Literature DB >> 23435091

Prediction of acute clinical response following a first episode of non affective psychosis: results of a cohort of 375 patients from the Spanish PAFIP study.

Benedicto Crespo-Facorro1, Victor Ortiz-Garcia de la Foz, Rosa Ayesa-Arriola, Rocío Pérez-Iglesias, Ignacio Mata, Paula Suarez-Pinilla, Rafael Tabares-Seisdedos, José Luis Vázquez-Barquero.   

Abstract

OBJECTIVE: Predicting response to antipsychotic treatment might optimize treatment strategies in early phases of schizophrenia. We aimed to investigate sociodemographic, premorbid and clinical predictors of response to antipsychotic treatment after a first episode of non-affective psychosis.
METHOD: 375 (216 males) patients with a diagnosis of non affective psychosis entered the study. The main outcome measure was clinical response at 6 weeks and variables at baseline were evaluated as predictors of response. ANOVA for continuous and chi-square for categorical data were used to compare responders and non-responders. Multivariate logistic regression was used to establish a prediction model.
RESULTS: 53.3% of study subjects responded to antipsychotic treatment. The following variables were associated with an unfavorable response: 1.--lower severity of symptoms at baseline; 2.--diagnosis of schizophrenia; 3.--longer DUI and DUP; 4.--poorer premorbid adjustment during adolescence and adulthood; 5.--family history of psychosis, and 6.--hospitalization. Patients with a family history of psychosis, longer DUP, poor premorbid functioning and lower severity of psychotic symptoms at intake have a reduced likelihood of responding to antipsychotic treatment.
CONCLUSION: Helping clinicians to identify those first episode patients with a lower probability of having a favorable clinical response is meant as a first step to achieve a successful initial treatment.
Copyright © 2013 Elsevier Inc. All rights reserved.

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Year:  2013        PMID: 23435091     DOI: 10.1016/j.pnpbp.2013.02.009

Source DB:  PubMed          Journal:  Prog Neuropsychopharmacol Biol Psychiatry        ISSN: 0278-5846            Impact factor:   5.067


  14 in total

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Review 2.  Treatment resistant schizophrenia: Clinical, biological, and therapeutic perspectives.

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3.  Prediction of Early Symptom Remission in Two Independent Samples of First-Episode Psychosis Patients Using Machine Learning.

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4.  Accessing Gene Expression in Treatment-Resistant Schizophrenia.

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7.  Polygenic Risk Score for Schizophrenia and Treatment-Resistant Schizophrenia.

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8.  Striatal D(2/3) Binding Potential Values in Drug-Naïve First-Episode Schizophrenia Patients Correlate With Treatment Outcome.

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Review 9.  Clinical predictors of therapeutic response to antipsychotics in schizophrenia.

Authors:  Maren Carbon; Christoph U Correll
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10.  Identification of increased genetic risk scores for schizophrenia in treatment-resistant patients.

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Journal:  Mol Psychiatry       Date:  2014-06-03       Impact factor: 15.992

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