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 Dmax (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.

Prediction of new-onset atrial fibrillation in patients with non-small cell lung cancer treated with curative-intent conventional radiotherapy / Tohidinezhad, F., Nurnberg, L., Vaassen, F., Ma Ter Bekke, R., Jwl Aerts, H., El Hendriks, L., Dekker, A., De Ruysscher, D., Traverso, A.. - In: RADIOTHERAPY AND ONCOLOGY. - ISSN 0167-8140. - 201:(2024). [10.1016/j.radonc.2024.110544]

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

Traverso A.
Ultimo
2024-01-01

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 Dmax (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.
2024
Inglese
Elsevier Ireland Ltd
201
7
Pubblicato
https://www.sciencedirect.com/science/article/pii/S0167814024035229?via=ihub
Esperti anonimi
Internazionale
Goal 3: Good health and well-being
Atrial fibrillation
Lung cancer
Machine learning
Prediction model
Radiotherapy
Prediction of new-onset atrial fibrillation in patients with non-small cell lung cancer treated with curative-intent conventional radiotherapy / Tohidinezhad, F., Nurnberg, L., Vaassen, F., Ma Ter Bekke, R., Jwl Aerts, H., El Hendriks, L., Dekker, A., De Ruysscher, D., Traverso, A.. - In: RADIOTHERAPY AND ONCOLOGY. - ISSN 0167-8140. - 201:(2024). [10.1016/j.radonc.2024.110544]
open
9
info:eu-repo/semantics/article
262
Tohidinezhad, F.; Nurnberg, L.; Vaassen, F.; Ma Ter Bekke, R.; Jwl Aerts, H.; El Hendriks, L.; Dekker, A.; De Ruysscher, D.; Traverso, A.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11768/207576
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