Impact of Local Recurrence on Cause-Specific Death After Stereotactic Body Radiotherapy for Early-Stage Non-Small Cell Lung Cancer: Dynamic Prediction Using Landmark Model

International Journal of Radiation Oncology*Biology*Physics(2022)

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摘要
Purpose: The purpose of this study was to assess the impact of local recurrence (LR) on cause-specific death (CSD) in patients with non-small cell lung cancer (NSCLC) treated with stereotactic body radiotherapy (SBRT). A dynamic prediction model that incorporated LR as a time-dependent covariate was used. Methods and materials: This study included 535 stage I (cT1-T2aN0M0) NSCLC patients treated with SBRT from two institutions. We developed a landmark dynamic prediction model to estimate the probability of a CSD. This model determined the probability of surviving for an additional 3 years at different prediction time points during follow-up, given the history of recurrence status. The baseline covariates included in the model were age, sex, T stage, and histology, while the time-dependent covariates were LR and regional and/or distant recurrence (RDR) status. Results: Overall, 137 patients (25.6%) died of lung cancer within a median follow-up of 4.1 years. Of the 195 patients who developed recurrence, 28, 125, and 42 patients had LR only, RDR only, and both, respectively. The landmark model showed that older age, advanced T stage, LR, and RDR were significantly associated with an increased risk of subsequent CSD. Among these covariates, LR (odds ratio [OR], 8.5; 95% confidence interval [CI], 6.0-12.0; P < .001) and RDR (OR, 11.6; 95% CI, 9.1 -14.9; P < .001) demonstrated strong effects on CSD within 3 years after the prediction time points. The dynamic prediction provided information on the probability of future CSD according to individual recurrence status during follow-up. Conclusions: Dynamic prediction using the landmark model showed that LR had a substantial impact on subsequent CSD, which was comparable to that of RDR. This result supports the notion that strategies to improve local control are reasonable. (C) 2021 Elsevier Inc. All rights reserved.
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