ESTRO 2022 - Abstract Book

S1011

Abstract book

ESTRO 2022

A total of 1823 patients with no missing clinical values was selected for the analysis and randomly split into training and validation set (1367 and 456 patients, respectively, representing 75% and 25% of the whole included population). The performance of the Cox’s proportional hazard (CPH) model in the test set was 0.71, while the c-index of Random Survival Forest (SRF) was 0.65 and the one of Survival Support Vector Machine (SSVM) reached 0.67. Considering the validation set, the performance of the CPH was comparable to those of SRF and SSVM, achieving c-indexes of 0.65, 0.65, and 0.67 in the validation test, respectively. Overall, the performance of the Cox’s proportional hazard (CPH) model was comparable to those of Random Survival Forest (SRF) and Survival Support Vector Machine (SSVM), achieving c-indexes of 0.65, 0.65, and 0.67 in the validation test, respectively. The most significant contributions to the CPH model are shown in Figure 1A . The SRF confirmed the statistically significant contribution of elevated Ki-67 (>20%), the primary tumor staging at surgery (pT), and the execution of any systemic treatment. The combination of risk factors and molecular subtypes also provided a significant contribution to the model, together with young age (<35 years). A graphical representation of variable importance is SRF is reported in Figure 1B .

Conclusion The prediction accuracy between CPH and ML algorithms in terms of C-index was comparable in both the test and validation sets. Overall, results of CPH were largely confirmed by those of SRF, with clinically-meaningful estimates of variables contribution for the prediction of LRR. The quantitative assessment of the importance of individual parameters in SSVM is more challenging. In perspective, external validation would be beneficial to confirm our results.

PO-1191 WBI and IORT for breast cancer: long-term results of a large mono-institution matched-pair analysis

F. De Rose 1 , L. Di Brina 1 , S. Mussari 1 , D. Ravanelli 2 , E. Magri 1 , T. Proto 1 , L. Bandera 1 , P. Ferrazza 1 , S. Fersino 1 , M. Andolina 1 , F. Ziglio 2 , A. Delana 2 , A. Martignano 2 , L. Menegotti 2 , S. Bou Selman 3 , V. Vanoni 1 1 Santa Chiara Hospital, Radiation Oncology, Trento, Italy; 2 Santa Chiara Hospital, Physics, Trento, Italy; 3 Bolzano Hospital, Radiation Oncology, Bolzano, Italy

Purpose or Objective