血液病预测模型的现状:令人担忧的评估
Xichao Wang1,2, Ke Zhang1, Lei Wang3
1Department of Biostatistics, School of Public Health, Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, MOE Key Laboratory of Geriatric Diseases and Immunology, Suzhou Medical College of Soochow University, Suzhou, Jiangsu.
Current opinion in hematology
|February 12, 2025
概括
血液学疾病的预测模型经常使用次优方法. 改善开发和验证这些模型的统计实践对于准确的诊断和治疗规划至关重要.
科学领域:
- 血液学 血液学 血液学
- 生物统计学 生物统计学
- 医疗信息学 医疗信息学
背景情况:
- 缺少血液学疾病的最佳治疗方法.
- 越来越需要准确的预测模型来诊断,治疗和患者的生活规划.
研究的目的:
- 讨论血液学预测模型的现状.
- 突出非最佳研究方法和统计实践的普遍性.
主要方法:
- 对100项关于血液学预测模型的研究进行了审查.
- 提出了用于开发和验证预测模型的统计考虑因素.
主要成果:
- 一些令人担忧的研究显示样本规模不足和模型评估不足.
- 确定了可疑的统计实践,包括缺乏必要的报告.
- 审查发现需要在模型开发和验证中提高统计学严谨性.
结论:
- 作者,评论员和编辑必须意识到基本的统计考虑.
- 在所有预测模型研究中加强统计标准是必要的.
- 改进的统计实践将提高血液学预测模型的评估和临床实用性.
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