Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

A Model to Predict Upstaging to Invasive Carcinoma in Patients Preoperatively Diagnosed with Low-grade Ductal Carcinoma In Situ of the Breast

Luca Nicosia
* ,
Anna Carla Bozzini
,
Silvia Penco
,
Chiara Trentin
,
Maria Pizzamiglio
,
Matteo Lazzeroni
ORCID logo ,
Germana Lissidini
,
Paolo Veronesi
,
Gabriel Farante
,
Samuele Frassoni
,
Vincenzo Bagnardi
,
Cristiana Fodor
,
Nicola Fusco
,
Elham Sajjadi
ORCID logo ,
Enrico Cassano
ORCID logo ,
Filippo Pesapane
Version 1 : Received: 13 November 2021 / Approved: 17 November 2021 / Online: 17 November 2021 (11:03:55 CET)

How to cite: Nicosia, L.; Bozzini, A.C.; Penco, S.; Trentin, C.; Pizzamiglio, M.; Lazzeroni, M.; Lissidini, G.; Veronesi, P.; Farante, G.; Frassoni, S.; Bagnardi, V.; Fodor, C.; Fusco, N.; Sajjadi, E.; Cassano, E.; Pesapane, F. A Model to Predict Upstaging to Invasive Carcinoma in Patients Preoperatively Diagnosed with Low-grade Ductal Carcinoma In Situ of the Breast. Preprints 2021, 2021110301. https://doi.org/10.20944/preprints202111.0301.v1 Nicosia, L.; Bozzini, A.C.; Penco, S.; Trentin, C.; Pizzamiglio, M.; Lazzeroni, M.; Lissidini, G.; Veronesi, P.; Farante, G.; Frassoni, S.; Bagnardi, V.; Fodor, C.; Fusco, N.; Sajjadi, E.; Cassano, E.; Pesapane, F. A Model to Predict Upstaging to Invasive Carcinoma in Patients Preoperatively Diagnosed with Low-grade Ductal Carcinoma In Situ of the Breast. Preprints 2021, 2021110301. https://doi.org/10.20944/preprints202111.0301.v1

Abstract

Background: We aimed to create a model of radiological and pathological criteria able to predict the upgrade rate of low-grade ductal carcinoma in situ (DCIS) to invasive carcinoma, in patients undergoing vacuum-assisted breast biopsy (VABB) and subsequent surgical excision. Methods: 3100 VABBs were retrospectively reviewed among which we reported 295 low-grade DCIS who subsequently underwent surgery. The association between patients’ features and the upgrade rate to invasive breast cancer (IBC) was evaluated by univariate analysis. Finally, we developed a predictive multivariable model based on the features which were significantly associated with the univariate analysis outcome. Results: the upgrade rate to invasive carcinoma was 10.8 %. At univariate analysis, the risk of upgrade was significantly lower in the absence of post- biopsy residual lesion (p<0.001), age > 50 (p=0.029), and in presence of low-grade DCIS only in specimens with microcalcifications (p=0.002). According to the final multivariable model, the predicted probability of diagnostic underestimation for a patient with all the three favourable features selected at univariate analysis was 1% (95% CI: 0.3%-4%). Conclusions: An easy to use predictive model of radiological and pathological criteria is able to identify patients with low-grade carcinoma in situ with low risk of upstaging to infiltrating carcinomas.

Keywords

ductal carcinoma in situ (DCIS); invasive breast carcinoma; breast; biopsy; overtreatment; active surveillance.

Subject

Medicine and Pharmacology, Pathology and Pathobiology

Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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