Implementing precision psychiatry: a systematic review of individualized prediction models for clinical practice

Background: The impact of precision psychiatry for clinical practice has not been systematically appraised. This study aims to provide a comprehensive review of validated prediction models to estimate the individual risk of being affected with a condition (diagnostic), developing outcomes (prognostic), or responding to treatments (predictive) in mental disorders. Methods: PRISMA/RIGHT/CHARMS-compliant systematic review of the Web of Science, Cochrane Central Register of Reviews, and Ovid/PsycINFO databases from inception until July 21, 2019 (PROSPERO CRD42019155713) to identify diagnostic/prognostic/predictive prediction studies that reported individualized estimates in psychiatry and that were internally or externally validated or implemented. Random effect meta-regression analyses addressed the impact of several factors on the accuracy of prediction models. Findings: Literature search identified 584 prediction modeling studies, of which 89 were included. 10.4% of the total studies included prediction models internally validated (n = 61), 4.6% models externally validated (n = 27), and 0.2% (n = 1) models considered for implementation. Across validated prediction modeling studies (n = 88), 18.2% were diagnostic, 68.2% prognostic, and 13.6% predictive. The most frequently investigated condition was psychosis (36.4%), and the most frequently employed predictors clinical (69.5%). Unimodal compared to multimodal models (β = .29, P = .03) and diagnostic compared to prognostic (β = .84, p < .0001) and predictive (β = .87, P = .002) models were associated with increased accuracy. Interpretation: To date, several validated prediction models are available to support the diagnosis and prognosis of psychiatric conditions, in particular, psychosis, or to predict treatment response. Advancements of knowledge are limited by the lack of implementation research in real-world clinical practice. A new generation of implementation research is required to address this translational gap.

Schlagwörter

Fachgebiet (DDC)

330 - Wirtschaft

Projekt

Veranstaltung

Startdatum der Ausstellung

Enddatum der Ausstellung

Startdatum der Konferenz

Enddatum der Konferenz

Datum der letzten Prüfung

ISBN

ISSN

1745-1701
0586-7614

Sprache

Englisch

Während FHNW Zugehörigkeit erstellt

Nein

Zukunftsfelder FHNW

Publikationsstatus

Veröffentlicht

Begutachtung

Peer-Review der ganzen Publikation

Open Access-Status

Hybrid

Lizenz

Zitation

SALAZAR DE PABLO, Gonzalo, Erich STUDERUS, Julio VAQUERIZO-SERRANO, Jessica IRVING, Ana CATALAN, Dominic OLIVER, Helen BALDWIN, Andrea DANESE, Seena FAZEL, Ewout W STEYERBERG, Daniel STAHL und Paolo FUSAR-POLI, 2021. Implementing precision psychiatry: a systematic review of individualized prediction models for clinical practice. Schizophrenia Bulletin. 2021. Bd. 47, Nr. 2, S. 284–297. DOI 10.1093/schbul/sbaa120. Verfügbar unter: https://doi.org/10.26041/fhnw-10896

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