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Stereotactic radiotherapy for early stage non-small cell lung cancer: current standards and ongoing research

Eugenia Vlaskou Badra, Michael Baumgartl, Silvia Fabiano, Aurélien Jongen, Matthias Gückenberger

2021Translational Lung Cancer Research35 citationsDOIOpen Access PDF

Abstract

Stereotactic body radiation therapy (SBRT) allows for the non-invasive and precise delivery of ablative radiation dose. The use and availability of SBRT has increased rapidly over the past decades. SBRT has been proven to be a safe, effective and efficient treatment for early stage non-small cell lung cancer (NSCLC) and is presently considered the standard of care in the treatment of medically or functionally inoperable patients. Evidence from prospective randomized trials on the optimal treatment of patients deemed medically operable remains owing, as three trials comparing SBRT to surgery in this cohort were terminated prematurely due to poor accrual. Yet, SBRT in early stage NSCLC is associated with favorable toxicity profiles and excellent rates of local control, prompting discussion in regard of the treatment of medically operable patients, where the standard of care currently remains surgical resection. Although local control in early stage NSCLC after SBRT is high, distant failure remains an issue, prompting research interest to the combination of SBRT and systemic treatment. Evolving advances in SBRT technology further facilitate the safe treatment of patients with medically or anatomically challenging situations. In this review article, we discuss international guidelines and the current standard of care, ongoing clinical challenges and future directions from the clinical and technical point of view.

Topics & Concepts

MedicineStage (stratigraphy)Lung cancerClinical trialRadiosurgeryRadiation therapyStandard of careRandomized controlled trialMedical physicsIntensive care medicineRadiologyOncologySurgeryInternal medicinePaleontologyBiologyLung Cancer Diagnosis and TreatmentAdvanced Radiotherapy TechniquesRadiomics and Machine Learning in Medical Imaging
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