分析全球癌症控制:通过复合指标和回归建模,研究国家癌症控制计划的进展
Rohit Singh Chauhan1, Anusheel Munshi2, Anirudh Pradhan3
1Department of Physics, GLA University, Mathura, Uttar Pradesh, India.
Journal of medical physics
|August 12, 2024
概括
综合指标有效评估国家癌症控制计划 (NCCPs) 的进展情况. 这项研究表明它们在预测癌症控制结果方面的有用性,有助于全球减少癌症的努力.
科学领域:
- 公共卫生 公共卫生
- 流行病学 流行病学
- 医疗保健服务研究 医疗服务研究
背景情况:
- 癌症是一个重大的全球健康挑战,需要有效的国家癌症控制计划 (NCCPs).
- 评估NCCP的有效性是复杂的,因为多方面的结果和影响因素.
- 综合指标为全面的NCCP评估提供了一个有希望的方法.
研究的目的:
- 评估复合指标在评估国家癌症控制计划 (NCCPs) 进展中的有用性.
- 建立综合指标和关键癌症控制结果之间的关系.
- 使用复合指标开发NCCP结果的预测模型.
主要方法:
- 汇编了来自144个国家的数据,包括8个复合指数和两个比较指标:死亡率与发病率 (MIR) 和流行率与发病率 (PCIR).
- 使用线性回归分析和皮尔森相关性来检查指标-结果关系.
- 开发了一个多重回归机器学习模型来预测NCCP结果.
主要成果:
- 低收入国家表现出最高的MIR,而高收入国家患病率最高.
- 综合指标显示MIR呈负趋势,PCIR呈正趋势.
- 人类发展指数和Legatum繁荣指数分别是MIR和PCIR的强有力的预测指标.
- 机器学习模型在预测NCCP结果方面取得了高准确性 (R2=0.86).
结论:
- 综合指标是评估NCCP业绩的有价值工具.
- 开发的模型准确地预测NCCP的结果,支持癌症控制策略.
- 这些发现可以指导NCCP的开发和监测,以改善全球癌症控制.
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