UMIN-CTR Clinical Trial

Public title

Development and validation of a clinical prediction model for psychotic relapse within 12 months after discharge in people with schizophrenia

Acronym

Development and validation of a clinical prediction model for psychotic relapse within 12 months after discharge in people with schizophrenia

Scientific Title

Development and validation of a clinical prediction model for psychotic relapse within 12 months after discharge in people with schizophrenia

Scientific Title:Acronym

Development and validation of a clinical prediction model for psychotic relapse within 12 months after discharge in people with schizophrenia

Region

Japan

Condition

Schizophrenia and related disorders

Classification by specialty

Psychiatry

Classification by malignancy

Others

Genomic information

NO

Narrative objectives1

To develop and validate a clinical prediction model for psychotic relapse within 12 months after discharge in people with schizophrenia and related disorders who are aged 18 years or older, by retrospectively collecting pre-specified prognostic factors by chart review in five urban and rural hospitals.

Basic objectives2

Others

Basic objectives -Others

This study aims to build a prediction model and validate its accuracy and generalisability.

Trial characteristics_1

Trial characteristics_2

Developmental phase

Primary outcomes

Psychotic relapse as a composite outcome defined by an occurrence of any one of the following: psychiatric hospitalisation, psychiatrist's decision that hospitalisation is required, an increase in antipsychotic dosage, an increase in the level of psychiatric care, and violence to self and/or others. Participants will be followed up up to 12 months after their discharge from the index hospitalisation.

Key secondary outcomes

Psychiatric hospitalisation due to psychotic relapse

Study type

Observational

Basic design

Randomization

Randomization unit

Blinding

Control

Stratification

Dynamic allocation

Institution consideration

Blocking

Concealment

No. of arms

Purpose of intervention

Type of intervention

Interventions/Control_1

Interventions/Control_2

Interventions/Control_3

Interventions/Control_4

Interventions/Control_5

Interventions/Control_6

Interventions/Control_7

Interventions/Control_8

Interventions/Control_9

Interventions/Control_10

Age-lower limit

18

years-old

<=

Age-upper limit

Not applicable

Gender

Male and Female

Key inclusion criteria

Patients who were discharged from one of five participating hospitals between January 2014 and December 2018 will be included if they were diagnosed as one of the following (ICD-10 code in the parentheses):
- Schizophrenia (F20)
- Schizotypal disorder (F21)
- Persistent delusional disorders (F22)
- Acute and transient psychotic disorders (F23)
- Induced delusional disorder (F24)
- Schizoaffective disorders (F25)
- Other nonorganic psychotic disorders (F28)
- Unspecified nonorganic psychosis (F29)

Key exclusion criteria

Patients with the following conditions will be excluded:
- Those who had been enrolled in this study with a previous episode of hospitalisation due to psychosis (i.e. a patient cannot be enrolled more than once during the study period)
- Those with substance/medication-induced psychosis
- Those with psychosis due to another medical condition, including peri-and postpartum psychosis and psychosis in dementia
- Those with diagnosis in the inclusion criteria whose admission are not due to psychosis as judged by one of investigators
- Those with diagnosis in the inclusion criteria with which one of investigators disagree due to the lack of sound reasoning
- Those discharged from a non-acute ward
- Those with a plan to be readmitted in the short period of time
- Those with ambiguous diagnosis as judged by one of investigators
- Those discharged to another psychiatric hospital
- Those discharged to medical hospital

Target sample size

800

Name of lead principal investigator

1st name	Toshiaki
Middle name	A
Last name	Furukawa

Organization

Kyoto University Graduate School of Medicine / School of Public Health

Division name

Department of Health Promotion and Human Behavior

Zip code

606-8501

Address

Yoshida Konoe-cho, Sakyo-ku, Kyoto

TEL

075-753-9491

Email

furukawa@kuhp.kyoto-u.ac.jp

Name of contact person

1st name	Akira
Middle name
Last name	Sato

Organization

Kyoto University School of Medicine

Division name

Department of Health Promotion and Human Behavior

Zip code

606-8501

Address

Yoshida Konoe-cho, Sakyo-ku, Kyoto

TEL

080-3475-7068

Homepage URL

Email

sato.akira.57m@st.kyoto-u.ac.jp

Institute

Department of Health Promotion and Human Behavior, Kyoto University School of Medicine

Institute

Department

Personal name

Organization

self-funding

Organization

Division

Category of Funding Organization

Self funding

Nationality of Funding Organization

Co-sponsor

Isogaya Hospital
Urawa Shinkei Sanatorium
Chiba Psychiatric Medical Centre
Tsukuba University

(We did not recruit participants at Wakamiya Hospital and Iwate Prefecture Nanko Hospital. Sep/13/2023)

Name of secondary funder(s)

Organization

Kyoto University Graduate School and Faculty of Medicine, Ethics Committee

Address

Yoshida-Konoe-cho, Sakyo-ku, Kyoto

Tel

075-753-4680

Email

ethcom@kuhp.kyoto-u.ac.jp

Secondary IDs

NO

Study ID_1

Org. issuing International ID_1

Study ID_2

Org. issuing International ID_2

IND to MHLW

Institutions

医療法人直樹会　磯ヶ谷病院(千葉県)、岩手県立南光病院(岩手県)、医療法人白翔会　浦和神経サナトリウム(埼玉県)、千葉県精神科医療センター(千葉県)、筑波大学(茨城県）、医療法人公徳会　若宮病院(山形県)

Date of disclosure of the study information

2021

Year

02

Month

20

Day

URL releasing protocol

https://doi.org/10.1186/s41512-022-00134-w

Publication of results

Published

URL related to results and publications

https://doi.org/10.3389/fpsyt.2023.1242918

Number of participants that the trial has enrolled

805

Results

The significant predictors were the number of previous hospitalizations (HR 1.42, 95% CI 1.22-1.64) and the current length of stay in days (HR 1.31, 95% CI 1.04-1.64). In model development for relapse, Harrells c-index was 0.59 (95% CI 0.55-0.63). The internal and internal-external validation for rehospitalization showed Harrells c-index to be 0.64 (95% CI 0.59-0.69) and 0.66 (95% CI 0.57-0.74), respectively. The calibration plot was found to be adequate

Results date posted

2023

Year

09

Month

13

Day

Results Delayed

Results Delay Reason

Date of the first journal publication of results

Baseline Characteristics

Participant flow

Adverse events

Outcome measures

Plan to share IPD

IPD sharing Plan description

Recruitment status

Main results already published

Date of protocol fixation

2020

Year

12

Month

15

Day

Date of IRB

2020

Year

12

Month

21

Day

Anticipated trial start date

2020

Year

12

Month

22

Day

Last follow-up date

2023

Year

05

Month

08

Day

Date of closure to data entry

Date trial data considered complete

Date analysis concluded

Other related information

Participants who discharged between 1 January 2014 and 31 December 2018 will be consecutively included in accordance with the eligibility criteria.

In order to pre-specify predictors from previous studies, we searched Ovid Medline on 3 September 2020. From 3490 records that were initially identified, 189 articles were included. By counting the numbers of predictors in the articles, the most common 8 predictors were pre-selected, along with other four predictors that were thought to be clinically important. Pre-selected predictors that will be collected by chart review are:

- Age at discharge
- Sex
- Past psychiatric hospitalisations
- Psychiatric hospitalisation last year
- Current length of stay
- Substance use disorder
- Psychosocial interventions
- Use of long acting injections
- Metabolic syndrome
- Body-mass index (BMI)
- Current smoking
- Receipt of beneficiary.

Missing data will be imputed by multiple imputation.

Statistical analyses will be performed with R. Multivariable regression analyses will be conducted, and estimated coefficients for each predictor will be penalised using shrinkage methods such as LASSO to avoid overfitting. Model's discrimination and calibration abilities will be evaluated. Internal validity and internal-external validity will be evaluated using, for example, leave-one-patient-out cross-validation and leave-one-site-out cross-validation, respectively. Modelling with machine learning such as random forest will also be evaluated for exploratory purposes.

In a subgroup analysis, a model will be developed using data from those with diagnosis of schizophrenia only, and as a sensitivity analysis, several models with varying conditions including how to treat missing data will be compared to assess the robustness of the original model.

Web application will be implemented with Shiny package in R to visually present the model.

The study will be reported in accordance with the TRIPOD recommendations.

Registered date

2021

Year

02

Month

16

Day

Last modified on

2023

Year

09

Month

13

Day

Link to view the page

Value
https://center6.umin.ac.jp/cgi-open-bin/ctr_e/ctr_view.cgi?recptno=R000049467