Prediction model for tumour-positive margins after breast-conserving surger - Evidencio
Prediction model for tumour-positive margins after breast-conserving surgery

Tumour-positive margins after breast-conserving surgery (BCS) for breast cancer increase local recurrence risk and require additional therapy.

In the Netherlands, in cases of incomplete surgical resections, we make a distinction between 'focally positive' (≤4 mm tumour margin involvement) and ‘extensively positive’ (>4 mm tumour margin involvement or multiple focally positive foci) surgical margins.

This prediction model incorporates all tumour-positive margins (both focally positive and extensively positive) and is based on 109.475 included patients undergoing BCS for non-metastatic breast cancer in the Netherlands from 2009-2022, selected from the Netherlands Cancer Registry. As the aim of our study was to assess potential impact of intraoperative margin assessment innovations, patients with a pathological complete response (pCR) were excluded and are not included in the prediction model.

The tool still requires external validation and is not yet suitable for use in clinical decision-making.

Research authors: Nijveldt JJ, Keizers B, Siesling S, Francken AB, Rajan KK, de Haas AH, van der Vegt B, Koppert LB, Kruijff S, van der Zaag PJ, Kelder W
Version: 1.1
  • Public
  • Surgery
  • {{ modelType }}
  • Algorithm
  • Details
  • Validate
  • Save input
  • Load input
  • {{ toolbarErrorMessage }}

Display
Units

{{ section.title }}

{{ section.description }}

Calculate the result

Set more parameters to perform the calculation

Risk of tumour-positive margins after BCS:

{{ resultSubheader }}
{{ $t('download_result_availability') }}
{{ chart.title }}
Result interval {{ additionalResult.min }} to {{ additionalResult.max }}

Conditional information

Your text input(s) have been changed. Please update your result. Update
{{ file.classification }}
PRO
Note
Notes are only visible in the result download and will not be saved by Evidencio

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.

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

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


Disclaimer: Calculations alone should never dictate patient care, and are no substitute for professional judgement.
Evidencio v3.40 © 2015 - 2026 Evidencio. All Rights Reserved