IBTR! 2.0: 10-year Ipsilateral Breast Tumor Recurrence (with RT) - Evidencio
IBTR! 2.0: 10-year Ipsilateral Breast Tumor Recurrence (with RT)
The Ipsilateral Breast Tumor Recurrence (IBTR) 2.0 is designed for use by physicians to guide medical decision-making regarding the use of radiation therapy in breast cancer patients who have undergone breast conserving surgery and appropriate axillary evaluation. This model calculates an evidence-based estimate of the 10-year ipsilateral breast tumor recurrence risk with and without the addition of whole breast radiation therapy. 

The IBTR 2.0 is not intended for use in the post-mastectomy setting, and it is not meant to address patients with multicentric disease or with in-situ only disease. It is assumed that all pathological specimens have been microscopically assessed with current histopathological standards. It is presumed that patients who are lymph node positive (with the exception of micrometastatic lymph node disease) will receive systemic therapy, either chemotherapy or hormonal therapy. The calculated benefit of hormonal therapy in this model is based on the tamoxifen literature and has been extrapolated to the use of aromatase inhibitors. Recent studies indicate that aromatase inhibitors have a similar, and possibly a slightly superior, impact on local control. 
Autores de la investigación: Mona Sanghani, Pauline T. Truong, Rita Abi Raad, Andrzej Niemierko, Mary Lesperance, Ivo A. Olivotto, David E. Wazer, Alphonse G. Taghian
Versión: 1.6
  • Público
  • Oncología
  • {{ modelType }}
  • Detalles
  • Validar algoritme
  • Guardar entrada
  • Entrada de carga
Mostrar
Unidades

{{ section.title }}

{{ section.description }}

Calcular el resultado

Establezca más parámetros para realizar el cálculo

10-Year risk of ipsilateral breast tumor recurrence with radiation therapy is: %

{{ resultSubheader }}
{{ $t('download_result_availability') }}
{{ chart.title }}
Intervalo de resultados {{ additionalResult.min }} a {{ additionalResult.max }}

Información condicional

The arm of the IBTR! nomogram that calculates local recurrence risk with radiation has undergone rigorous validation testing with collaboration of two large institutional datasets. The calculation of local recurrence risk without radiation has not been validated because of unavailability of a large diverse cohort of patients that did not receive radiation therapy. Therefore the predicted recurrence risk without radiation therapy is based on the consistent relative risk reduction of 0.7 seen across multiple randomized trials with the use of breast irradiation.

{{ file.classification }}
PRO
Nota
Las notas sólo son visibles en la descarga de resultados y no serán guardadas por Evidencio

Este algoritme se proporciona con fines educativos, formativos e informativos. No debe utilizarse para apoyar la toma de decisiones médicas ni para prestar servicios médicos o de diagnóstico. Lea nuestro disclaimer.

Algoritmer subyacentes Parte de
Comentarios
Comentario
Escriba un comentario
Los comentarios son visibles para cualquiera

Comentarios sobre el algoritme

Aún no hay comentarios 1 comentario {{ model.comments.length }} Comentarios
En {{ comment.created_at }} {{ comment.user.username }} un autor ya no registrado escribió:
{{ comment.content }}
logo

Inicia sesión para activar las funciones de impresión de Evidencio

Para poder utilizar las funciones de impresión de Evidencio, debe estar conectado.
Si no tiene una cuenta de la Comunidad Evidencio puede crear su cuenta personal gratuita en:

https://www.evidencio.com/registration

Resultados impresos - Ejemplos {{ new Date().toLocaleString() }}


Beneficios de la Cuenta Comunitaria Evidencio


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.


Descargo de responsabilidad: Los cálculos por sí solos nunca deben dictar la atención al paciente, y no sustituyen al juicio profesional.
Evidencio v3.38 © 2015 - 2025 Evidencio. Todos los derechos reservados