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Suicide Risk Prediction in Cancer Patients

NCT ID: NCT06167720

Last Updated: 2023-12-15

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

COMPLETED

Total Enrollment

176000 participants

Study Classification

OBSERVATIONAL

Study Start Date

1979-01-01

Study Completion Date

2021-12-31

Brief Summary

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Previous studies have found that the suicide risk of cancer patients is influenced by socioeconomic factors, clinical characteristics, and environmental factors. But prediction model with multiple predictors for suicide risk in cancer patients is limited.

The aim of this study is to assess the association of socioeconomic factors, clinical characteristics and meteorological factors with cancer patients' suicide, based on retrospective cohorts, and to establish a suicide risk prediction model with multiple predictors for cancer patients.

Detailed Description

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Cancer is a serious public health concern, with almost 10 million people dying from cancer in 2020. Previous studies have reported that cancer patients are more likely to die by suicide than the general public, especially in the six months to one year following cancer diagnosis. Since suicide is a result of the interaction of various factors such as socioeconomic factors, clinical characteristics, and environmental factors, it is necessary to construct a multivariate prediction model to predict the suicide risk in cancer patients.

A retrospective cohort of cancer patients based on the Surveillance, Epidemiology, and End Results (SEER) program database was used to assess the association of socioeconomic factors, clinical characteristics and meteorological factors with cancer patients' suicide, and to establish prediction model with multiple predictors for cancer patients. Another retrospective cohort conducted from Shandong Multi-Center Healthcare Big Data Platform (SMCHBDP) was used to verify the predictive ability and generalization ability of the prediction model.

Conditions

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Cancer

Keywords

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Cancer patients Suicide risk Prediction model Meteorological factors

Study Design

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Observational Model Type

COHORT

Study Time Perspective

RETROSPECTIVE

Study Groups

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Cancer patients cohort in SEER database

A retrospective cohort of cancer patients based on the Surveillance, Epidemiology, and End Results (SEER) program database was used to assess the association of socioeconomic factors, clinical characteristics and meteorological factors with cancer patients' suicide, and to establish prediction model with multiple predictors for cancer patient

No interventions assigned to this group

Cancer patients cohort in SMCHBDP

Retrospective cohort conducted from Shandong Multi-Center Healthcare Big Data Platform (SMCHBDP) was used to verify the predictive ability and generalization ability of the prediction model.

No interventions assigned to this group

Eligibility Criteria

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Inclusion Criteria

1\. Cancer patients in SEER database and SMCHBDP

Exclusion Criteria

1. No certain cause of death
2. Missing area code
3. Lost to follow-up
Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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Fang Tang

OTHER

Sponsor Role lead

Responsible Party

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Fang Tang

Doctor

Responsibility Role SPONSOR_INVESTIGATOR

Principal Investigators

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Fang Tang, Doctor

Role: PRINCIPAL_INVESTIGATOR

The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital

Locations

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The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital

Jinan, Shandong, China

Site Status

Countries

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China

Other Identifiers

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YXLL-KY-2023(139)

Identifier Type: -

Identifier Source: org_study_id