AUTHOR=Liang Sixiang , Liu Xinyu , Li Dan , Zhang Jinhe , Zhao Guangwei , Yu Hongye , Zhao Xixi , Sha Sha 

TITLE=Development and validation of a nomogram to predict suicidal behavior in female patients with mood disorder

JOURNAL=Frontiers in Psychiatry

VOLUME=14

YEAR=2023

URL=https://www.frontiersin.org/journals/psychiatry/articles/10.3389/fpsyt.2023.1212579

DOI=10.3389/fpsyt.2023.1212579

ISSN=1664-0640

ABSTRACT=<sec id="sec1"><title>Introduction</title><p>This study aims to explore the risk factors associated with suicidal behavior and establish predictive models in female patients with mood disorders, specifically using a nomogram of the least absolute shrinkage and selection operator (LASSO) regression.</p></sec><sec id="sec2"><title>Methods</title><p>A cross-sectional survey was conducted among 396 female individuals diagnosed with mood disorders (F30-F39) according to the International Classification of Diseases and Related Health Problems 10th Revision (ICD-10). The study utilized the Chi-Squared Test, <italic>t</italic>-test, and the Wilcoxon Rank-Sum Test to assess differences in demographic information and clinical characteristics between the two groups. Logistic LASSO Regression Analyses were utilized to identify the risk factors associated with suicidal behavior. A nomogram was constructed to develop a prediction model. The accuracy of the prediction model was evaluated using a Receiver Operating Characteristic (ROC) curve.</p></sec><sec id="sec3"><title>Result</title><p>The LASSO regression analysis showed that psychotic symptoms at first-episode (<italic>β</italic> = 0.27), social dysfunction (<italic>β</italic> = 1.82), and somatic disease (<italic>β</italic> = 1.03) increased the risk of suicidal behavior. Conversely, BMI (<italic>β</italic> = −0.03), age of onset (<italic>β</italic> = −0.02), polarity at onset (<italic>β</italic> = −1.21), and number of hospitalizations (<italic>β</italic> = −0.18) decreased the risk of suicidal behavior. The area under ROC curve (AUC) of the nomogram predicting SB was 0.778 (95%CI: 0.730–0.827, <italic>p</italic> &lt; 0.001).</p></sec><sec id="sec4"><title>Conclusion</title><p>The nomogram based on demographic and clinical characteristics can predict suicidal behavior risk in Chinese female patients with mood disorders.</p></sec>