法医学杂志

法医学杂志 ›› 2024, Vol. 40 ›› Issue (6): 582-588.DOI: 10.12116/j.issn.1004-5619.2023.431005

• 论著 • 上一篇    下一篇

亲密伴侣杀人案预测模型构建与评价

吕伟平1(), 廖信彪2, 任李聚3, 孔小平3, 陈燕嫦4, 常亚斐4, 罗斌4()   

  1. 1.新兴县公安局，广东 新兴 527400
    2.广东省公安厅刑事技术中心 法医病理学公安部重点实验室，广东 广州 510000
    3.广州市公安局番禺分局，广东 广州 510080
    4.中山大学法医鉴定中心，广东 广州 510080
  • 收稿日期:2023-10-26 发布日期:2025-03-10 出版日期:2024-12-25
  • 通讯作者: 罗斌
  • 作者简介:吕伟平（1984—），男，硕士，警务技术副高级任职资格，主要从事法医病理学、法医临床学、法医现场学科研及检案；E-mail：261431316@qq.com
  • 基金资助:
    广东省刑事技术“双十计划”资助项目(2022GDSSGG05);国家自然科学基金资助项目(81671866);广东省自然科学基金资助项目(2016A030313223)

Construction and Evaluation of Intimate Partner Homicide Prediction Model

Wei-ping LÜ1(), Xin-biao LIAO2, Li-ju REN3, Xiao-ping KONG3, Yan-chang CHEN4, Ya-fei CHANG4, Bin LUO4()   

  1. 1.Xinxing Public Security Bureau, Xinxing 527400, Guangdong Province, China
    2.Key Laboratory of Forensic Pathology, Ministry of Public Security, PRC, Guangdong Forensic Science Institute, Guangzhou 510000, China
    3.Panyu Branch of Guangzhou Public Security Bureau, Guangzhou 510080, China
    4.Forensic Medicine Center, Sun Yat-sen University, Guangzhou 510080, China
  • Received:2023-10-26 Online:2025-03-10 Published:2024-12-25
  • Contact: Bin LUO

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摘要：

目的 分析亲密伴侣杀人（intimate partner homicide，IPH）案的独立影响因素，构建IPH预测模型，为案犯刻画提供依据。 方法 收集广东省2014年1月1日—2020年12月31日法院已判决命案资料共476例作为建模数据，根据案犯与被害人是否为亲密伴侣将案例分为IPH组（n=180）和非亲密伴侣杀人（non-intimate partner homicide，N-IPH）组（n=296）。采用Logistic回归构建模型，通过受试者操作特征（receiver operating characteristic，ROC）曲线分析对模型进行评价并绘制列线图。采用十折交叉验证法进行内部验证。随机收集国内非广东省2011年1月1日—2020年12月31日的法院判决书126例进行外部验证。 结果 通过多因素Logistic回归分析，最终筛选出7个变量纳入模型。模型Hosmer-Lemeshow拟合优度检验结果为χ2 =13.158，P=0.068。ROC曲线下面积（area under the curve，AUC）为0.939（95% CI：0.919~0.959），cut-off值为0.292，敏感度为0.900，特异度为0.865，校准曲线在理想曲线附近。十折交叉验证结果显示准确率为0.863，Kappa值为0.708，外部验证结果显示AUC为0.922（95% CI：0.872~0.971），cut-off值为0.292，敏感度为0.890，特异度为0.886，校准曲线趋于理想曲线。 结论 基于法医现场学指标构建的IPH模型预测能力良好，准确性和稳定性可靠，可为案犯刻画提供科学方法。

关键词: 法医病理学, 亲密伴侣杀人, 预测模型, 案犯刻画

Abstract:

Objective To analyze the independent influencing factors of intimate partner homicide （IPH） cases, construct an IPH prediction model, and provide a basis for criminal profiling. Methods A total of 476 convicted homicide cases in Guangdong Province from January 1, 2014, to December 31, 2020, were collected as modeling dataset. They were divided into the IPH group （n=180） and the non-intimate partner homicide （N-IPH） group （n=296） based on whether the offender and victim were intimate partners. Logistic regression was used to build the model, the model was evaluated through the receiver operating characteristic （ROC） curve analysis and a nomogram was drawn. Internal validation was conducted using ten-fold cross-validation method. A total of 126 court judgments from outside Guangdong Province from January 1, 2011, to December 31, 2020, were randomly collected for external validation. Results Through multi-factor Logistic regression analysis, 7 variables were ultimately selected for inclusion in the model. The Hosmer-Lemeshow goodness of fit test result of the model was χ2=13.158, P=0.068. The ROC area under the curve （AUC） of the model was 0.939 （95% CI: 0.919-0.959）, the cut-off value was 0.292, the sensitivity was 0.900, and the specificity was 0.865. The calibration curve was close to the ideal curve. The ten-fold cross-validation showed the accuracy of 0.863 and a Kappa value of 0.708. The external validation results showed an AUC of 0.922 （95% CI: 0.872-0.971）, a cut-off value of 0.292, a sensitivity of 0.890, and a specificity of 0.886. The calibration curve tended to the ideal curve. Conclusion The IPH prediction model based on forensic field indicators has good predictive ability, reliable accuracy and stability, and can provide a scientific method for criminal profiling.

Key words: forensic pathology, intimate partner homicide, prediction model, criminal profiling

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