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Predicción de los resultados informados por el paciente tras el tratamiento del cáncer de próstata localizado:

Adam B Weiner1, Shannon C Martin2, Holly Wilhalme2

  • 1Department of Urology, David Geffen School of Medicine, University of California, Los Angeles, CA; Department of Urology, Cedars-Sinai Medical Center, Los Angeles, CA; Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, CA.

Clinical genitourinary cancer
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Resumen

La predicción de los resultados del paciente después del tratamiento del cáncer de próstata utilizando factores de referencia mostró una precisión modesta en un estudio global. Los datos internacionales a gran escala resaltan la heterogeneidad, lo que sugiere la necesidad de modelos predictivos específicos para cada región.

Palabras clave:
Toma de decisiones clínicasNeoplasias de próstata/diagnóstico por imagenNeoplasias de próstata/epidemiologíaNeoplasias de próstata/terapiaVigilancia activa

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Área de la Ciencia:

  • Oncología; Investigación de Servicios de Salud; Bioestadística

Sus antecedentes:

  • La toma de decisiones compartida para el cáncer de próstata localizado (CP) requiere la comprensión de los factores que predicen los resultados informados por el paciente (PRO).
  • Los modelos predictivos previos para los resultados del tratamiento del CP se limitaron a cohortes de pacientes pequeñas y de una sola región.
  • El Movember True North Global Registry (TNGR) ofrece un conjunto de datos grande y multinacional para desarrollar modelos predictivos robustos.

Objetivo del estudio:

  • Desarrollar y evaluar modelos predictivos para los resultados informados por el paciente (PRO) a los 12 meses en pacientes con Cáncer de Próstata localizado.
  • Utilizar el extenso conjunto de datos multinacional TNGR para el desarrollo de modelos mejorados.
  • Identificar los factores basales que predicen los resultados funcionales después del tratamiento del Cáncer de Próstata.

Principales métodos:

  • Se analizó una cohorte de 27.499 hombres con Cáncer de Próstata localizado de 15 países (2016-2022).
  • Los pacientes se asignaron aleatoriamente a cohortes de entrenamiento (n=18.332) y validación (n=9.167).
  • Las regresiones lineales multivariables integraron los PRO basales, datos demográficos, país, modalidad de tratamiento y características del tumor para predecir los cambios en 5 dominios de EPIC-26.

Principales resultados:

  • La función basal, el tipo de tratamiento y las características del tumor influyeron significativamente en los cambios funcionales a los 12 meses.
  • Los modelos explicaron el 15% (incontinencia urinaria), el 14% (irritación urinaria), el 19% (intestinal), el 32% (sexual) y el 28% (hormonal) de la varianza en la cohorte de validación.
  • El rendimiento varió entre los diferentes dominios funcionales, lo que indica una predictibilidad diferencial.

Conclusiones:

  • El primer análisis global de los resultados funcionales post-tratamiento del Cáncer de Próstata reveló una precisión predictiva modesta debido a la heterogeneidad regional y de la práctica significativa.
  • Estos hallazgos resaltan las limitaciones de los modelos predictivos universales y la importancia de los datos internacionales a gran escala para la evaluación comparativa de resultados.
  • La investigación futura que utilice datos de TNGR se centrará en modelos específicos de la región para apoyar el asesoramiento personalizado del paciente y la mejora de la calidad.