5
Analysis of risk factors for antipsychotic-resistant schizophrenia in young patients – a retrospective analysis
Authors: Octavian Vasiliu, Daniel Vasile, Andreea F. Făinărea, Mihaela C. Pătrașcu, Elena A. Morariu, Raluca Manolache, Iulia Alexandru, Flavius T. Androne
Number of views: 375
Treatment resistant schizophrenia (TRS) is a severely disabling disorder, which decreases
dramatically the quality of life and overall functionality, while it increases the rate of hospital
admissions and overall healthcare costs. The main objective of this research was to evaluate the risk
factors for TRS in a group of patients based on a retrospective analysis. The secondary objective was to
design an algorithm for initial evaluation in patients with schizophrenia, in order to detect the
candidates at risk for developing TRS. Medical charts and consultation records of all patients aged
between 18 and 30, diagnosed with TRS, evaluated during 1-year in our department, were selected for
analysis. The most significant risk factors for TRS found in univariate model were younger age at
schizophrenia onset, male gender, living in rural areas, co-morbid drug dependence, lower therapeutic
adherence, and premorbid personality disorder. Marginally significant were higher Positive and
Negative Syndrome Scale (PANSS) scores at previous admissions, higher scores on PANSS negative
symptoms sub-scale, and lower educational background. In the multivariate model, TRS was still
significantly predicted (p<0.05) by younger age at the disease onset, addictive co-morbidity, and lower
therapeutic adherence. An algorithm based on these risk factors is suggested, based on (a) structured
PANSS evaluation using SCI-PANSS and Informant Questionnaire for PANSS, (b) a scale for the detection
of co-morbid drug dependence (i.e. Inventory of Drug Taking Situations, IDTS), (c) an
interview for detecting premorbid personality disorders (i.e. Structured Clinical
Interview for DSM IV – Axis II Disorders, SCID-II), and (d) Treatment Satisfaction
Questionnaire for Medication (TSQM) for therapeutic adherence monitoring. Also,
the inclusion of several pharmacogenetic parameters (at least CYP450 2D6 panel for
detection of poor/ultrarapid metabolizers) could be useful when establishing an
adequate therapeutic management, and may help in decreasing the rate of nonresponse
due to variations in antipsychotics plasma levels