Molecular Expression Assays Improve the Prediction of Local and Invasive Local Recurrence After Breast-Conserving Surgery for Ductal Carcinoma In Situ.

Abstract

Purpose: Ductal carcinoma in situ (DCIS) is routinely treated with adjuvant radiotherapy (RT) after breast-conserving surgery (BCS). The inability to accurately estimate an individual's risk of local recurrence (LR) and invasive LR using clinicopathologic factors (CPF) contributes to the overtreatment of DCIS. We examined the impact of the 12-gene DCIS Score (DS) and the 21-gene Recurrence Score (RS) on the accuracy of predicting LR and invasive LR.

Methods: A population-based cohort diagnosed with pure DCIS treated with BCS ± RT from 1994 to 2003 was used. All patients had expert pathology review and assessment of the DS and RS. Predictive models (CPF alone, DS + CPF, and RS + CPF) were developed using multivariable Cox regression analyses to predict 10-year LR and invasive LR risks. Models were evaluated on the basis of c-statistic, -2log likelihood estimate (-2LLE), and Akaike information criterion. Calibration was performed using bootstrap resamples, with replacement.

Results: The cohort includes 1,226 women treated with BCS; 712 received RT. 194 women (15.8%) experienced ipsilateral LR as a first event; 112 were invasive. Models including the DS or RS performed better in predicting the 10-year risk of LR compared with models on the basis of CPF alone with excellent calibration. The two molecular-based models also performed better in predicting invasive LR compared with the CPF model but the model incorporating the RS did not perform better in the prediction of invasive LR compared with the DS-based model.

Conclusion: Models incorporating the DS or RS more accurately predicted the 10-year risk of LR and invasive LR after BCS compared with models on the basis of CPF alone. Inclusion of the RS, compared with DS, did not improve the prediction of the 10-year risk of invasive LR.