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预测接受根治性常规放疗的非小细胞肺癌患者新发心房颤动。

Prediction of new-onset atrial fibrillation in patients with non-small cell lung cancer treated with curative-intent conventional radiotherapy.

机构信息

Department of Radiation Oncology (Maastro Clinic), School for Oncology and Reproduction (GROW), Maastricht University Medical Center, Maastricht, the Netherlands.

Department of Radiation Oncology (Maastro Clinic), School for Oncology and Reproduction (GROW), Maastricht University Medical Center, Maastricht, the Netherlands; Artificial Intelligence in Medicine (AIM) Program, Mass General Brigham, Harvard Medical School, Boston, MA, USA; Department of Radiology and Nuclear Medicine, Maastricht University Medical Center, Maastricht, the Netherlands.

出版信息

Radiother Oncol. 2024 Dec;201:110544. doi: 10.1016/j.radonc.2024.110544. Epub 2024 Sep 26.

Abstract

BACKGROUND

Atrial fibrillation (AF) is an important side effect of thoracic Radiotherapy (RT), which may impair quality of life and survival. This study aimed to develop a prediction model for new-onset AF in patients with Non-Small Cell Lung Cancer (NSCLC) receiving RT alone or as a part of their multi-modal treatment.

PATIENTS AND METHODS

Patients with stage I-IV NSCLC treated with curative-intent conventional photon RT were included. The baseline electrocardiogram (ECG) was compared with follow-up ECGs to identify the occurrence of new-onset AF. A wide range of potential clinical predictors and dose-volume measures on the whole heart and six automatically contoured cardiac substructures, including chambers and conduction nodes, were considered for statistical modeling. Internal validation with optimism-correction was performed. A nomogram was made.

RESULTS

374 patients (mean age 69 ± 10 years, 57 % male) were included. At baseline, 9.1 % of patients had AF, and 42 (11.2 %) patients developed new-onset AF. The following parameters were predictive: older age (OR=1.04, 95 % CI: 1.013-1.068), being overweight or obese (OR=1.791, 95 % CI: 1.139-2.816), alcohol use (OR=4.052, 95 % CI: 2.445-6.715), history of cardiac procedures (OR=2.329, 95 % CI: 1.287-4.215), tumor located in the upper lobe (OR=2.571, 95 % CI: 1.518-4.355), higher forced expiratory volume in 1 s (OR=0.989, 95 % CI: 0.979-0.999), higher creatinine (OR=1.008, 95 % CI: 1.002-1.014), concurrent chemotherapy (OR=3.266, 95 % CI: 1.757 to 6.07) and left atrium D (OR=1.022, 95 % CI: 1.012-1.032). The model showed good discrimination (area under the curve = 0.80, 95 % CI: 0.76-0.84), calibration and positive net benefits.

CONCLUSION

This prediction model employs readily available predictors to identify patients at high risk of new-onset AF who could potentially benefit from active screening and timely management of post-RT AF.

摘要

背景

心房颤动(AF)是胸部放射治疗(RT)的一个重要副作用,可能会影响生活质量和生存率。本研究旨在为接受单纯放疗或作为多模式治疗一部分的非小细胞肺癌(NSCLC)患者新发生 AF 建立预测模型。

患者和方法

纳入接受根治性常规光子 RT 治疗的 I-IV 期 NSCLC 患者。比较基线心电图(ECG)和随访 ECG 以确定新发生 AF 的情况。考虑了广泛的潜在临床预测因素和整个心脏以及六个自动勾画的心脏亚结构(包括腔室和传导结)的剂量-体积测量值,用于统计建模。进行了带有乐观校正的内部验证,并制作了诺莫图。

结果

共纳入 374 例患者(平均年龄 69±10 岁,57%为男性)。基线时,9.1%的患者有 AF,42 例(11.2%)患者新发 AF。以下参数具有预测性:年龄较大(OR=1.04,95%CI:1.013-1.068)、超重或肥胖(OR=1.791,95%CI:1.139-2.816)、饮酒(OR=4.052,95%CI:2.445-6.715)、心脏手术史(OR=2.329,95%CI:1.287-4.215)、肿瘤位于上叶(OR=2.571,95%CI:1.518-4.355)、用力呼气量 1 秒(FEV1)较高(OR=0.989,95%CI:0.979-0.999)、肌酐较高(OR=1.008,95%CI:1.002-1.014)、同期化疗(OR=3.266,95%CI:1.757 至 6.07)和左心房 D(OR=1.022,95%CI:1.012-1.032)。该模型具有良好的区分度(曲线下面积为 0.80,95%CI:0.76-0.84)、校准度和阳性净获益。

结论

该预测模型采用易于获得的预测因素来识别新发生 AF 风险较高的患者,这些患者可能受益于主动筛查和及时管理 RT 后 AF。

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