Validation of a normal tissue complication probability model for late unfavourable aesthetic outcome after breast-conserving therapy

Abstract

Purpose: To validate a normal tissue complication probability (NTCP) model for late unfavourable aesthetic outcome (AO) after breast-conserving therapy. Materials/Methods: The BCCT.core software evaluated the AO using standardized photographs of patients treated at the University Hospitals Leuven between April 2015 and April 2016. Dose maps in 2 Gy equivalents were calculated assuming a/b ¼ 3.6 Gy. The discriminating ability of the model was described by the AUC of the receiver operating characteristic curve. A 95% confidence interval (CI) of AUC was calculated using 10,000 bootstrap replications. Calibration was evaluated with the calibration plot and Nagelkerke R 2. Patients with unfavourable AO at baseline were excluded. Patient, tumour and treatment characteristics were compared between the development and the validation cohort. The prognostic value of the characteristics in the validation cohort was further evaluated in univariable and multivariable analysis. Results: Out of 175 included patients, 166 were evaluated two years after RT and 44 (26.51%) had unfavourable AO. AUC was 0.66 (95% CI 0.56; 0.76). Calibration was moderate with small overestimations at higher risk. When applying all of the univariable significant clinicopathological and dosimetrical variables from the validation cohort in a multivariable model, the presence of a seroma and V45 were selected as significant risk factors for unfavourable AO (Odds Ratio 4.40 (95% CI 1.96; 9.86) and 1.14 (95% CI 1.03; 1.27), p-value <.001 and .01, respectively). Conclusions: The NTCP model for unfavourable AO shows a moderate discrimination and calibration in the present prospective validation cohort with a small overestimation in the high risk patients.

Patterns of Post-Mastectomy Radiotherapy in Immediate Breast Reconstruction – Results from the iBRA-2 Cohort Study

“…In terms of complications from IBR, predictive risk models have been externally validated with receipt of PMRT (or not) as a predictor [38,39]. Other risk prediction models for individual radiotherapy side-effects in the breast have been validated [40,41], though none in the setting of IBR. In the future, personalised medicine approaches including the patient germline and tumour genomic pro le may aid decision-making around IBR and PMRT.…”