RESUMEN
Únicamente el 50% de los pacientes con infección crónica por el genotipo 1 del virus de la hepatitis C responde con éxito a la terapia estándar con interferón alfa pegilado y ribavirina, y los recientemente aprobados inhibidores de la proteasa deberán administrarse conjuntamente con estos dos fármacos. En consecuencia, predecir la respuesta a la terapia estándar, idealmente antes de iniciarla, sigue siendo un reto importante. Aunque se han descrito varios factores basales predictivos del fallo terapéutico, tanto del hospedador como del virus, ninguno de ellos es capaz de proporcionar predicciones fiables a nivel individual. Por otro lado, el desarrollo de modelos multivariantes que agrupan varios factores predictivos, hasta el momento no ha permitido obtener predicciones con el grado de fiabilidad necesario para poder ser implementados en la práctica clínica. Por lo tanto es necesario seguir investigando para mejorar estos modelos predictivos y describir nuevos factores que nos ayuden a predecir la respuesta de manera más fiable y reproducible. El desarrollo de algoritmos de selección de candidatos a recibir las nuevas terapias en función de sus probabilidades de responder o no a la terapia estándar permitirá reducir los costes asociados al tratamiento y mejorar la calidad de vida de los pacientes. Con esta revisión hemos querido dar una visión de las posibilidades actuales para predecir la respuesta a la terapia estándar en los pacientes con hepatitis C crónica por el genotipo 1 del virus de la hepatitis C (AU)
Only about 50% of patients chronically infected with hepatitis C virus genotype 1 achieve a successful response to standard treatment with pegylated interferon-alfa and ribavirin. Moreover, the recently approved protease inhibitors will have to be administered together with these drugs. Consequently, predicting response to standard treatment, ideally before starting it, remains an important challenge. Although several baseline predictors of treatment failure have been described, including clinical and virological factors, none of them is able to provide reliable predictions at the individual level. In addition, the development of multivariate models combining several predictive factors has not yet yielded predictions with the requisite reliability for use in clinical practice. Therefore, further research is needed to improve predictive models and to describe new factors that would enable us to predict treatment outcome with greater reliability and reproducibility. The development of candidate selection algorithms that help clinicians to identify which patients could benefit from the new therapies on the basis of their chances of responding to standard therapy is of major interest for both patient well-being and healthcare expense. This review attempts to provide a view of the current options for predicting the response to pegylated interferon-alfa plus ribavirin therapy in patients chronically infected with hepatitis C virus genotype 1 (AU)
Asunto(s)
Humanos , Hepacivirus/genética , Hepatitis C Crónica/tratamiento farmacológico , Tropismo Viral/genética , Antivirales/farmacocinética , Genotipo , Interferón-alfa/farmacocinética , Análisis MultivarianteRESUMEN
Only about 50% of patients chronically infected with hepatitis C virus genotype 1 achieve a successful response to standard treatment with pegylated interferon-alfa and ribavirin. Moreover, the recently approved protease inhibitors will have to be administered together with these drugs. Consequently, predicting response to standard treatment, ideally before starting it, remains an important challenge. Although several baseline predictors of treatment failure have been described, including clinical and virological factors, none of them is able to provide reliable predictions at the individual level. In addition, the development of multivariate models combining several predictive factors has not yet yielded predictions with the requisite reliability for use in clinical practice. Therefore, further research is needed to improve predictive models and to describe new factors that would enable us to predict treatment outcome with greater reliability and reproducibility. The development of candidate selection algorithms that help clinicians to identify which patients could benefit from the new therapies on the basis of their chances of responding to standard therapy is of major interest for both patient well-being and healthcare expense. This review attempts to provide a view of the current options for predicting the response to pegylated interferon-alfa plus ribavirin therapy in patients chronically infected with hepatitis C virus genotype 1.
