Improving Prognostic Accuracy in Subjects at Clinical High Risk for Psychosis: Systematic Review of Predictive Models and Meta-analytical Sequential Testing Simulation

Abstract

Discriminating subjects at clinical high risk (CHR) for psychosis who will develop psychosis from those who will not is a prerequisite for preventive treatments. However, it is not yet possible to make any personalized prediction of psychosis onset relying only on the initial clinical baseline assessment. Here, we first present a systematic review of prognostic accuracy parameters of predictive modeling studies using clinical, biological, neurocognitive, environmental, and combinations of predictors. In a second step, we performed statistical simulations to test different probabilistic sequential 3-stage testing strategies aimed at improving prognostic accuracy on top of the clinical baseline assessment. The systematic review revealed that the best environmental predictive model yielded a modest positive predictive value (PPV) (63%). Conversely, the best predictive models in other domains (clinical, biological, neurocognitive, and combined models) yielded PPVs of above 82%. Using only data from validated models, 3-stage simulations showed that the highest PPV was achieved by sequentially using a combined (clinical + electroencephalography), then structural magnetic resonance imaging and then a blood markers model. Specifically, PPV was estimated to be 98% (number needed to treat, NNT = 2) for an individual with 3 positive sequential tests, 71%–82% (NNT = 3) with 2 positive tests, 12%–21% (NNT = 11–18) with 1 positive test, and 1% (NNT = 219) for an individual with no positive tests. This work suggests that sequentially testing CHR subjects with predictive models across multiple domains may substantially improve psychosis prediction following the initial CHR assessment. Multistage sequential testing may allow individual risk stratification of CHR individuals and optimize the prediction of psychosis.

The Clinical High-Risk State for Psychosis (CHR-P), Version II

“…Specifically, individuals referred by first episode and inpatient mental health services have a high pretest risk. 13 These findings advance knowledge indicating that CHR-P assessment should primarily be offered to selected samples of individuals "already distressed by mental problems and seeking help for them" (European Psychiatric Association recommendation n.4 14 ). Stratification of these subgroups 11 may inform outreach campaigns, subsequent testing 13 and optimize the psychosis prediction.…”

Brain morphologic changes in early stages of psychosis: Implications for clinical application and early intervention

“…has suggested the feasibility of identifying individuals at the highest risk of developing psychosis using neuroanatomical patterns (especially cortical and subcortical volumes) at the single‐subject level. Given the significant differences between the ARMS‐P and ‐NP groups, also in the gross morphologic features (e.g., sulcogyral pattern), functional neuroimaging data, and event‐related potentials (e.g., mismatch negativity), it may be expected that the combination of potential biological predictive markers in addition to clinical predictors, such as a high level of depression, cognitive impairments, poor functioning and negative symptoms, enhances accuracy in the prediction of psychosis onset in the clinical setting …”

Early psychosis detection program in Chile: A first step for the South American challenge in psychosis research

“…identified predictors of psychosis onset in other cohorts, such as some positive (unusual thought content and suspiciousness) and negative (anhedonia, asociality) symptoms (Cannon et al, 2016;Fusar-Poli et al, 2013;Schmidt et al, 2017), will also have prognostic value in our cohort. Sample will show similar results.…”

“…In our small cohort, baseline symptom severity does not predict transition to psychosis, likely due to insufficient power. We expect that as our cohort increases in size over time, identified predictors of psychosis onset in other cohorts, such as some positive (unusual thought content and suspiciousness) and negative (anhedonia, asociality) symptoms (Cannon et al, ; Fusar‐Poli et al, ; Schmidt et al, ), will also have prognostic value in our cohort. Sample will show similar results.…”