Huang Shu, Lewis Motomori O, Bao Yuhua, Adekkanattu Prakash, Adkins Lauren E, Banerjee Samprit, Bian Jiang, Gellad Walid F, Goodin Amie J, Luo Yuan, Fairless Jill A, Walunas Theresa L, Wilson Debbie L, Wu Yonghui, Yin Pengfei, Oslin David W, Pathak Jyotishman, Lo-Ciganic Wei-Hsuan
Department of Pharmaceutical Outcomes and Policy, College of Pharmacy, University of Florida, Gainesville, FL 32610, USA.
Department of Population Health Sciences, Weill Cornell Medicine, New York, NY 10065, USA.
J Clin Med. 2022 Aug 17;11(16):4813. doi: 10.3390/jcm11164813.
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 ( = 3 studies) ranged 0.67-0.84, overall accuracy( = 5): 0.78-0.96, sensitivity( = 2): 0.65-0.91, and positive predictive values( = 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.
自杀是美国主要的死因之一。患有疼痛病症的患者自杀风险更高。在一项系统性综述中，我们检索了2000年1月1日至2020年9月12日来自多个来源（如医学期刊数据库）的观察性研究，评估了现有自杀预测模型（SPM）的性能，并确定了疼痛病症患者中的风险因素及其衍生数据源。与自杀相关的结果包括自杀意念、自杀未遂、自杀死亡和自杀行为。在纳入的87项研究（其中8项为SPM研究）中，确定了107个自杀风险因素（分为27类）。最常出现的风险因素类别是抑郁及其严重程度（33%）。约20%的风险因素类别需要从结构化数据（如临床记录）以外的数据源中识别。对于8项SPM研究（只有2项进行了验证），报告的预测指标/性能各不相同：C统计量（=3项研究）范围为0.67 - 0.84，总体准确率（=5项）：0.78 - 0.96，敏感性（=2项）：0.65 - 0.91，以及阳性预测值（=3项）：0.01 - 0.43。使用改良的预后来研究质量工具评估偏倚风险，4项SPM研究存在中度至高度偏倚风险。这项系统性综述确定了一份全面的风险因素清单，可能有助于改善对疼痛病症患者自杀风险的预测。未来的研究需要考察性能差异的原因以及SPM的临床实用性。
