A prediction model for underestimation of invasive breast cancer for patien

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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

Details Formula Study characteristics Files & References

★★★

Model author

pwestenend

Model ID

1074

Version

1.42

Revision date

2020-06-17

Specialty

Oncology, Pathology, Radiology, Surgery

MeSH terms

DCIS

Breast Cancer

Sentinel Node

Breast

Model type

Logistic regression ^{(Calculation)}

Status

public

Rating

★ ★ ★

Formula
No Formula defined yet

Condition	Formula

Additional information

The data are population based data from the Netherlands, incidence in 2011 or 2012.

Of the 2,892 DCIS diagnosis at biopsy, 596 (20.6%) were underestimated as the diagnosis was invasive breast cancer at excision.

Characteristics of the study population: mean age 58.7 years, 66% was screen-detected, 22% was palpable, 75% had BI-RADS score 4 and 12% had BI-RADS score 5, 5% had a suspected invasive component at biopsy and the DCIS grade distribution was 15% low, 39% intermediate and 46% high.

In total, 379 (13%) had missing data for one or more risk factor: 148 for palpability, 223 for BI-RADS score, 84 for DCIS grade and 81 for detection mode. To account for missing data, multiple imputation with fully conditional specification was used in the multivariable logistic analysis. 20 imputed data sets were generated, and the results were pooled according to Rubin’s rules.

Study Population

Total population size: 2892

Categorical characteristics

Name	Subset / Group	Nr. of patients
Detection mode	Screening	1850
	Otherwise	961
DCIS histological grade at biopsy	Low	422
	Intermediate	1083
	High	1303
Palpable	No	2147
	Yes	597
BI-RADS score	3	365
	4	1996
	5	308
Suspect invasive component at biopsy	No	2743
	Yes	149

	A prediction model for underestimation of invasive breast cancer for patients with a biopsy diagnosis of Ductal Carcinoma In Situ (DCIS)
	V-1.42-1074.20.06.17
	Refer to Intended Use for instructions before use
	Evidencio B.V., Irenesingel 19, 7481 GJ, Haaksbergen, the Netherlands

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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

Calculations alone should never dictate patient care, and are no substitute for professional judgement. See our full disclaimer.

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Disclaimer: Calculations alone should never dictate patient care, and are no substitute for professional judgement.

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Study Population

Categorical characteristics

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