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Medir la carga de participación de los pacientes en las evaluaciones de resultados clínicos para ensayos clínicos
Abigail Dirks1, Hana Do2, Chelsea Gallagher3
1Tufts Center for the Study of Drug Development, Boston, United States. abigail.dirks@tufts.edu.
Therapeutic innovation & regulatory science
|August 21, 2025
Resumen
La carga de la participación en ensayos clínicos varía según el tipo y la duración de la evaluación. La comprensión de la carga del paciente y el sitio de las evaluaciones de resultados clínicos puede informar el diseño del protocolo para reducir la complejidad del ensayo.
Área de la Ciencia:
- Metodología de los ensayos clínicos
- Resultados de la investigación informados por pacientes
- Investigación en servicios de salud
Sus antecedentes:
- Bristol Myers Squibb (BMS), ZS y Tufts CSDD evaluaron la carga de participación en las evaluaciones de resultados clínicos (COA).
- Esta evaluación se centró en los resultados informados por los pacientes (PRO) y otros COA utilizados en ensayos clínicos.
Objetivo del estudio:
- Evaluar la carga de participación asociada con los diferentes COA en ensayos clínicos.
- Identificar los factores que contribuyen a la carga para los pacientes y los centros de investigación.
- Informar estrategias para reducir la carga de participación en el diseño de ensayos clínicos.
Principales métodos:
- Se empleó un método mixto.
- Se realizó una encuesta global en línea de 258 pacientes.
- Se llevaron a cabo entrevistas en profundidad con 12 pacientes y 12 miembros del personal del centro de investigación.
Principales resultados:
- La percepción de la carga por parte de los pacientes difiere significativamente según la modalidad y el tipo de AOC.
- Los COA de más de 30 minutos o administrados varias veces al mes se asociaron con una mayor carga.
- La edad del paciente, la etnia y los desafíos técnicos con los COA electrónicos impactaron la carga percibida.
Conclusiones:
- Los hallazgos del estudio aumentan la conciencia de la carga de participación del paciente relacionada con los AOC.
- Los resultados informan las decisiones para reducir selectivamente la carga de participación en los protocolos de ensayos clínicos.
- Esta investigación se basa en el algoritmo de carga del paciente de Tufts CSDD-ZS.
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