DCIS-met model for predicting metastases in patients with biopsy-proven DCIS
This model calculates the predicted risk for lymph node metastasis after a DCIS diagnosis by biopsy.

The model uses pre-operatively known risk factors: age, 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, Sabine Siesling, Pieter J. Westenend
Version: 1.24
  • Public
  • Surgery
  • {{ modelType }}
  • Details
  • Validate model
  • Save input
  • Load input

{{section.title}}

Calculate the result

Set more parameters to perform the calculation

Predicted risk of metastases:

{{ resultSubheader }}
{{ chart.title }}
Result interval {{ additionalResult.min }} to {{ additionalResult.max }}

Conditional information

Overall information regarding the model:
The model was based on 2,892 cases of DCIS and 127 events of lymph node metastases. The predicted risks in our study ranged from 0.4% to 40.4%, the mean was 4.4% and the median was 2.8%. The c-index was 0.745 and it was 0.748 after correction for optimism by bootstrapping. In this study the sensitivity was the rate of metastasis that was correctly predicted as high-risk and 1-specificity was the rate of no-metastasis that was falsely predicted as high-risk. The calibration plot had a slope of 1.029 and an intercept of 0.090. The decision curve analysis showed that the model has a higher benefit than performing the sentinel lymph node biopsy for all patients. Below the prediction cut-off point of 25% the model has a higher benefit than performing the sentinel lymph node biopsy for none patients.

The validation cohort consisted of the 2,269 patients. In total, 53 (2.2%) had metastasis. The calibration plot showed that the observed proportions were lower than the predicted proportions. The AUC in the validation cohort was 0.741 (95% confidence interval 0.662 to 0.820). The maximum value of the Youden’s index was found at a predicted risk of 3.5%, with a sensitivity of 71.4% and a specificity of 70.6%.

Patients with previous ipsilateral DCIS or invasive breast cancer, patients with biopsy-proven micro-invasive cancer and patients who underwent excisional biopsy were excluded from the cohorts on which the model was developed or validated.

How to use the model:
The model can be used to calculate the individual risk of lymph node metastasis for patients with biopsy-proven DCIS.

{{ file.classification }}
PRO
Note
Notes are only visible in the result download and will not be saved by Evidencio

This model 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.

Underlying models Part of
Comments
Comment
Please enter a comment
Comments are visible to anyone

Model feedback

No feedback yet 1 Comment {{ model.comments.length }} Comments
On {{ comment.created_at }} {{ comment.user.username }} a no longer registered author wrote:
{{ comment.content }}
logo

Please sign in to enable Evidencio print features

In order to use the Evidencio print features, you need to be logged in.
If you don't have an Evidencio Community Account you can create your free personal account at:

https://www.evidencio.com/registration

Printed results - Examples {{ new Date().toLocaleString() }}

Evidencio Community Account Benefits

With an Evidencio Community account you can:

  • Create and publish your own prediction models.
  • Share your prediction models with your colleagues, research group, organization or the world.
  • Review and provide feedback on models that have been shared with you.
  • Validate your models and validate models from other users.
  • Find models based on Title, Keyword, Author, Institute, or MeSH classification.
  • Use and save prediction models and their data.
  • Use patient specific protocols and guidelines based on sequential models and decision trees.
  • Stay up-to-date with new models in your field as they are published.
  • Create your own lists of favorite models and topics.

A personal Evidencio account is free, with no strings attached!
Join us and help create clarity, transparency, and efficiency in the creation, validation, and use of medical prediction models.

Disclaimer: Calculations alone should never dictate patient care, and are no substitute for professional judgement.
Terms & Conditions | Privacy Policy | Disclaimer | Contact | Refuse cookies |
Evidencio v3.30 © 2015 - 2024 Evidencio. All Rights Reserved