Farooq, S ORCID: https://orcid.org/0000-0003-2088-6876, Hattle, M, Dazzan, P, Kingstone, T ORCID: https://orcid.org/0000-0001-9179-2303, Ajnakina, O, Shiers, D, Nettis, MA, Lawrence, A, Riley, RD ORCID: https://orcid.org/0000-0001-8699-0735 and van der Windt, DA ORCID: https://orcid.org/0000-0002-7248-6703 (2022) Study protocol for the development and internal validation of Schizophrenia Prediction of Resistance to Treatment (SPIRIT): a clinical tool for predicting risk of treatment resistance to antipsychotics in first-episode schizophrenia. BMJ Open, 12 (4). e056420.

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Abstract

INTRODUCTION: Treatment-resistant schizophrenia (TRS) is associated with significant impairment of functioning and high treatment costs. Identification of patients at high risk of TRS at the time of their initial diagnosis may significantly improve clinical outcomes and minimise social and functional disability. We aim to develop a prognostic model for predicting the risk of developing TRS in patients with first-episode schizophrenia and to examine its potential utility and acceptability as a clinical decision tool. METHODS AND ANALYSIS: We will use two well-characterised longitudinal UK-based first-episode psychosis cohorts: Aetiology and Ethnicity in Schizophrenia and Other Psychoses and Genetics and Psychosis for which data have been collected on sociodemographic and clinical characteristics. We will identify candidate predictors for the model based on current literature and stakeholder consultation. Model development will use all data, with the number of candidate predictors restricted according to available sample size and event rate. A model for predicting risk of TRS will be developed based on penalised regression, with missing data handled using multiple imputation. Internal validation will be undertaken via bootstrapping, obtaining optimism-adjusted estimates of the model's performance. The clinical utility of the model in terms of clinically relevant risk thresholds will be evaluated using net benefit and decision curves (comparative to competing strategies). Consultation with patients and clinical stakeholders will determine potential thresholds of risk for treatment decision-making. The acceptability of embedding the model as a clinical tool will be explored using qualitative focus groups with up to 20 clinicians in total from early intervention services. Clinicians will be recruited from services in Stafford and London with the focus groups being held via an online platform. ETHICS AND DISSEMINATION: The development of the prognostic model will be based on anonymised data from existing cohorts, for which ethical approval is in place. Ethical approval has been obtained from Keele University for the qualitative focus groups within early intervention in psychosis services (ref: MH-210174). Suitable processes are in place to obtain informed consent for National Health Service staff taking part in interviews or focus groups. A study information sheet with cover letter and consent form have been prepared and approved by the local Research Ethics Committee. Findings will be shared through peer-reviewed publications, conference presentations and social media. A lay summary will be published on collaborator websites.

Item Type: Article
Additional Information: This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial.
Subjects: R Medicine > R Medicine (General)
Divisions: Faculty of Medicine and Health Sciences > Primary Care Health Sciences
Related URLs:
Depositing User: Symplectic
Date Deposited: 04 May 2022 14:22
Last Modified: 04 May 2022 14:22
URI: https://eprints.keele.ac.uk/id/eprint/10855

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