Development and external validation of a prediction model for overall survival after resection of distal cholangiocarcinoma
OBJECTIVE
To develop and validate a prediction model for 3-year overall survival after pancreatoduodenectomy for distal cholangiocarcinoma.

DESIGN
International cohort study.

MAIN OUTCOME MEASURE
3-year overall survival
Research authors: Ali Belkouz, Stijn van Roessel, Marin Strijker, Jacob L. van Dam, Lois Daamen, Lydia G. van der Geest, Alberto Balduzzi, Andrea Benedetti Cacciaguerra, Susan van Dieren, Quintus Molenaar, Bas Groot Koerkamp, Joanne Verheij, Elizabeth van Eycken, Giuseppe Malleo, Mohammed Abu Hilal, Martijn G.H. van Oijen, Ivan Borbath, Chris Verslype, Cornelis J.A. Punt, Marc G. Besselink, Heinz-Jozef Klümpen, and Dutch Pancreatic Cancer Group
Version: 1.15
  • Details
  • Validate model
  • Save input
  • Load input

Calculate the result

Set more parameters to perform the calculation

3-Year overall survival probability

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

Conditional information

Background: Various prognostic factors are associated with overall survival (OS) after resection of distal cholangiocarcinoma (dCCA). The objective of this study was to develop and validate a prediction model for 3-year OS after pancreatoduodenectomy for dCCA.

Methods: The derivation cohort consisted of all patients who underwent pancreatoduodenectomy for dCCA in the Netherlands (2009-2016). Clinically relevant variables were selected based on the Akaike information criterion using a multivariate Cox proportional hazards regression model, with model performance being assessed by concordance index (C-index) and calibration plots. External validation was performed using patients from the Belgium Cancer Registry (2008-2016), and patients from two university hospitals of Southampton (U.K.) and Verona (Italy).

Results: Independent prognostic factors for OS in the derivation cohort of 454 patients after pancreatoduodenectomy for dCCA were age (HR 1.02, 95% CI 1.01-1.03), pT (HR 1.43, 95% CI 1.07-1.90) and pN category (pN1: HR 1.78, 95% CI 1.37-2.32; pN2: HR 2.21, 95% CI 1.63-3.01), resection margin status (HR 1.79, 95% CI 1.39-2.29) and tumour differentiation (HR 2.02, 95% CI 1.62-2.53). The prediction model was based on these prognostic factors. The optimism-adjusted C-indices were similar in the derivation cohort (0.69), and in the Belgian (0.66) and Southampton-Verona (0.68) validation cohorts. Calibration was accurate in the Belgian validation cohort (slope = 0.93, intercept = 0.12), but slightly less optimal in the Southampton-Verona validation cohort (slope = 0.88, intercept = 0.32). Based on this model, three risk groups with different prognoses were identified (3-year OS of 65.4%, 33.2% and 11.8%).

Conclusions: The prediction model for 3-year OS after resection of dCCA had reasonable performance in both the derivation and geographically external validation cohort. Calibration slightly differed between validation cohorts. The model is readily available via www. pancreascalculator.com to inform patients from Western European countries on their prognosis, and may be used to stratify patients for clinical trials.

{{ 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.
Evidencio v3.24 © 2015 - 2024 Evidencio. All Rights Reserved