ESTRO 36 Abstract Book

S68 ESTRO 36 _______________________________________________________________________________________________

compared with the recalibrated QP-model. This suggested the need to add different factors to improve discrimination. Using restrictive (BIC) analysis, the final model contained smoking status (current vs former&never) and MLD (AUC=0.78; R 2 =0.23). At less restrictive analysis (AIC), age, total-lung-volume, V5 and V30 of the heart, sequential chemotherapy, and MLD might be useful; in addition, MLD may be replaced by ipsilateral-lung V20 and total-lung V5. At internal validation, this latter model rendered AUC=0.80 and R 2 =0.28, however with much higher correction for optimism, implying potentially decreased generalizability to other cohorts. Conclusion Intending external validation, both the QP and the AQP- models needed recalibration (of slope and intercept, and of intercept only, respectively), which might be explained by employment of modern RT techniques and 90% administration of chemoradiotherapy in our cohort. A conservatively improved pneumonitis model employing modern chemoradiotherapy-techniques includes MLD and current-smoking status (Figure).

OC-0140 Updating QUANTEC and clinically adjusted QUANTEC models for pneumonitis at external validation A. Van Der Schaaf 1 , J. Lodeweges 1 , A. Niezink 1 , J. Langendijk 1 , J. Widder 1 1 UMCG University Medical Center Groningen, Radiation Oncology, Groningen, The Netherlands Purpose or Objective To externally validate and eventually recalibrate and update the original QUANTEC pneumonitis (QP) model (Marks et al, IJROBP 2010) and the QUANTEC model adjusted for clinical risk factors (AQP; Appelt et al, Acta Oncol 2014) in a cohort treated with 3D-CRT, IMRT, or VMAT, combined in 90% with chemotherapy. Material and Methods The external validation cohort was composed of n=220 patients with lung cancer (NSCLC, SCLC) stages (II-)III with complete dosimetric and prospectively scored pneumonitis data (G2 or higher), treated from 2013 to 2016 within the framework of a prospective data registration program (clinicaltrials.gov NCT02421718). Model performance was tested for discrimination (area under the curve, AUC), (pseudo-)explained variance (Nagelkerke’s R 2 ), and calibration (Hosmer-Lemeshow test, HL-test), before and after intercept and slope recalibration. Then, updating was performed by first refitting the coefficients from the AQP-model to our data, then stepwise manually removing unnecessary variables, followed by adding new potential variables. The procedure was then repeated automatically using Akaike and Bayes Information Criteria (AIC, BIC), respectively. Resulting models were in turn internally validated to correct AUC and R 2 for optimism using bootstrapping with backward elimination based on AIC. Results After recalibration of intercept and slope, the QP-model predicting pneumonitis based exclusively on mean lung dose (MLD) performed well (AUC=0.77; R 2 =0.21; HL-test: p=0.38), while without recalibration the model would not fit our data (HL-test: p<0.001). The AQP-model needed recalibration of the intercept only, but discriminated worse and explained less variance (AUC=0.72; R 2 =0.16)

OC-0141 Validation of dose-sensitive heart regions affecting survival in SABR lung cancer patients A. McWilliam 1 , J. Kennedy 2 , C. Faivre-Finn 1 , M. Van Herk 1 1 The University of Manchester, Division of Molecular and Clinical Cancer Science- Faculty of Biology- Medicine and Health, Manchester, United Kingdom 2 The Christie NHS Foundation Trust, Department of Informatics, Manchester, United Kingdom Purpose or Objective Recent advances in radiotherapy allow an increasing proportion of lung cancer patients to be treated with curative intent. However, evidence is emerging that dose to critical organs may be influencing patient survival. The authors recently presented their work identify a dose sensitive sub-region located in the base of the heart where excess dose resulted in worse patient survival (McWilliam IJROBP 96(2S):S48-S49). This work aims to determine whether the same effect was observed in patients treated with Stereotactic Ablative Radiotherapy (SABR), thereby validating our previous results. Material and Methods The previous work used 1101 non-small cell lung cancer patients treated with 55Gy in 20 fractions. Validation was performed in 89 SABR patients treated with 60Gy in 5 fractions. For both groups, CT scans and dose distributions