Abstract P4-09-01: The DCIS score predicts risk of local recurrence risk after breast-conserving surgery more accurately than ER plus HER2

Abstract

Abstract Introduction: Improved individual prediction of 10 yr local recurrence (LR) risk following breast-conserving surgery (BCS) for ductal carcinoma in situ (DCIS) is needed to identify women at low risk, for whom radiotherapy (RT) may be omitted. We hypothesized that LR prediction that includes the Oncotype DCIS score (DS) would be more accurate, and would identify more women with very low LR risks compared to models that include estrogen receptor (ER) plus HER2 without the DS. Methods: Three predictive models of LR (clinicopathological factors (CPFs) alone; CPFs+ER+HER2; CPFs+DS) were developed and compared in 1,102 cases of DCIS for whom complete covariate and outcome data were available. CPFs included age at diagnosis, lesion size, nuclear grade, comedonecrosis, multifocality, and resection margin width. Categorizations of discrete variables and transformations of continuous variables were examined in Cox models; two-way interactions and interactions with time were assessed. Internal validation was performed by bootstrapping. Individual predicted 10-yr LR risks after treatment with BCS alone were computed from covariate values, estimated regression parameters and the estimated baseline survival function. Model performance was assessed by c-statistics and calibration plots. Results: 863/1,102 (78.3%) women were age >= 50 years at diagnosis. Lesion size was <= 10 mm in 555/1,102 (50.4%). Nuclear grade was low or moderate in 62.4%. Comedonecrosis was present in 22.1%. Multifocality was observed in 25.2%. Post-BCS RT was received by 54.4%. Mean DS = 37.49 (sd 23.29). DS risk category = low in 611/1,102 (55.4%). ER = positive in 1,025 /1,102 (93.0%) cases. HER2 overexpression = positive in 212/1,102 (19.2%), equivocal in 95 / 1,102 (8.6%) and negative in 795 / 1,102 (72.1%) cases. Adjusting for all CPFs, the hazard ratios (HR) for LR per 50-unit increase in DS = 2.00 (95% CI 1.42, 2.83), for ER positive = 0.58 (95% CI 0.36, 0.95) and for HER2 positive = 0.73 (95% CI 0.41, 1.30). The strongest prediction model incorporated CPFs+DS. C-statistics for CPFs+DS, CPFs+ER+HER2, or CPFs alone models were 0.7025, 0.6879, and 0.6825. The CPFs+DS model was better calibrated at predicting low (<=10%) individual 10-yr LR risks after BCS alone than models incorporating CPF+ER+HER2 or CPFs alone, evidenced by c-statistics and plots of observed by predicted risks. Specifically, among women age >= 50 with no adverse CPFs, the CPFs+DS model identified the greatest proportion of women (62.3%) with predicted 10-year LR risk <= 10% without RT, compared to the CPFs+ER+HER2 (50.9%) or CPFs alone (46.5%) models. When applying the prediction equations to similar women as those in the cohort who were treated with RT, the CPFs+DS model again identified the greatest proportion of women (44.4%) with a low predicted 10-yr LR risk without RT (for whom RT could have been omitted) compared to the CPFs+ER+HER2 model (39.4%) and the CPFs alone model (32.3%). Conclusion: Individual prediction of LR risk that incorporates the DCIS score plus clinicopathological factors is more accurate than prediction models based on ER plus HER2, and identifies a higher proportion of women with a low predicted risk of LR after BCS alone, for whom radiotherapy may be omitted. Citation Format: Rakovitch E, Sutradhar R, Zhou L, Nofech-Mozes S, Hanna W, Paszat L. The DCIS score predicts risk of local recurrence risk after breast-conserving surgery more accurately than ER plus HER2 [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr P4-09-01.