Department of Economics and Business Economics

Validation of an algorithm-based definition of treatment resistance in patients with schizophrenia

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  • Olesya Ajnakina, Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK. Electronic address: olesya.ajnakina@kcl.ac.uk.
  • ,
  • Henriette Thisted Horsdal
  • John Lally, Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK; Department of Psychiatry, Royal College of Surgeons in Ireland, Beaumont Hospital, Dublin, Ireland; Department of Psychiatry, School of Medicine and Medical Sciences, University College Dublin, St Vincent's University Hospital, Dublin, Ireland.
  • ,
  • James H MacCabe, Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK; National Institute for Health Research (NIHR) Mental Health Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King's College London, UK.
  • ,
  • Robin M Murray, Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK; National Institute for Health Research (NIHR) Mental Health Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King's College London, UK.
  • ,
  • Christiane Gasse
  • Theresa Wimberley

Large-scale pharmacoepidemiological research on treatment resistance relies on accurate identification of people with treatment-resistant schizophrenia (TRS) based on data that are retrievable from administrative registers. This is usually approached by operationalising clinical treatment guidelines by using prescription and hospital admission information. We examined the accuracy of an algorithm-based definition of TRS based on clozapine prescription and/or meeting algorithm-based eligibility criteria for clozapine against a gold standard definition using case notes. We additionally validated a definition entirely based on clozapine prescription. 139 schizophrenia patients aged 18-65years were followed for a mean of 5years after first presentation to psychiatric services in South-London, UK. The diagnostic accuracy of the algorithm-based measure against the gold standard was measured with sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV). A total of 45 (32.4%) schizophrenia patients met the criteria for the gold standard definition of TRS; applying the algorithm-based definition to the same cohort led to 44 (31.7%) patients fulfilling criteria for TRS with sensitivity, specificity, PPV and NPV of 62.2%, 83.0%, 63.6% and 82.1%, respectively. The definition based on lifetime clozapine prescription had sensitivity, specificity, PPV and NPV of 40.0%, 94.7%, 78.3% and 76.7%, respectively. Although a perfect definition of TRS cannot be derived from available prescription and hospital registers, these results indicate that researchers can confidently use registries to identify individuals with TRS for research and clinical practices.

Original languageEnglish
JournalSchizophrenia Research
Volume197
Pages (from-to)294-297
Number of pages4
ISSN0920-9964
DOIs
Publication statusPublished - 2018

    Research areas

  • 1ST-EPISODE PSYCHOSIS, ADHERENCE, ANTIPSYCHOTICS, ASSOCIATION, CLOZAPINE, Clozapine, GUIDELINES, INITIATION, LONG-TERM COURSE, Negative predictive value, PREDICTORS, Positive predictive value, REMISSION, Schizophrenia, Sensitivity, Specificity, Treatment resistance, Validation

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