Suicide Risk in Borderline Personality Disorder: a Machine Learning Tool based on Clinical and MRI Data

Borderline Personality Disorder (BPD) is a complex mental condition. Individuals with BPD have an average of three lifetime suicide attempts, and 10% of them die by suicide. Understanding risk factors linked to suicidal behaviors is crucial for effective intervention strategies. In recent years, machine learning (ML) approaches for predicting suicide risk in persons with mental disorders have been developed, but a reliable, BPD-specific tool is lacking. In this work, we developed DRAMA-BPD (Detecting Risk factors for suicide Attempts with Machine learning Approaches in Borderline Personality Disorder), a second-opinion tool to assess suicide risk in individuals with BPD. DRAMA-BPD, built upon a Support Vector Machine (SVM) classifier, is trained on the CLIMAMITHE (CLM) dataset, which encompasses sociodemographic, clinical, emotional assessments, and MRI data. Feature selection revealed that 6 out of the 7 most important features are MRI-derived, and a comprehensive review was conducted to ensure consistency with existing scientific literature. The classifier achieved an overall Area Under the Curve (AUC) of 0.73, Precision (P) of 0.75, Recall (R) of 0.70, and F1-score of 0.72. Tests were conducted on the independent SUDMEX_CONN dataset, yielding an AUC of 0.59, P of 0.46, R of 0.92, and F1 of 0.62. While there is a significant imbalance between Precision and Recall, these results demonstrate the potential utility of the proposed model. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement The trial CLIMAMITHE was funded by the Italian Ministry of Health (GR-2011-02351347); Roberta Rossi, Michela Pievani, and Michela Pievani were supportedand partially by the Italian Ministry of Health (Ricerca Corrente - Utilizzo di strumenti di Intelligenza Artificiale (AI) per l'analisi dei disturbi psichici) ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: Ethics committee of IRCCS Centro San Giovanni di Dio Fatebenefratelli gave ethical approval for this work (67/2014) I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes All data produced in the present study are available upon reasonable request to the authors