A prediction model for underestimation of invasive breast cancer for patien - Evidencio
A prediction model for underestimation of invasive breast cancer for patients with a biopsy diagnosis of Ductal Carcinoma In Situ (DCIS)
This model calculates the predicted risk for underestimation of invasive breast cancer after a DCIS diagnosis by biopsy. The model uses pre-operatively known risk factors: the detection mode, the biopsy DCIS grade, palpability of the tumour, the BI-RADS score and the presence of a histologic suspected invasive component.
Research authors: Claudia J.C. Meurs, Joost van Rosmalen, Marian B.E. Menke-Pluijmers, Bert P.M. ter Braak, Linda de Munck, Sabine Siesling, Pieter J. Westenend
Version: 1.42
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  • Oncology
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Predicted risk:

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Overall information regarding the model:
The model was based on 2,892 cases of DCIS and 589 events of underestimated invasive breast cancer. The predicted risks in our study ranged from 9.5% to 80.2%, the mean was 20.6% and the median was 14.7%. The c-index was 0.668 and it was 0.661 after correction for optimism by bootstrapping. In this study the sensitivity was the rate of underestimates that was correctly predicted as high-risk and 1-specificity was the rate of DCIS at excision that was falsely predicted as high-risk. The model has not been validated externally.

How to use the model:
The model can be used to calculate the individual risk of underestimation based on routinely available pre-operatively known risk factors

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This algorithm is provided for educational, training and information purposes. It must not be used to support medical decision making, or to provide medical or diagnostic services. Read our full disclaimer.

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