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An unbiased point estimate is often insufficient to predict a population estimate, such as population mean or population proportion. In this scenario, a confidence interval is used. A confidence interval is an estimate similar to a  sample proportion. However, unlike the point estimate which is a single value, the confidence interval  contains a range of values. These values have lower and upper limits, known as confidence limits, and can be designated as L1 and L2, respectively.
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Los intervalos de referencia personalizados (RIper) mejoran la precisión del diagnóstico al tener en cuenta la variabilidad individual. El marco paramétrico empírico de Bayes (PEB) permite un RIper confiable utilizando datos de población, incluso con resultados individuales limitados.

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Área de la Ciencia:

  • Medicina de laboratorio
  • Análisis de los biomarcadores
  • Diagnóstico personalizado

Sus antecedentes:

  • Los intervalos de referencia de toda la población (RIpop) pueden no reflejar los rangos homeostáticos individuales.
  • Los intervalos de referencia personalizados (RIper) pueden mejorar la precisión del diagnóstico.
  • Un marco de Bayes empírico paramétrico (PEB) estabiliza las estimaciones individuales para RIper confiable.

Objetivo del estudio:

  • Aplicar el marco PEB para la estimación de RIper para nueve biomarcadores clave.
  • Para comparar el RIper basado en PEB con los RIpop convencionales y los valores de cambio de referencia (RCV).
  • Evaluar la viabilidad del uso de datos rutinarios del Sistema de Información de Laboratorio (LIS) o de variación biológica (BV) para el establecimiento de parámetros de PEB.

Principales métodos:

  • Se aplicó el marco PEB para estimar el RIper de la albúmina, la creatinina, el fosfato, la cortisona, el cortisol, la testosterona, la androstenediona, la 17-hidroxiprogesterona y el 11-deoxicortisol.
  • Parámetros derivados de la PEB a partir de los datos del LIS y de un estudio local de la BV.
  • Evaluar los resultados marcados y comparar RIper con RIpop y RCV utilizando muestras de serie de adultos sanos.

Principales resultados:

  • Los RIper basados en PEB fueron consistentemente más estrechos que los RIpop, reduciendo los resultados marcados para la albúmina, el fosfato y la cortisona.
  • El marcado para la 17-hidroxiprogesterona aumentó pero se mantuvo cerca del 5% esperado.
  • Los umbrales de PEB corregidos para la regresión hacia la media, resultan más estrechos que las estimaciones estándar de RCV sin aumentar los resultados marcados.

Conclusiones:

  • El marco PEB genera efectivamente límites personalizados para las pruebas de laboratorio, incluso con datos individuales limitados.
  • Los parámetros PEB se pueden derivar de los datos LIS o BV, indicando una vía de implementación factible.
  • Este enfoque ofrece un método rentable para mejorar la precisión diagnóstica a través de intervalos de referencia personalizados.