Application of a novel prognostic invasive lesion index in ductal carcinoma in situ with minimal invasion of the breast

Abstract

Multiple invasive foci has been shown to increase the risk of lymph node metastasis (LNM) in early breast cancer, but its prognostic implication remains unknown. We aimed to identify the prognostic value of the number of invasive foci in ductal carcinoma in situ with minimal invasion of the breast (DCIS-MI), and further establish a prognostic invasive lesion index (ILI). A total of 193 patients with DCIS-MI (the invasive component was up to 10 mm in diameter) were included. Univariate and multivariate analysis (logistic regression) were used to evaluate the predictive value of the number of invasive foci in LNM. The Kaplan–Meier curve was used for survival analysis. More than five invasive foci was an independent predictor for LNM (OR, 2.67, 95% CI, 1.12–6.33, P = 0.026), and associated with significantly shorter disease-free survival (DFS) and overall survival (OS) compared with no more than five invasive foci (mean DFS 123.8 vs. 148.0 months, P = 0.002; and mean OS 133.5 vs. 151.4 months, P = 0.025). The ILI was established by the sum scores of the number of invasive foci and the invasive component size, having an optimal cut-off point of 5.5 scores. The high-ILI group (ILI >5 scores) had a higher incidence of LNM (23.6% vs. 6.9%) and worse prognosis than the low-ILI group (ILI ≤5 scores). In conclusion, more than five invasive foci was an independent predictor for LNM and an unfavorable prognostic parameter. The ILI could potentially be used to predict survival prognosis in patients with DCIS-MI.

Multiple invasive foci has been shown to increase the risk of lymph node metastasis (LNM) in early breast cancer, but its prognostic implication remains unknown. In this study, we found that more than five invasive foci is an independent predictor for LNM and an unfavorable prognostic parameter. Furthermore, the invasive lesion index, established by the number of invasive foci and the invasive component size, could potentially be used to predict survival prognosis in patients with DCIS-MI.

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