Predictive Modeling for Suicide-Related Outcomes and Risk Factors among Patients with Pain Conditions: A Systematic Review

Shu Huang, Motomori O. Lewis, Yuhua Bao, Prakash Adekkanattu, Lauren E. Adkins, Samprit Banerjee, Jiang Bian, Walid F. Gellad, Amie J. Goodin, Yuan Luo, Jill A. Fairless, Theresa L. Walunas, Debbie L. Wilson, Yonghui Wu, Pengfei Yin, David W. Oslin, Jyotishman Pathak, Wei Hsuan Lo-Ciganic*

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

3 Scopus citations

Abstract

Suicide is a leading cause of death in the US. Patients with pain conditions have higher suicidal risks. In a systematic review searching observational studies from multiple sources (e.g., MEDLINE) from 1 January 2000–12 September 2020, we evaluated existing suicide prediction models’ (SPMs) performance and identified risk factors and their derived data sources among patients with pain conditions. The suicide-related outcomes included suicidal ideation, suicide attempts, suicide deaths, and suicide behaviors. Among the 87 studies included (with 8 SPM studies), 107 suicide risk factors (grouped into 27 categories) were identified. The most frequently occurring risk factor category was depression and their severity (33%). Approximately 20% of the risk factor categories would require identification from data sources beyond structured data (e.g., clinical notes). For 8 SPM studies (only 2 performing validation), the reported prediction metrics/performance varied: C-statistics (n = 3 studies) ranged 0.67–0.84, overall accuracy(n = 5): 0.78–0.96, sensitivity(n = 2): 0.65–0.91, and positive predictive values(n = 3): 0.01–0.43. Using the modified Quality in Prognosis Studies tool to assess the risk of biases, four SPM studies had moderate-to-high risk of biases. This systematic review identified a comprehensive list of risk factors that may improve predicting suicidal risks for patients with pain conditions. Future studies need to examine reasons for performance variations and SPM’s clinical utility.

Original languageEnglish (US)
Article number4813
JournalJournal of Clinical Medicine
Volume11
Issue number16
DOIs
StatePublished - Aug 2022

Keywords

  • pain conditions
  • predictive modeling
  • suicide-related outcomes

ASJC Scopus subject areas

  • General Medicine

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