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How Can Pharmacogenomics Biomarkers Be Translated into Patient Benefit
- D. Collier, E. Achilla, G. Breen, S. Curran, D. Dima, R. Flanagan, J. Frank, S. Frangou, C. Gasse, I. Giegling, M. Rietschel, D. Rujescu, J. Maccabe, P. McCrone, J. Mill, E. Sigurdsson, H. Stefansson, J. Walters, M. Verbelen, M. Helthuis
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- Journal:
- European Psychiatry / Volume 30 / Issue S1 / March 2015
- Published online by Cambridge University Press:
- 15 April 2020, p. 1
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Treatment resistant schizophrenia (TRS) is one of the most disabling of psychiatric disorders, affecting about 1/3 of patients. First-line treatments include both atypical and typical antipsychotics. The original atypical, clozapine, is a final option, and although it has been shown to be the only effective treatment for TRS, many patients do not respond well to clozapine. Clozapine use is related to adverse events, most notably agranulocytosis, a potentially fatal blood disorder which affects about 1% of those prescribed clozapine and requires regular blood monitoring. This as a barrier to prescription and there is a long delay in access for TRS patients, of five or more years, from first antipsychotic prescription. Better tools to predict treatment resistance and to identify risk of adverse events would allow faster and safer access to clozapine for patients who are likely to benefit from it. The CRESTAR project (www.crestar-project.eu) is a European Framework 7 collaborative project that aims to develop tools to predict i) treatment response, particularly patients who are less likely to respond to usual antipsychotics, indicating treatment with clozapine as early as possible, ii) patients who are at high or low risk of adverse events and side effects, iii) extreme TRS patients so that they can be stratified in clinical trials for novel treatments. CRESTAR has addressed these questions by examining genome-wide association data, genome sequence, epigenetic biomarkers and epidemiological data in European patient cohorts characterized for treatment response, and adverse drug reaction using data from clozapine therapeutic drug monitoring and linked National population medical and pharmacy databases, to identify predictive factors. In parallel CRESTAR will perform health economic research on potential benefits, and ethics and patient-centred research with stakeholders.
Factors associated with use of psychiatric intensive care and seclusion in adult inpatient mental health services
- A. E. Cullen, L. Bowers, M. Khondoker, S. Pettit, E. Achilla, L. Koeser, L. Moylan, J. Baker, A. Quirk, F. Sethi, D. Stewart, P. McCrone, A. D. Tulloch
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- Journal:
- Epidemiology and Psychiatric Sciences / Volume 27 / Issue 1 / February 2018
- Published online by Cambridge University Press:
- 20 October 2016, pp. 51-61
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Aims.
Within acute psychiatric inpatient services, patients exhibiting severely disturbed behaviour can be transferred to a psychiatric intensive care unit (PICU) and/or secluded in order to manage the risks posed to the patient and others. However, whether specific patient groups are more likely to be subjected to these coercive measures is unclear. Using robust methodological and statistical techniques, we aimed to determine the demographic, clinical and behavioural predictors of both PICU and seclusion.
Methods.Data were extracted from an anonymised database comprising the electronic medical records of patients within a large South London mental health trust. Two cohorts were derived, (1) a PICU cohort comprising all patients transferred from general adult acute wards to a non-forensic PICU ward between April 2008 and April 2013 (N = 986) and a randomly selected group of patients admitted to general adult wards within this period who were not transferred to PICU (N = 994), and (2) a seclusion cohort comprising all seclusion episodes occurring in non-forensic PICU wards within the study period (N = 990) and a randomly selected group of patients treated in these wards who were not secluded (N = 1032). Demographic and clinical factors (age, sex, ethnicity, diagnosis, admission status and time since admission) and behavioural precursors (potentially relevant behaviours occurring in the 3 days preceding PICU transfer/seclusion or random sample date) were extracted from electronic medical records. Mixed effects, multivariable logistic regression analyses were performed with all variables included as predictors.
Results.PICU cases were significantly more likely to be younger in age, have a diagnosis of bipolar disorder and to be held on a formal section compared with patients who were not transferred to PICU; female sex and longer time since admission were associated with lower odds of transfer. With regard to behavioural precursors, the strongest predictors of PICU transfer were incidents of physical aggression towards others or objects and absconding or attempts to abscond. Secluded patients were also more likely to be younger and legally detained relative to non-secluded patients; however, female sex increased the odds of seclusion. Likelihood of seclusion also decreased with time since admission. Seclusion was significantly associated with a range of behavioural precursors with the strongest associations observed for incidents involving restraint or shouting.
Conclusions.Whilst recent behaviour is an important determinant, patient age, sex, admission status and time since admission also contribute to risk of PICU transfer and seclusion. Alternative, less coercive strategies must meet the needs of patients with these characteristics.