Evidence map›Paper›PMID 39556133›Full record

ArticleEuropean child & adolescent psychiatry2025

A nomogram for predicting non-suicide self-injury in youth depression patients: a longitudinal analysis.

Yingwen Li, Yarong Ma, Bin Sun, Robert Rosenheck, Jie Zhang, Hongbo He

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Article in European child & adolescent psychiatry, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

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6citing papers in PubMed
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1 · What the graph read from it

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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.

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3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Yingwen LiThe Affiliated Brain Hospital, Guangzhou Medical University, Guangzhou, China.
Yarong MaThe Affiliated Brain Hospital, Guangzhou Medical University, Guangzhou, China.
Bin SunThe Affiliated Brain Hospital, Guangzhou Medical University, Guangzhou, China.
Robert RosenheckDepartment of Psychiatry, Yale School of Medicine, New Haven, CT, USA.
Jie ZhangThe Affiliated Brain Hospital, Guangzhou Medical University, Guangzhou, China.
Hongbo HeGuangdong Mental Health Center, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, 510030, China. hongbo_he@gzhmu.edu.cn.ORCID http://orcid.org/0000-0002-9595-8603

Funding

Guangzhou Municipal Science and Technology Bureau 202206010090Guangzhou Municipal Science and Technology Project 2022A031003
6 · The paper itself

Abstract

Non-suicidal self-injury (NSSI) behavior is a common issue in youth with depression while lacks a prognostic prediction model. This study aims to develop a nomogram for NSSI in youth with depression. A total of 701 patients were included in the analysis based a youth depression cohort. They were further divided into a training set and a validation set. The Lasso regression and binary logistic regression were used to select variables for the nomogram. The nomogram's discrimination, calibration, accuracy, clinical applicability, and generalization involved the use of metrics such as the area under the receiver operating characteristic curve (ROC), Hosmer-Lemeshow (HL) test, Brier score, calibration curve, decision curve analysis (DCA), and internal validation. The Delong test was employed to compare the ROC performance between the two models. These patients had an average age of 19.3+/-3.3 years, and 101 (20.6%) individuals reported NSSI. Five risk factors for NSSI were identified: age, age at first medication, previous instances of NSSI, academic stress score in the Adolescent Self-rating Life Events Check List (ASLEC), and somatic anxiety of the 14 item Hamilton Anxiety Rating Scale (HAMA-14). The training set and validation set of binary logistic regression-based model showed good discrimination (area under the curve (AUC) 0.781, 95% CI: 0.735 ~ 0.827; and 0.757, 95% CI: 0.682 ~ 0.831, respectively), calibration (P = 0.421 and 0.175, respectively), and accuracy (Brier score 0.119 to 0.155 and 0.109 to 0.168, respectively). A prognostic nomogram was developed and validated to assist clinicians in predicting NSSI of youth with depression.

Indexed as

Depressive DisorderNomogramsSelf-Injurious BehaviorAdolescentFemaleHumansLogistic ModelsLongitudinal StudiesMaleRisk FactorsROC CurveYoung AdultNomogramNon-suicidal self-injuryPredicting modelYouth depression

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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.