1.Impact of Local Control on Cause-Specific Survival After SBRT for Early-Stage NSCLC: Dynamic Prediction With Landmarking

对早期NSCLC关于SBRT后特异性病因生存率局部控制的影响:具有标致性的动态预测

Introduction
介绍

Stereotactic body radiotherapy (SBRT) is an effective treatment for early-stage non-small cell lung cancer (NSCLC), especially in inoperable patients. Although previous studies have indicated that local control improves with higher doses above the biologically effective dose (BED) 100 Gy, the effect of improved local control on survival remains unclear. The purpose of this study was to assess the impact of local recurrence (LR) on cause-specific survival with a dynamic prediction model that incorporates LR as a time-dependent covariate.

立体定向体放射治疗(SBRT)是治疗早期非小细胞肺癌(NSCLC)的一种有效方法，尤其是对无法手术的患者。虽然以前的研究表明，当剂量高于生物有效剂量(BED) 100 Gy时，局部控制会改善，但改进的局部控制对存活率的影响仍不清楚。本研究的目的是评估局部复发(LR)对病因特异性生存的影响，采用动态预测模型，将LR作为一个时间依赖的协变量。

Methods
研究方法

This study included 386 stage IA NSCLC patients treated with SBRT from two centers, one using a high BED of 140 Gy or more and the other using a conventional BED of 105 Gy. We developed landmark dynamic prediction models for the probability of cause-specific survival. This model provides the probability of surviving an additional 2 years at different prediction time points during follow-up, given the history of recurrent status. Baseline covariates included in the model were age, gender and tumor diameter, and the time-dependent covariates were LR and regional or distant recurrence (RDR). The interactions between prediction time points and covariates were also considered in the model. LR was defined as recurrence within the radiation field.

该研究包括386名IA期NSCLC患者，他们接受了来自两个中心的SBRT治疗，一个使用140戈瑞或以上的高床位，另一个使用105戈瑞的常规床位。我们开发了具有里程碑意义的原因特异性生存概率的动态预测模型。该模型提供了在随访期间不同预测时间点存活2年的概率，考虑到复发病史。模型中纳入的基线协变量为年龄、性别和肿瘤直径，时间依赖的协变量为LR和局部或远处复发(RDR)。模型中还考虑了预测时间点与协变量之间的相互作用。LR定义为辐射场内的复发。

Results
结果

With the median follow-up of 4.3 years, 89 patients (23%) died of lung cancer. In a total of 127 patients who developed recurrence, 18 had LR only, 81 had RDR only, and 28 had both. The landmark model showed that age, tumor diameter, LR and RDR were significantly associated with increased odds of shorter cause-specific survival. Among these covariates, LR (adjusted odds ratio [aOR], 16.1; 95% CI, 9.7-26.7; P < .001) and RDR (aOR, 16.0; 95%CI, 11.6-22.0; P < .001)) demonstrated a strong effect on cause-specific death 2 years after the prediction time points.

中位随访时间为4.3年，89例患者(23%)死于肺癌。在127例复发患者中，18例仅LR, 81例仅RDR, 28例两者均有。里程碑模型显示，年龄、肿瘤直径、LR和RDR与较短病因特异性生存率的增加显著相关。在这些协变量中，LR(调整优势比[aOR]， 16.1;95%置信区间,9.7 - -26.7;P < .001)和RDR (aOR, 16.0;95%置信区间,11.6 - -22.0;(P < .001))显示了对预测时间点2年后的死因特异性死亡的强烈影响。

Conclusion
结论

The dynamic prediction using landmark model showed that LR had a strong impact on subsequent cause-specific deaths. This result suggests that improving local control with higher doses is a reasonable strategy.

使用标志性模型进行的动态预测表明，LR对随后的死因特异性死亡有很强的影响。这一结果表明，提高剂量以改善局部控制是一项合理的策略。