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

IF 4.9 1区医学 Q1 ONCOLOGY

Radiotherapy and Oncology Pub Date : 2024-09-26 DOI:10.1016/j.radonc.2024.110544

Fariba Tohidinezhad , Leonard Nürnberg , Femke Vaassen , Rachel MA ter Bekke , Hugo JWL Aerts , Lizza El Hendriks , Andre Dekker , Dirk De Ruysscher , Alberto Traverso

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引用次数: 0

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_max (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.

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非小细胞肺癌患者接受根治性常规放射治疗后新发心房颤动的预测

背景心房颤动（AF）是胸部放疗（RT）的一个重要副作用，可能会影响生活质量和生存。本研究旨在开发一种预测模型，用于预测单独接受 RT 或作为多模式治疗一部分的非小细胞肺癌（NSCLC）患者新发房颤。将基线心电图（ECG）与随访心电图进行比较，以确定新发房颤的发生情况。在建立统计模型时，考虑了各种潜在的临床预测因素以及整个心脏和六个自动轮廓心脏亚结构（包括心腔和传导节点）的剂量-体积测量。通过乐观校正进行了内部验证。结果共纳入 374 名患者（平均年龄 69 ± 10 岁，57% 为男性）。基线时，9.1% 的患者患有房颤，42 例（11.2%）患者为新发房颤。以下参数具有预测作用：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）、1 秒内用力呼气量较高（OR=0.989，95 % CI：0.979-0.999）、肌酐较高（OR=1.008，95 % CI：1.002-1.014）、同时接受化疗（OR=3.266，95 % CI：1.757-6.07）和左心房 Dmax（OR=1.022，95 % CI：1.012-1.032）。该模型显示出良好的区分度（曲线下面积 = 0.80，95 % CI：0.76-0.84）、校准和正净效益。结论该预测模型采用了现成的预测指标来识别新发房颤的高风险患者，这些患者有可能从积极筛查和及时处理 RT 后房颤中获益。

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

Radiotherapy and Oncology 医学-核医学

CiteScore

10.30

自引率

10.50%

发文量

2445

审稿时长

45 days

期刊介绍： Radiotherapy and Oncology publishes papers describing original research as well as review articles. It covers areas of interest relating to radiation oncology. This includes: clinical radiotherapy, combined modality treatment, translational studies, epidemiological outcomes, imaging, dosimetry, and radiation therapy planning, experimental work in radiobiology, chemobiology, hyperthermia and tumour biology, as well as data science in radiation oncology and physics aspects relevant to oncology.Papers on more general aspects of interest to the radiation oncologist including chemotherapy, surgery and immunology are also published.