Abstract
BackgroundWe aimed to develop a multivariable model for prediction of underestimated invasiveness in women with ductal carcinoma in situ at stereotactic large core needle biopsy, that can be used to select patients for sentinel node biopsy at primary surgery.MethodsFrom the literature, we selected potential preoperative predictors of underestimated invasive breast cancer. Data of patients with nonpalpable breast lesions who were diagnosed with ductal carcinoma in situ at stereotactic large core needle biopsy, drawn from the prospective COBRA (Core Biopsy after RAdiological localization) and COBRA2000 cohort studies, were used to fit the multivariable model and assess its overall performance, discrimination, and calibration.Results348 women with large core needle biopsy-proven ductal carcinoma in situ were available for analysis. In 100 (28.7%) patients invasive carcinoma was found at subsequent surgery. Nine predictors were included in the model. In the multivariable analysis, the predictors with the strongest association were lesion size (OR 1.12 per cm, 95% CI 0.98-1.28), number of cores retrieved at biopsy (OR per core 0.87, 95% CI 0.75-1.01), presence of lobular cancerization (OR 5.29, 95% CI 1.25-26.77), and microinvasion (OR 3.75, 95% CI 1.42-9.87). The overall performance of the multivariable model was poor with an explained variation of 9% (Nagelkerke’s R 2), mediocre discrimination with area under the receiver operating characteristic curve of 0.66 (95% confidence interval 0.58-0.73), and fairly good calibration.ConclusionThe evaluation of our multivariable prediction model in a large, clinically representative study population proves that routine clinical and pathological variables are not suitable to select patients with large core needle biopsy-proven ductal carcinoma in situ for sentinel node biopsy during primary surgery.
Highlights
Since the implementation of breast cancer screening, the number of women diagnosed with ductal carcinoma in situ (DCIS) has increased [1]
We aim to develop and evaluate a multivariable model build with routine clinicopathological variables to predict DCIS underestimation in women with nonpalpable breast lesions who are diagnosed through stereotactic large core needle biopsy (LCNB)
We excluded 12 more women because final diagnosis could not be ascertained (no subsequent surgery following non-representative open-breast biopsy (n=5), patients refraining from surgery after LCNB diagnosis (n=5), neoadjuvant therapy for contralateral synchronous breast cancer (n=1), ipsilateral synchronous invasive cancer (n=1)), leaving 348 (90%) women available for analysis
Summary
Since the implementation of breast cancer screening, the number of women diagnosed with ductal carcinoma in situ (DCIS) has increased [1]. We aimed to develop a multivariable model for prediction of underestimated invasiveness in women with ductal carcinoma in situ at stereotactic large core needle biopsy, that can be used to select patients for sentinel node biopsy at primary surgery. Data of patients with nonpalpable breast lesions who were diagnosed with ductal carcinoma in situ at stereotactic large core needle biopsy, drawn from the prospective COBRA (Core Biopsy after RAdiological localization) and COBRA2000 cohort studies, were used to fit the multivariable model and assess its overall performance, discrimination, and calibration. Conclusion: The evaluation of our multivariable prediction model in a large, clinically representative study population proves that routine clinical and pathological variables are not suitable to select patients with large core needle biopsyproven ductal carcinoma in situ for sentinel node biopsy during primary surgery
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