Transdiagnostic Individualized Clinically Based Risk Calculator for the Detection of Individuals at Risk and the Prediction of Psychosis: Model Refinement Including Nonlinear Effects of Age - Fusar-Poli, Paolo; Davies, Cathy; Rutigliano, Grazia; Stahl, Daniel; Bonoldi, Ilaria; McGuire, Philip (Frontiers in Psychiatry, 2019)
Background The first rate-limiting step for primary indicated prevention of psychosis is the detection of young people who may be at risk. The ability of specialised clinics to detect individuals at risk for psychosis is limited. A clinically based, individualised, transdiagnostic risk calculator has been developed and externally validated to improve the detection of individuals at risk in secondary mental health care. This calculator employs core sociodemographic and clinical predictors, including age, which is defined in linear terms. Recent evidence has suggested a non-linear impact of age on the probability of psychosis onset. Aim To define at a meta-analytical level the function linking age and probability of psychosis onset. To incorporate this function in a refined version of the transdiagnostic risk calculator and to test its prognostic performance, compared to the original specification. Design Secondary analyses on a previously published meta-analysis and clinical register-based cohort study based on 2008-2015 routine secondary mental health care in South-London and Maudsley (SLaM) National Health Service (NHS) Foundation Trust. Participants All patients receiving a first index diagnosis of non-organic/non-psychotic mental disorder within SLaM NHS Trust in the period 2008-2015. Main outcome measure Prognostic accuracy (Harrell’s C). Results 91199 patients receiving a first index diagnosis of non-organic and non-psychotic mental disorder within SLaM NHS Trust were included in the derivation (33820) or external validation (54716) datasets. The mean follow-up was 1588 days. The meta-analytical estimates showed that a second-degree fractional polynomial model with power (-2, -1: age1=age-2 and age2=age-1) was the best fitting model (P<0.001). The refined model which included this function showed an excellent prognostic accuracy in the external validation (Harrell’s C 0.805, 95%CI from 0.790 to 0.819), which was statistically higher than the original model, although of modest magnitude (Harrell’s C change=0.0136, 95%Cis from 0.006 to 0.021, P<0.001). Conclusions The use of a refined version of the clinically based, individualised, transdiagnostic risk calculator, which allows for non-linearity in the association between age and risk of psychosis onset may offer a modestly improved prognostic performance. This calculator may be particularly useful in young individuals at risk of psychosis who access secondary mental health care.