Development and validation of a prediction nomogram for non-suicidal self-injury in female patients with mood disorder

Abstract

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BackgroundNon-suicidal self-injury (NSSI) is a highly prevalent behavioral problem among people with mental disorders that can result in numerous adverse outcomes. The present study aimed to systematically analyze the risk factors associated with NSSI to investigate a predictive model for female patients with mood disorders.MethodsA cross-sectional survey among 396 female patients was analyzed. All participants met the mood disorder diagnostic groups (F30–F39) based on the Diseases and Related Health Problems 10th Revision (ICD-10). The Chi-Squared Test, t-test, and the Wilcoxon Rank-Sum Test were used to assess the differences of demographic information and clinical characteristics between the two groups. Logistic LASSO Regression Analyses was then used to identify the risk factors of NSSI. A nomogram was further used to construct a prediction model.ResultsAfter LASSO regression selection, 6 variables remained significant predictors of NSSI. Psychotic symptom at first-episode (β = 0.59) and social dysfunction (β = 1.06) increased the risk of NSSI. Meanwhile, stable marital status (β = −0.48), later age of onset (β = −0.01), no depression at onset (β = −1.13), and timely hospitalizations (β = −0.10) can decrease the risk of NSSI. The C-index of the nomogram was 0.73 in the internal bootstrap validation sets, indicated that the nomogram had a good consistency.ConclusionOur findings suggest that the demographic information and clinical characteristics of NSSI can be used in a nomogram to predict the risk of NSSI in Chinese female patients with mood disorders.

Keywords

• prediction model
• mood disorder
• non-suicidal self-injury
• nomogram
• LASSO regression