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开发和验证用于结直肠癌诊断的后勤回归模型

Cong Li¹, Weili Zhang¹, Qichen Chen¹

¹Department of Colorectal Surgery, Sun Yat-Sen University Cancer Center, 651 East Dongfeng Road, Yuexiu District, Guangzhou, 510060, China.

Scientific reports

|April 28, 2025

概括

这项研究使用生物标志物开发了结直肠癌 (CRC) 的新诊断模型. 该模型显示出高灵敏度和特异性,有助于早期检测CRC.

科学领域:

在瘤学瘤学.
生物标志物发现发现
诊断发展诊断发展

背景情况:

结肠直肠癌 (CRC) 的诊断往往由于非特异性症状而延迟.
现有的CRC生物标志物模型具有低灵敏度和不一致的截止值,限制了临床效用.

研究的目的:

开发和验证一种新的结直肠癌 (CRC) 诊断模型.
提高基于生物标志物的CRC检测的准确性和临床适用性.

主要方法:

一组489名患者 (337名CRC,152名良性疾病) 被随机分配到培训和验证组.
使用后勤回归分析来确定独立的风险因素,包括年龄,CA153,CEA,CYFRA 21-1,费里丁和hs-CRP.
用灵敏度,特异性和曲线下的面积 (AUC) 来评估诊断性能.

主要成果:

开发的模型确定了年龄,CA153,CEA,CYFRA 21-1,费里丁和hs-CRP作为CRC的重要独立风险因素.
该模型实现了高诊断准确度,在培训队列中具有88.61%的敏感度和82.86%的特异性,在验证队列中具有90.00%的敏感度和76.60%的特异性.
值得注意的是,该模型对早期CRC (95.45%) 与晚期CRC (87.27%) 相比显示出更高的敏感性,AUC为0.907 (训练) 和0.872 (验证).

结论:

这种新的生物标志物模型为改善结直肠癌 (CRC) 诊断提供了一个有前途的工具.
该模型的高灵敏度,特别是对于早期疾病,强调了其在通过早期检测改善患者结果方面的潜在实用性.
该模型的进一步验证和临床实施可以解决CRC当前的诊断挑战.

关键词:

它们的AUC AUC.结肠直肠癌是一种癌症.早期诊断早期诊断早期诊断后勤回归的逻辑回归血清中的生物标志物

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