Implementing Precision Psychiatry: A Systematic Review of Individualized Prediction Models for Clinical Practice

doi:10.1093/schbul/sbaa120

. 2021 Mar 16;47(2):284-297.

doi: 10.1093/schbul/sbaa120.

Implementing Precision Psychiatry: A Systematic Review of Individualized Prediction Models for Clinical Practice

Gonzalo Salazar de Pablo^{1

2

3}, Erich Studerus⁴, Julio Vaquerizo-Serrano^{1

2

3}, Jessica Irving¹, Ana Catalan^{1

5

6

7}, Dominic Oliver¹, Helen Baldwin¹, Andrea Danese^{3

8

9}, Seena Fazel¹⁰, Ewout W Steyerberg^{11

12}, Daniel Stahl¹³, Paolo Fusar-Poli^{1

14

15

16}

Affiliations

¹ Early Psychosis: Interventions and Clinical-detection Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, 16 De Crespigny Park, London, UK.
² Institute of Psychiatry and Mental Health, Department of Child and Adolescent Psychiatry, Hospital General Universitario Gregorio Marañón School of Medicine, Universidad Complutense, Instituto de Investigación Sanitaria Gregorio Marañón, CIBERSAM, Madrid, Spain.
³ Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.
⁴ Division of Personality and Developmental Psychology, Department of Psychology, University of Basel, Basel, Switzerland.
⁵ Department of Psychiatry, Basurto University Hospital, Bilbao, Spain.
⁶ Mental Health Group, BioCruces Health Research Institute, Bizkaia, Spain.
⁷ Neuroscience Department, University of the Basque Country UPV/EHU, Leioa, Spain.
⁸ Social, Genetic and Developmental Psychiatry Centre, King's College London, London, UK.
⁹ National and Specialist CAMHS Clinic for Trauma, Anxiety, and Depression, South London and Maudsley NHS Foundation Trust, London, UK.
¹⁰ Department of Psychiatry, University of Oxford, Oxford, UK.
¹¹ Department of Biomedical Data Sciences, Leiden University Medical Centre, Leiden, the Netherlands.
¹² Department of Public Health, Erasmus MC, Rotterdam, the Netherlands.
¹³ Biostatistics Department, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.
¹⁴ OASIS Service, South London and Maudsley NHS Foundation Trust, London, UK.
¹⁵ Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy.
¹⁶ National Institute for Health Research, Maudsley Biomedical Research Centre, South London and Maudsley NHS Foundation Trust, London, UK.

PMID: 32914178
PMCID: PMC7965077
DOI: 10.1093/schbul/sbaa120

Implementing Precision Psychiatry: A Systematic Review of Individualized Prediction Models for Clinical Practice

Gonzalo Salazar de Pablo et al. Schizophr Bull. 2021.

. 2021 Mar 16;47(2):284-297.

doi: 10.1093/schbul/sbaa120.

Authors

Affiliations

¹ Early Psychosis: Interventions and Clinical-detection Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, 16 De Crespigny Park, London, UK.
² Institute of Psychiatry and Mental Health, Department of Child and Adolescent Psychiatry, Hospital General Universitario Gregorio Marañón School of Medicine, Universidad Complutense, Instituto de Investigación Sanitaria Gregorio Marañón, CIBERSAM, Madrid, Spain.
³ Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.
⁴ Division of Personality and Developmental Psychology, Department of Psychology, University of Basel, Basel, Switzerland.
⁵ Department of Psychiatry, Basurto University Hospital, Bilbao, Spain.
⁶ Mental Health Group, BioCruces Health Research Institute, Bizkaia, Spain.
⁷ Neuroscience Department, University of the Basque Country UPV/EHU, Leioa, Spain.
⁸ Social, Genetic and Developmental Psychiatry Centre, King's College London, London, UK.
⁹ National and Specialist CAMHS Clinic for Trauma, Anxiety, and Depression, South London and Maudsley NHS Foundation Trust, London, UK.
¹⁰ Department of Psychiatry, University of Oxford, Oxford, UK.
¹¹ Department of Biomedical Data Sciences, Leiden University Medical Centre, Leiden, the Netherlands.
¹² Department of Public Health, Erasmus MC, Rotterdam, the Netherlands.
¹³ Biostatistics Department, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.
¹⁴ OASIS Service, South London and Maudsley NHS Foundation Trust, London, UK.
¹⁵ Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy.
¹⁶ National Institute for Health Research, Maudsley Biomedical Research Centre, South London and Maudsley NHS Foundation Trust, London, UK.

PMID: 32914178
PMCID: PMC7965077
DOI: 10.1093/schbul/sbaa120

Abstract

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.

Keywords: evidence; implementation; individualized; prediction; prevention; prognosis; risk; validation.

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Figures

**Fig. 1.**
Preferred Reporting Items for Systematic Reviews and Meta-Analyses flowchart outlining study selection process.

**Fig. 2.**
Proportion of prediction models studies developed, internally validated, externally validated, and implemented in the psychiatric literature.

**Fig. 3.**
Most frequently reported predictors (above, top 10%) and conditions (below, all) in the included studies.

**Fig. 4.**
Correlation between apparent and external accuracy (n = 18).

See this image and copyright information in PMC

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References

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[1] Terry SF. Obama’s precision medicine initiative. Genet Test Mol Biomarkers. 2015;19(3):113–114. - PMC - PubMed

[2] Terry SF. Obama’s precision medicine initiative. Genet Test Mol Biomarkers. 2015;19(3):113–114. - PMC - PubMed

[3] Genetics Reference. What is precision medicine?https://ghr.nlm.nih.gov/primer/precisionmedicine/definition. Accessed March 1, 2020.

[4] Genetics Reference. What is precision medicine?https://ghr.nlm.nih.gov/primer/precisionmedicine/definition. Accessed March 1, 2020.

[5] Farhud DD, Zarif Yeganeh M. A brief history of human blood groups. Iran J Public Health. 2013;42(1):1–6. - PMC - PubMed

[6] Farhud DD, Zarif Yeganeh M. A brief history of human blood groups. Iran J Public Health. 2013;42(1):1–6. - PMC - PubMed

[7] Fusar-Poli P, Hijazi Z, Stahl D, Steyerberg EW. The science of prognosis in psychiatry: a review. JAMA Psychiatry. 2018;75(12):1289–1297. - PubMed

[8] Fusar-Poli P, Hijazi Z, Stahl D, Steyerberg EW. The science of prognosis in psychiatry: a review. JAMA Psychiatry. 2018;75(12):1289–1297. - PubMed

[9] Wolff RF, Moons KGM, Riley RD, et al. ; PROBAST Group . PROBAST: a tool to assess the risk of bias and applicability of prediction model studies. Ann Intern Med. 2019;170(1):51–58. - PubMed

[10] Wolff RF, Moons KGM, Riley RD, et al. ; PROBAST Group . PROBAST: a tool to assess the risk of bias and applicability of prediction model studies. Ann Intern Med. 2019;170(1):51–58. - PubMed

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Implementing Precision Psychiatry: A Systematic Review of Individualized Prediction Models for Clinical Practice

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Implementing Precision Psychiatry: A Systematic Review of Individualized Prediction Models for Clinical Practice

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