Conditional survival in patients with resectable esophageal cancer - Evidencio
Conditional survival in patients with resectable esophageal cancer
Most provided survival rates in current literature are static, calculated from the day of surgery. But as time proceeds after surgery, the risk of death in esophageal cancer patients changes. Conditional survival accounts for the time already survived after surgery and may be informative in addition to conventional estimates during follow-up. This nomogram shows an accurate prediction of survival in patients after esophageal cancer surgery, taking the years already survived after surgery into account. This nomogram can be helpful in counselling patients in the follow-up after surgery.
Research authors: E.R.C. Hagens, MD, M.L. Feenstra, MD, W.J. Eshuis, MD, PhD , M.C.C.M. Hulshof, MD, PhD, H.W.M. van Laarhoven, MD, PhD, M.I. van Berge Henegouwen, MD, PhD, S.S. Gisbertz, MD, PhD
Version: 1.28
  • Public
  • Oncology
  • {{ modelType }}
  • Details
  • Validate algorithm
  • Save input
  • Load input
Display
Units

{{section.title}}

Calculate the result

Set more parameters to perform the calculation

Probability of survival 5-years after neoadjuvant chemoradiation and esophageal resection is %, given the number of years already survived

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

Conditional information

This model calculates 5-year survival after neoadjuvant chemoradiation (CROSS regimen1) and esophagectomy in patients with esophageal cancer. 

Model performance:
Predictive factors for death in patients with esophageal carcinoma included in the nomogram were: cN+ (HR 1.31, 95%CI 1.01 – 1.69), ypT-stage (HR for ypT1 1.19, 95%CI 0.79 – 1.80, p=0.441; and ypT2-3 in relation to ypT0 1.50, 95%CI 1.07 – 2.11, p=0.020), ypN-stage (HR 2.51, 95%CI 1.89 – 3.31; HR 3.14, 95%CI 2.25 – 4.36 and HR 6.34, 95%CI 4.16 – 9.58, respectively for ypN1, ypN2, ypN3 with ypN0 as reference), cardiovascular comorbidity (HR 1.37, 95%CI 1.08 – 1.71), chyle leak (HR 1.51, 95%CI 1.07 – 2.11) and pulmonary complications (HR 1.53, 95%CI 1.20 – 1.94). The C-statistic was 0.70 (0.69 to 0.70).

Source:
A reference to the published paper will be placed here.
(Accepted in British Journal of Surgery, DOI: 10.1002/bjs.11476)

References:
1. van Hagen P, Hulshof MCCM, van Lanschot JJB, et al. Preoperative Chemoradiotherapy for Esophageal or Junctional Cancer. N Engl J Med. 2012;366(22):2074-2084. doi:10.1056/NEJMoa1112088.
2. Rice TW, Patil DT, Blackstone EH. 8th edition AJCC/UICC staging of cancers of the esophagus and esophagogastric junction: application to clinical practice. Ann Cardiothorac Surg. 2017 Mar; 6(2): 119–130.

{{ 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.
Terms & Conditions | Privacy Policy | Disclaimer | Contact | Refuse cookies |
Evidencio v3.36 © 2015 - 2025 Evidencio. All Rights Reserved