S829
Clinical - Lung
ESTRO 2026
colorectal cancer (27%) and NSCLC (19%).Grade 3+ adverse events were observed in 31/1236 (2.5%) patients who had these recorded. There were 2 grade 4 events (pneumonitis and pleural effusion) and 1 episode of grade 5 pneumonitis.Local control at 5 years was 88% (95% CI 84,91) for primary NSCLC and 83% (95% CI 73,89) for pulmonary oligometastases. Median progression-free survival was 30 months (95% CI 27,34) for primary NSCLC and 10 months for pulmonary oligometastases (95% CI 9,12). Rates of regional nodal-only and distant failure for primary NSCLC at 5 years were 5% (95% CI 3,6) and 19% (95% CI 16,21), respectively. Median overall survival was 40 months (95% CI 36,43) for primary NSCLC and 50 months (95% CI 42,57) for pulmonary oligometastases. Conclusion: Single-fraction SABR is a safe and effective treatment for primary NSCLC and pulmonary oligometastases. References: 1. Videtic GM et al. A randomized phase 2 study comparing 2 stereotactic body radiation therapy schedules for medically inoperable patients with stage I peripheral non-small cell lung cancer: NRG Oncology RTOG 0915 (NCCTG N0927). IJROBP; 93(4):757-64 (2015)2. Singh AK et al. One versus three fractions of stereotactic body radiation therapy for peripheral stage I to II non-small cell lung cancer: a randomized, multi-institution, phase 2 trial. IJROBP; 105(4):752-9 (2019) 3. Siva S et al. Single-fraction vs multifraction stereotactic ablative body radiotherapy for pulmonary oligometastases (SAFRON II). The Trans Tasman Radiation Oncology Group 13.01 Phase 2 Randomized Clinical Trial. JAMA Oncol; 7(10):1476-85 (2021) Keywords: Single-fraction lung SABR, Pooled analysis Predicting tumour regression in advance of RT: training and external testing of the Proliferation Saturation Index mathematical model in NSCLC Sarah Barrett 1,2 , Vincent Bourbonne 1,3 , Conor K McGarry 4,5 , Mohammad U Zahid 6 , Heiko Enderling 6,7 , Gerard M Walls 4,5 , Laure Marignol 1,2 1 Discipline of Radiation Therapy, Trinity College Dublin, Dublin, Ireland. 2 Trinity St. James’s Cancer Institute, Digital Poster 4024 Trinity College Dublin, Dublin, Ireland. 3 Radiation Oncology Department, University Hospital of Brest, Brest, France. 4 Patrick G. Johnston Centre for Cancer Research, Queen’s University Belfast, Belfast, United Kingdom. 5 Northern Ireland Cancer Centre, Belfast Health & Social Care, Belfast, United Kingdom. 6 Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, USA. 7 Institute for Data Science in Oncology, The University of Texas MD Anderson Cancer Center, Houston, USA
Purpose/Objective: The Proliferation Saturation Index (PSI) is a three- parameter mathematical model used to predict tumour volume regression (TVR) in response to radiotherapy (RT). It incorporates a radiation sensitivity parameter ( α ), a tumour growth rate ( λ ), and a patient-specific PSI value. Previous studies have demonstrated its ability to forecast TVR in non-small cell lung cancer (NSCLC) during conventionally fractionated RT using early treatment response data [1–3]. This study evaluates the model’s performance using only pre-treatment tumour growth dynamics, and tests its predictive accuracy as a single-parameter model in an external dataset. Material/Methods: Model training was conducted on dataset 1, n=37 patients treated with 55Gy in 20 fractions of RT alone, in Northern Ireland (Table 1). Pre-treatment volumes of visible GTV were obtained from planning CT Average Intensity Projection (AVIP) reconstructions of a 4DCT and day 1 CBCT scans [4]. From these, α and λ were derived.The external validation cohort (dataset 2) of n=110 patients were treated with 60–66Gy in 30–33 fractions RT, in combination with chemotherapy, in France. Tumour volumes were extracted from 3DCT planning scans and day 1 CBCTs. Model predictions were compared to actual tumour volumes at the final on-treatment CBCT (CBCTFINAL) using the Coefficient of determination (R ² ) and Pearson correlation coefficient (PCC). Results: In the training cohort (dataset 1), derived parameter values of α = 0.03 and λ = 0.025 yielded strong agreement between predicted and measured volumes (R ² = 0.86, PCC = 0.93) (Figure 1A).In Dataset 2, n=47/110 of the patients exhibited pre-treatment tumour growth (volume increase between planning CT and first CBCT) and had no induction chemotherapy (i.e. unperturbed tumour growth)(Table 1). Pre- treatment TVR predictions in this subset appeared reasonable (R ² = 0.72, PCC = 0.85, Figure 1B) but negative PSI values generated indicate an underestimated tumour growth ( λ ) parameter. This suggests the need for parameter re-optimisation in this clinical scenario.
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