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

Speaker(s)

Huang S1, Lewis M1, Bao Y2, Bian J1, Gellad WF3, Wu Y1, Pathak J2, Oslin D4, Adkins LE1, Yin P1, Sutton JA1, Goodin AJ1, Wang F2, Banerjee S2, Adekkanattu P2, Wilson DL1, Lo-Ciganic W1
1University of Florida, Gainesville, FL, USA, 2Weill Cornell Medical College, New York, NY, USA, 3University of Pittsburgh, Pittsburgh, PA, USA, 4University of Pennsylvania, Philadelphia, PA, USA

Presentation Documents

OBJECTIVES: Suicide is a leading cause of death in the United States, and patients with pain conditions are at an elevated risk. The objective of this study is to evaluate performance of existing suicide prediction models (SPMs) and identify suicide risk factors among patients with pain conditions.

METHODS: This systematic review searched MEDLINE, PsycINFO, EMBASE, SCOPUS, Cochrane Library, Web of Science, ProQuest Thesis Dissertations, and CINAHL (01/01/2000–12/09/2020). We included observational studies that developed SPMs and/or reported suicide risk factors among patients with pain conditions. We extracted key study information (e.g., identified risk factors) from included studies. For SPM studies, we also collected prediction performance metrics reported (e.g., positive predictive values [PPV]), and assessed the risk of biases using the modified Quality in Prognosis Studies (QUIPS) tool. We looked at suicide-related outcomes including suicidal ideation, suicide attempts, suicide deaths, and suicide behaviors.

RESULTS: We identified 87 studies (including 8 SPM studies) reporting a total of 107 suicide risk factors, which were grouped into 27 categories. The top three categories were: depression and its severity(33%), other patient reported factors(29%), and unspecified physical health illness(24%). Approximately 20% of the risk factor categories would require use of data sources beyond structured data (e.g., clinical notes). Among 8 SPM studies for patients with pain conditions, only 2 performed SPM validation. The prediction metrics and performance from these SPM studies varied: C-statistics(n=3 studies) ranged from 0.67 to 0.84, overall accuracy(n=5) ranged from 0.78 to 0.96, sensitivity(n=2) ranged from 0.65 to 0.91, and PPV(n=3) ranged from 0.01 to 0.43. Three SPM studies had moderate to high risk of biases.

CONCLUSIONS: Predicting suicide for patients with pain conditions may be improved with a comprehensive list of risk factors identified from this systematic review. Future studies are warranted to examine heterogeneity leading to performance variations and to evaluate its clinical utility.

Code

CO124

Topic

Clinical Outcomes, Epidemiology & Public Health, Methodological & Statistical Research, Study Approaches

Topic Subcategory

Clinician Reported Outcomes, Literature Review & Synthesis

Disease

Drugs, Injury and Trauma, Mental Health