老年人中非黑色素瘤皮肤癌的全球负担:使用机器学习方法进行全面分析
Yumeng Pan1, Bo Tang2, Yingwu Guo1
1Department of Dermatology, The First Affiliated Hospital of Kunming Medical University, Kunming, 650032, Yunnan, China.
Scientific reports
|May 1, 2025
概括
全球非黑色素瘤皮肤癌 (NMSCs) 如基底细胞癌 (BCC) 和状细胞癌 (SCC) 显著增加,特别是在老年人和高收入地区. 预测表明,在未来,发病率将略有下降.
科学领域:
- 流行病学 流行病学
- 在瘤学瘤学.
- 公共卫生 公共卫生
背景情况:
- 非黑色素瘤皮肤癌 (NMSCs),包括基底细胞癌 (BCC) 和状细胞癌 (SCC),代表着日益增长的全球健康负担.
- 地区,性别和社会人口群体之间存在重大差异,需要全面的趋势分析.
研究的目的:
- 通过综合的多模型方法全面分析1990-2021年全球NMSC趋势.
- 用机器学习来比较不同人群中BCC和SCC的负担,并预测未来的疾病负担.
主要方法:
- 流行病学分解分析以确定发病率,流行率和残疾调整寿命年 (DALYs) 的时间趋势.
- 边界分析以评估区域差异.
- 应用和选择八个机器学习模型用于疾病负担预测 (2022-2050).
主要成果:
- 从1990年到2021年,全球BCC和SCC负担大幅增加,发病率上升了291.85% (BCC) 和322.77% (SCC).
- 高社会人口指数 (SDI) 的地区显示了最大的年龄标准化增长率,而人口增长是NMSC负担的主要驱动因素.
- 机器学习模型预测到2050年,BCC和SCC发病率略有下降,预计SCC的DALY下降,但BCC略有增加.
结论:
- 全球越来越多的NMSC负担,特别是在高SDI地区和老年人中,需要定制的预防和管理策略.
- 综合的多模型方法和机器学习为NMSC趋势和未来的挑战提供了关键的见解.
- 解决区域和社会人口差异对于有效的NMSC控制至关重要.
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