Yale formula (update of the Roach formula).
A new formula for prostate cancer lymph node risk
Many investigators have created tools for predicting extraprostatic disease and lymph node (LN) involvement. One widely used tool is a linear formula created by Roach et al. the Roach formula (RF), which defines the risk of pelvic LN as follows: (% pelvic LN risk = prostate-specific antigen [PSA])2/3 + (Gleason – 6))10). There has been significant stage migration in prostate cancer over the past decade since the creation of the RF. To provide clinicians with a practical approach to estimating LN risk that was developed from a population-based sample of patients who reflect the vast majority of patients diagnosed in the modern PSA era, and whose care reflects current patterns of care, we developed and validated a new predictive formula using the SEER database. A fast, accurate, and easy-to-use formula would be helpful in discussing LN risk with patients and in the conceptualization of LN risk for future clinical trials.
Research authors: James B. Yu, Danil V. Makarov, Cary Gross
Version: 1.10
  • Public
  • Oncology
  • {{ modelType }}
  • Details
  • Validate model
  • Save input
  • Load input
Display
Units

{{section.title}}

Calculate the result

Set more parameters to perform the calculation

The calculated probability of lymph node involvement is: %

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

Conditional information

Reported sensitivity is 39% and specificity is 94,9%.
Compared to the Roach Formula (RF) and Nguyen Formula (NF), our Yale Formula (YF) was able to classify the most patients in the high-risk (>15%) group while still maintaining good PPV and specificity. The YF had the best combination of sensitivity with high specificity and did not underestimate LN risk as the NF did. Underestimation of LN risk is potentially more harmful than overestimation of risk if patients are counseled to undergo prostate-only therapy based on an underestimation of risk, whereas they could potentially undergo pelvic LN irradiation with a chance at improving subsequent pelvic and cure rates. The utility of pelvic radiotherapy remains controversial, but it stands to reason that pelvic radiotherapy should be given more often to patients at higher risk for LN metastases than to those who are at lower risk.

{{ 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 v3.31 © 2015 - 2024 Evidencio. All Rights Reserved