通过整合环境社会经济和卫生系统预测因素,为伊朗甲状腺癌流行病学提供先进的机器学习框架
Mohsen Soleimani1, Hossein Chiti2
1Metabolic Diseases Research Center, Health and Metabolic Diseases Research Institute, Zanjan University of Medical Sciences, Zanjan, Iran. mo_soleimani@zums.ac.ir.
Scientific reports
|August 15, 2025
概括
在伊朗,甲状腺癌的发病率因省份和性别而异. 机器学习确定了阳光持续时间,教育,海拔,实验室可用性和婚姻率作为关键预测因素,突出了环境和社会经济影响.
科学领域:
- 瘤学和公共卫生
- 环境流行病学环境流行病学
- 健康的社会经济决定因素
背景情况:
- 全球甲状腺癌 (TC) 发病率的上升是一个重大的公共卫生挑战.
- 伊朗在TC发病率方面表现出明显的省级和基于性别的差异,需要进行深入分析.
- 现有的研究缺乏对影响TC的环境,社会经济和医疗保健因素的综合分析.
研究的目的:
- 采用多模型机器学习 (ML) 框架来识别伊朗TC发病率的时间空间决定因素.
- 阐明气候,社会经济,医疗保健和环境因素对TC发病率的影响.
- 通过揭示区域和性别特异性风险概况,为基于证据的公共卫生战略提供信息.
主要方法:
- 利用了来自伊朗国家基于人口的癌症登记 (INPCR) (2014-2017) 的数据和来自公共存储库的55个变量.
- 计算的年龄标准化发病率 (ASR),按性别和省份分层.
- 应用了9个ML模型用于特征选择和SHAP分析用于预测器验证.
主要成果:
- 总体而言,四年ASR为每10万人口中的11.13,女性 (35.1/100,000) 显著高于男性 (9.6/100,000).
- 关键预测因素包括阳光持续时间,省级教育率,海拔,实验室可用性和社区婚姻率.
- 展示了显著的省级差异 (例如,Yazd与Semnan) 和中等到强大的ML模型预测准确性 (R2:0.21-0.86).
结论:
- 开创性的研究揭示了气候,社会经济,医疗保健和环境因素在伊朗TC发病率中的关键作用.
- 揭示了TC风险概况的显著区域和性别特异性差异.
- 倡导有针对性的公共卫生干预措施,以减轻环境暴露和医疗保健差异,以有效预防TC.
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