The complete blood count (CBC) performed by automated hematology analyzers is one of the most ordered laboratory tests. It is a first-line tool for assessing a patient's general health status, or diagnosing and monitoring disease progression. When the analysis does not fit an expected setting, technologists manually review a blood smear using a microscope. The International Consensus Group for Hematology Review published in 2005 a set of criteria for reviewing CBCs. Commonly, adjustments are locally needed to account for laboratory resources and populations characteristics. Our objective is to provide a decision support tool to identify which CBC variables are associated with higher risks of abnormal smear and at which cutoff values. We propose a cost-sensitive Lasso-penalized additive logistic regression combined with stability selection. Using simulated and real CBC data, we demonstrate that our tool correctly identify the true cutoff values, provided that there is enough available data in their neighbourhood.
翻译:由自动血液分析师进行的完整的血清计数(CBC)是最有序的实验室测试之一,是评估病人一般健康状况或诊断和监测疾病进展的第一线工具。当分析不符合预期环境时,技术专家用显微镜人工检查血清。国际血清审查共识小组于2005年公布了一套审查血清计数的标准。通常,当地需要作出调整,以考虑到实验室资源和人口特点。我们的目标是提供一个决定支持工具,以确定哪些CBC变量与异常涂片的高风险有关,哪些是截断值。我们提出一个成本敏感的Lasso-Penal化添加式后勤回归,同时选择稳定性。我们使用模拟和真实的 CBC数据,证明我们的工具正确识别了真正的截断值,只要他们周围有足够的数据。