Evidence map›Paper›PMID 42701990›Full record

ReviewEuropean archives of psychiatry and clinical neuroscience2026

Toward precision medicine: can neuroimaging prospectively predict early treatment outcomes in schizophrenia spectrum disorders? A systematic review and meta-analysis.

Claudio Caiazza, Giancarlo Fusco, Lorenzo Ugga, Flavia Rossano, Claudia Toni, Mario Cirillo, Gaia Sampogna, Andrea Fiorillo

Abstract readReview
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In one paragraph

Review in European archives of psychiatry and clinical neuroscience, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Claudio CaiazzaAzienda Sanitaria Locale Napoli 3 Sud, U.O.S.M. 55-57 Torre del Greco, Ercolano, Via Guglielmo Marconi, 66, 80059, Torre del Greco, Italy. claudiocaiazza@gmail.com.
Giancarlo FuscoDepartment of Advanced Biomedical Sciences, University of Naples "Federico II", Naples, Italy.
Lorenzo UggaDepartment of Advanced Medical and Surgical Sciences, University of Campania "Luigi Vanvitelli", Naples, Italy.
Flavia RossanoAzienda Sanitaria Locale Napoli 1 Centro, Unità Operativa Complessa Salute Mentale 32 e 33, Via Walt Disney, 6, Naples, Italy.
Claudia ToniDepartment of Psychiatry, University of Campania "Luigi Vanvitelli", Naples, Italy.
Mario CirilloDepartment of Advanced Medical and Surgical Sciences, University of Campania "Luigi Vanvitelli", Naples, Italy.
Gaia SampognaDepartment of Psychiatry, University of Campania "Luigi Vanvitelli", Naples, Italy.
Andrea FiorilloDepartment of Psychiatry, University of Campania "Luigi Vanvitelli", Naples, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundVariability in antipsychotic response results from interaction of illness-related, treatment-related, environmental factors, and intrinsic interindividual differences that have not yet been addressed. Since early non-response may predict later non-response, biomarkers capable of identifying individuals at higher risk of treatment failure may have important implications for management personalization. This study aimed to evaluate whether baseline neuroimaging can predict subsequent treatment outcomes in Schizophrenia-spectrum Disorders.

methodsA systematic search of PubMed/EMBASE/IEEE Xplore was conducted until 04/20/2026, in accordance with PRISMA-DTA guidelines and a pre-registered protocol. Prospective studies using Magnetic Resonance Imaging/Positron Emission Tomography with predictive models for subsequent treatment outcomes were included. A random-effects multi-level meta-analysis was performed to pool areas under the curve (AUC). Hierarchical summary receiver operating characteristic (HSROC) curves estimated sensitivity/specificity. QUADAS-2 assessed Risk-of-bias.

resultsSixteen studies were included. The overall pooled discriminatory performance of multi-level hierarchical models was good (AUC = 0.75,95%C.I.[0.70-0.80],τ²=0.071,I

conclusionBaseline neuroimaging may provide relevant prognostic information in Schizophrenia Spectrum, especially based on functional connectivity, supporting that treatment response may be related to disturbances in large-scale network organization than to isolated structural abnormalities. These findings support the potential of prognostic neuroimaging in precision psychiatry and early-risk stratification. However, methodological standardization, external validation, and geographically-diverse samples remain necessary before a full clinical translation.

Indexed as

AntipsychoticsBiomarkersMachine learningPrecision psychiatryPrognosisPsychosis

Identifiers

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.