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使用ROC近似法进行与截断值无关的肿瘤标志物评估。

Cut-off-independent tumour marker evaluation using ROC approximation.

作者信息

Bitterlich Norman, Schneider Joachim

机构信息

Medizin und Service GmbH, Zwickauer Str. 227, D-09116 Chemnitz, Germany.

出版信息

Anticancer Res. 2007 Nov-Dec;27(6C):4305-10.

Abstract

BACKGROUND

The analysis of tumour markers is based on the evaluation of data in relation to defined cut-off values. Changes in the method of determination or reference study group have led to different results. Cut-off-independent diagnostic evaluation of laboratory parameters can avoid laboratory-based and method-derived systematic errors. The decision guarantee (DG) is an appropriate parameter that can be determined using a defined reference population and its respective receiver operating characteristic (ROC) curve. The influence of ROC differences on the determination of DG is examined.

PATIENTS AND METHODS

A group of 281 consecutive patients with newly diagnosed, histologically confirmed lung cancer and a control group of 231 patients were examined. Histological classification of the tumour cases defined in 59 small-cell carcinoma, 102 squamous cell carcinomas, 66 adenocarcinomas and 54 large-cell carcinomas or mixed bronchial carcinomas without classification. The control group without tumours consisted of 23 healthy subjects, 125 patients with silicosis or asbestosis, 27 with chronic obstructive pulmonary diseases (COPD) and 56 suffering from inflammatory lung diseases.

RESULTS

Cytokeratin-19 fragments (CYFRA 21-1) was the most sensitive marker with a sensitivity of 57.3% and a specificity of 94.9%. Sensitivity and specificity influence each other. Related to the ROC curve, the method described here ensured the diagnosis of lung cancer on the basis of the data collected in comparison with a reference population. Thus, it was possible to determine with statistical certainty whether the evaluation of the sample data would lead to a diagnosis of lung cancer.

CONCLUSION

The DG provides the basis for a laboratory-and method-independent support for a diagnosis including fairer information about the reference population in the data analysis.

摘要

背景

肿瘤标志物的分析基于与确定的临界值相关的数据评估。测定方法或参考研究组的变化导致了不同的结果。实验室参数的非临界值诊断评估可避免基于实验室和方法产生的系统误差。决策保证(DG)是一个合适的参数,可使用定义的参考人群及其相应的受试者工作特征(ROC)曲线来确定。研究了ROC差异对DG测定的影响。

患者和方法

对一组281例新诊断、经组织学证实的肺癌患者和231例对照组患者进行了检查。肿瘤病例的组织学分类包括59例小细胞癌、102例鳞状细胞癌、6例腺癌和54例大细胞癌或未分类的混合支气管癌。无肿瘤的对照组包括23名健康受试者、125例矽肺或石棉肺患者、27例慢性阻塞性肺疾病(COPD)患者和56例患有炎症性肺病的患者。

结果

细胞角蛋白19片段(CYFRA 21-1)是最敏感的标志物,敏感性为57.3%,特异性为94.9%。敏感性和特异性相互影响。与ROC曲线相关,此处描述的方法可根据与参考人群相比收集的数据确保肺癌的诊断。因此,可以通过统计确定性确定样本数据的评估是否会导致肺癌诊断。

结论

DG为诊断提供了独立于实验室和方法的支持基础,包括在数据分析中提供关于参考人群更公平的信息。

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