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Genetic variants in combination with early partial improvement as a clinical utility predictor of treatment outcome in major depressive disorder: the result of two pooled RCTs
Pharmacogenetics may allow for a personalized treatment, but a combination with clinical variables may further enhance prediction. In particular, in the present paper, we investigated early partial improvement (EPI) defined as 20% or more improvement by rating scales 2 weeks after treatment, in com...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4445755/ https://www.ncbi.nlm.nih.gov/pubmed/25710119 http://dx.doi.org/10.1038/tp.2015.6 |
Sumario: | Pharmacogenetics may allow for a personalized treatment, but a combination with clinical variables may further enhance prediction. In particular, in the present paper, we investigated early partial improvement (EPI) defined as 20% or more improvement by rating scales 2 weeks after treatment, in combination with selected gene variants as a predictor of treatment outcome in patients with major depressive disorder. Two randomized controlled trials with 168 Japanese depressed patients were used. A stepwise multiple linear regression model with HAM-D score change at week 6 as the dependent variable and genotypes, EPI, baseline HAM-D score, age and sex as independent variables was performed in paroxetine, fluvoxamine and milnacipran, respectively, to estimate the prediction of HAM-D change at week 6. In the paroxetine sample, only EPI (P<0.001) was significantly associated with HAM-D change (n=81, R(2)=0.25, P<0.001). In the fluvoxamine sample, 5-HTTLPR La/Lg, S (P=0.029), FGF2 rs1449683C/T (P=0.013) and EPI (P=0.003) were associated with HAM-D change (n=42, R(2)=0.43, P<0.001). In the milnacipran sample, HTR-1A-1019C/G (P=0.001), ADRA2A-1297C/G (P=0.028) and EPI (P<0.001) were associated with outcome (n=45, R(2)=0.71, P<0.001). EPI in combination with genetic variants could be a useful predictor of treatment outcome and could strengthen the practical use of pharmacogenetic data in clinical practice. |
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