ESTRO 2023 - Abstract Book

S113

Saturday 13 May

ESTRO 2023

449 patients (74%) discontinued treatment within a median of 2 days (range 1-16). 30% of the days that treatment was interrupted were due to holidays, 12% to toxicity, and 58% to other reasons (breakdowns, maintenance, undetermined). The median of interruptions due to toxicity was 3 days (range 1-16). Fifteen patients (3.3%) had a replanning of their treatment. We did not find a different risk for presenting and interruption in patients who received concomitant chemotherapy (p = 0.63) or with a Karnofsky score higher than 80 (p = 0.78). It was found more interruptions in NSCLC than SCLC (X2 = 1.98; p = 0.001; OR = 1.20). Patients who discontinued due to toxicity were excluded from survival analysis to avoid potential biases. When comparing patients who prolong their treatment with patients who do not interrupt, we found no significant differences in OS (p = 0.983), neither in LRFS (p = 0.903). In the subgroup study, during a 4-year follow-up, we found an increased risk of local relapse near to significance in patients with NSCLC who discontinued for more than 5 days (p = 0.052) (Fig. 1). However, we observed a significant increase in the risk of local recurrence in patients with adenocarcinoma histology who discontinued for more than 4 days (HR 3.67; CI95% [1.34; 10.02], p-value = 0.011) (Fig. 2). In SCLC we did not find differences in LRFS (p = 0.20). No differences in the OS or LRFS were found according to histology.

Conclusion Our data show that only 12% of interruptions in lung cancer were related to toxicity. Moreover, differences according to histologies were found. Our results suggest that patients with NSCLC could experiment more interruptions than SCLC which could impact in prognosis, especially in adenocarcinoma with interruptions for more than 4 days where we found a significant reduction in LRFS. We consider that this subgroup could benefit from compensatory measures. No other alterations in OS or LRFS were identified based on interruptions when we analyzed them according to histology. PD-0152 Radiation-induced lymphopenia risk model predicts durvalumab benefit in non-small cell lung cancer. P. van Rossum 1 , P. Damen 2,1 , T. Xu 1 , B. Hobbs 3 , R. Mohan 4 , Z. Liao 1 , S. Lin 1 1 The University of Texas MD Anderson Cancer Center, Radiation Oncology, Houston (TX), USA; 2 UMC Utrecht, Radiation Oncology, Utrecht, The Netherlands; 3 The University of Texas at Austin, Population Health, Dell Medical School, Austin (TX), USA; 4 The University of Texas MD Anderson Cancer Center, Radiation Physics, Houston (TX), USA Purpose or Objective Severe radiation-induced lymphopenia (RIL) in patients undergoing concurrent chemoradiotherapy (CRT) for non-small cell lung cancer (NSCLC) is associated with decreased immunotherapy efficacy and survival. Severe RIL mostly occurs in the final weeks of CRT, when it is too late for meaningful modification of RT plans or techniques for lymphocyte-sparing. Therefore, a prediction model that identifies patients at high risk of severe RIL before treatment (i.e. a-priori) is warranted. The primary aim of this study was to develop and validate a nomogram based on pretreatment predictors for severe RIL. A secondary aim was to assess the survival impact of adjuvant durvalumab for different RIL risk groups. Materials and Methods Patients who underwent concurrent CRT for NSCLC between 2010 and 2019 were identified. Absolute lymphocyte counts (ALCs) were obtained prior to, and weekly during CRT. Severe RIL was defined as a lowest ALC during CRT (ALCnadir) of <0.24 K/ µ L. Multivariable logistic regression analysis was used to build a prediction model for severe RIL and internal validation was performed using bootstrapping. The model was evaluated in terms of discrimination and calibration, and presented as nomogram. For 2 nomogram risk groups, progression-free survival (PFS) and overall survival (OS) after durvalumab vs. no durvalumab were evaluated. Results