A nomogram for predicting underestimation of invasiveness in ductal carcinoma in situ diagnosed by preoperative needle biopsy

Hyung Seok Park, Ha Yan Kim, Seho Park, Eun Kyung Kim, Seung Il Kim, Byeong Woo Park

Research output: Contribution to journalArticle

24 Citations (Scopus)

Abstract

It is unnecessary to perform axillary staging in patients with ductal carcinoma in situ (DCIS) of the breast because of the low incidence of axillary metastasis. However, diagnosis of DCIS by core needle biopsy showed a high rate of underestimation of invasive cancer. Thus, it is necessary to predict invasiveness in DCIS patients on core before surgery. We analyzed 340 patients with DCIS diagnosed by needle biopsy. The cases were divided into training and validation sets. Logistic regression was performed to predict the presence of invasive cancer in the final pathology, and a nomogram was constructed from the training set using the presence of palpability, the presence of ultrasonographic calcification and mass, the biopsy tools, and the presence of microinvasion. The model was subsequently applied to the validation set. The nomogram for the training set was both accurate and discriminating, with an area under the receiver operating characteristic curve (AUC) of 0.75. When applied to the validation group, the model accurately predicted the likelihood of invasive cancer (AUC: 0.71). Our nomogram will allow surgeons to easily and accurately estimate the likelihood of invasive cancer in patients with DCIS as diagnosed by preoperative needle biopsy.

Original languageEnglish
Pages (from-to)869-873
Number of pages5
JournalBreast
Volume22
Issue number5
DOIs
Publication statusPublished - 2013 Oct

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Nomograms
Carcinoma, Intraductal, Noninfiltrating
Needle Biopsy
Area Under Curve
Neoplasms
Large-Core Needle Biopsy
ROC Curve
Breast
Logistic Models
Pathology
Neoplasm Metastasis
Biopsy
Incidence

All Science Journal Classification (ASJC) codes

  • Surgery

Cite this

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title = "A nomogram for predicting underestimation of invasiveness in ductal carcinoma in situ diagnosed by preoperative needle biopsy",
abstract = "It is unnecessary to perform axillary staging in patients with ductal carcinoma in situ (DCIS) of the breast because of the low incidence of axillary metastasis. However, diagnosis of DCIS by core needle biopsy showed a high rate of underestimation of invasive cancer. Thus, it is necessary to predict invasiveness in DCIS patients on core before surgery. We analyzed 340 patients with DCIS diagnosed by needle biopsy. The cases were divided into training and validation sets. Logistic regression was performed to predict the presence of invasive cancer in the final pathology, and a nomogram was constructed from the training set using the presence of palpability, the presence of ultrasonographic calcification and mass, the biopsy tools, and the presence of microinvasion. The model was subsequently applied to the validation set. The nomogram for the training set was both accurate and discriminating, with an area under the receiver operating characteristic curve (AUC) of 0.75. When applied to the validation group, the model accurately predicted the likelihood of invasive cancer (AUC: 0.71). Our nomogram will allow surgeons to easily and accurately estimate the likelihood of invasive cancer in patients with DCIS as diagnosed by preoperative needle biopsy.",
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A nomogram for predicting underestimation of invasiveness in ductal carcinoma in situ diagnosed by preoperative needle biopsy. / Park, Hyung Seok; Kim, Ha Yan; Park, Seho; Kim, Eun Kyung; Kim, Seung Il; Park, Byeong Woo.

In: Breast, Vol. 22, No. 5, 10.2013, p. 869-873.

Research output: Contribution to journalArticle

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AU - Park, Byeong Woo

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AB - It is unnecessary to perform axillary staging in patients with ductal carcinoma in situ (DCIS) of the breast because of the low incidence of axillary metastasis. However, diagnosis of DCIS by core needle biopsy showed a high rate of underestimation of invasive cancer. Thus, it is necessary to predict invasiveness in DCIS patients on core before surgery. We analyzed 340 patients with DCIS diagnosed by needle biopsy. The cases were divided into training and validation sets. Logistic regression was performed to predict the presence of invasive cancer in the final pathology, and a nomogram was constructed from the training set using the presence of palpability, the presence of ultrasonographic calcification and mass, the biopsy tools, and the presence of microinvasion. The model was subsequently applied to the validation set. The nomogram for the training set was both accurate and discriminating, with an area under the receiver operating characteristic curve (AUC) of 0.75. When applied to the validation group, the model accurately predicted the likelihood of invasive cancer (AUC: 0.71). Our nomogram will allow surgeons to easily and accurately estimate the likelihood of invasive cancer in patients with DCIS as diagnosed by preoperative needle biopsy.

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