A novel approach for selecting combination clinical markers of pathology applied to a large retrospective cohort of surgically resected pancreatic cysts
A novel approach for selecting combination clinical markers of pathology applied to a large retrospective cohort of surgically resected pancreatic cysts
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DOI：
10.1093/jamia/ocw069
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发表时间：
2017-01-01
影响因子：
6.4
通讯作者：
Lennon, Anne Marie
中科院分区：
文献类型：
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作者：
Masica, David L.;Dal Molin, Marco;Lennon, Anne Marie
目的：我们的目的是开发一种从不同临床数据类型中选择病理组合标记的方法。我们在胰腺囊肿的分类问题上展示了这种方法。材料和方法：我们分析了1026例手术切除的胰腺囊肿，包括584例导管内乳头状粘液瘤，332例浆液性囊腺瘤，78例粘液性囊性肿瘤和42例实性假乳头状肿瘤。为了从术前临床和放射学数据中获得囊肿分类的最佳标记，我们开发了一种统计方法，将任何数量的分类、二分类或连续值临床参数结合到单个病理预测因子中。这种方法是公正的，在统计上是严谨的。使用10倍交叉验证测试了数百万个特征组合，并在130例手术切除胰腺囊肿患者的独立队列中验证了最具信息量的特征。结果：我们确定了分类浆液性囊腺瘤的组合临床标志物，敏感性为95%，特异性为83%；实体假乳头状肿瘤，敏感性89%，特异性86%；粘液囊性肿瘤的敏感性为91%，特异性为83%；导管内乳头状粘液瘤的敏感性为94%特异性为90%。没有任何一个单独的特征像组合标记那样准确。我们在130个胰腺囊肿的独立队列中进一步验证了这些组合标记，并获得了高且平衡的准确性。识别需要手术切除的患者的总体敏感性和特异性分别为84%和81%。结论：我们的方法确定了胰腺囊肿分类的组合标记物，相对于它们所包含的个体特征，这些标记物的表现有所改善。原则上，这种方法可以应用于任何包含二分类、分类和连续值参数的临床数据集。
Objective: Our objective was to develop an approach for selecting combinatorial markers of pathology from diverse clinical data types. We demonstrate this approach on the problem of pancreatic cyst classification.Materials and Methods: We analyzed 1026 patients with surgically resected pancreatic cysts, comprising 584 intraductal papillary mucinous neoplasms, 332 serous cystadenomas, 78 mucinous cystic neoplasms, and 42 solid-pseudopapillary neoplasms. To derive optimal markers for cyst classification from the preoperative clinical and radiological data, we developed a statistical approach for combining any number of categorical, dichotomous, or continuous-valued clinical parameters into individual predictors of pathology. The approach is unbiased and statistically rigorous. Millions of feature combinations were tested using 10-fold cross-validation, and the most informative features were validated in an independent cohort of 130 patients with surgically resected pancreatic cysts.Results: We identified combinatorial clinical markers that classified serous cystadenomas with 95% sensitivity and 83% specificity; solid-pseudopapillary neoplasms with 89% sensitivity and 86% specificity; mucinous cystic neoplasms with 91% sensitivity and 83% specificity; and intraductal papillary mucinous neoplasms with 94% sensitivity and 90% specificity. No individual features were as accurate as the combination markers. We further validated these combinatorial markers on an independent cohort of 130 pancreatic cysts, and achieved high and well-balanced accuracies. Overall sensitivity and specificity for identifying patients requiring surgical resection was 84% and 81%, respectively.Conclusions: Our approach identified combinatorial markers for pancreatic cyst classification that had improved performance relative to the individual features they comprise. In principle, this approach can be applied to any clinical dataset comprising dichotomous, categorical, and continuous-valued parameters.