariable competing risk models, maximal dose of the esophagus (Dmax) was found to have significant impact on the incidence of SEAE, and the cutoff distinguishing patients who developed SEAE or not was 77 Gy. CONCLUSION:Boosting the gross tumor to 63 Gy while delivering 50.4 Gy to subclinical diseases in 28 fractions in locally advanced ESCC is well tolerated with promising long-term survival. Intenser dose regimen should be considered with caution before further toxicity assessment. Esophageal Dmax was significantly associated with severe late esophageal injury, while more findings of dose-volume predictors need larger-sample investigation.
更多
查看译文
关键词
Esophageal squamous cell carcinoma, Radiotherapy, Dose escalation, Simultaneous integrated boost, Late toxicity
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要