Development and initial evaluation of a clinical prediction model for risk of treatment resistance in first-episode psychosis: Schizophrenia Prediction of Resistance to Treatment (SPIRIT) (2024)
Journal Article
Farooq, S., Hattle, M., Kingstone, T., Ajnakina, O., Dazzan, P., Demjaha, A., …Riley, R. D. (2024). Development and initial evaluation of a clinical prediction model for risk of treatment resistance in first-episode psychosis: Schizophrenia Prediction of Resistance to Treatment (SPIRIT). British Journal of Psychiatry, 1-10. https://doi.org/10.1192/bjp.2024.101

Background
A clinical tool to estimate the risk of treatment-resistant schizophrenia (TRS) in people with first-episode psychosis (FEP) would inform early detection of TRS and overcome the delay of up to 5 years in starting TRS medication.

Aims... Read More about Development and initial evaluation of a clinical prediction model for risk of treatment resistance in first-episode psychosis: Schizophrenia Prediction of Resistance to Treatment (SPIRIT).

Risk of bias assessments in individual participant data meta-analyses of test accuracy and prediction models: a review shows improvements are needed. (2023)
Journal Article
Levis, B., Snell, K. I., Damen, J. A., Hattle, M., Ensor, J., Dhiman, P., …Riley, R. D. (in press). Risk of bias assessments in individual participant data meta-analyses of test accuracy and prediction models: a review shows improvements are needed. Journal of Clinical Epidemiology, S0895-4356(23)00282-2. https://doi.org/10.1016/j.jclinepi.2023.10.022

Risk of bias assessments are important in meta-analyses of both aggregate and individual participant data (IPD). There is limited evidence on whether and how risk of bias of included studies or datasets in IPD meta-analyses (IPDMAs) is assessed. We r... Read More about Risk of bias assessments in individual participant data meta-analyses of test accuracy and prediction models: a review shows improvements are needed..