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标准化预测值、准确性和误诊率的新概念与方法。

New concepts and methods of standardizing predictive value, accuracy and incorrect diagnostic rate.

作者信息

Shen H, Chen Q

机构信息

Department of Pathology, First Military Medical University, Guangzhou, People's Republic of China.

出版信息

Anal Quant Cytol Histol. 2000 Feb;22(1):76-9.

Abstract

OBJECTIVE

To express the value of a diagnostic test under standardized and comparable conditions.

STUDY DESIGN

Four new concepts of standardizing positive predictive value (SPPV), standardizing negative predictive value (SNPV), standardizing accuracy (SAc) and standardizing an incorrect diagnostic test were developed. The theoretical positive predictive value (SPPV), theoretical negative predictive value (SNPV), theoretical accuracy (SAc) and theoretical incorrect diagnosis rate (SIDR), which are not affected by a different constituent ratio of disease and nondisease groups and are obtained under the theoretical standard condition that the sample size in the disease group equals that in the nondisease group, were defined. Based on these concepts and the principles and methods of statistics and evaluation of diagnostic tests, corresponding formulas were deduced.

RESULTS

The formulas are: SPPV = a(b + d)/[a(b + d) + b(a + c)] = Se/(1 + Se - Sp), SNPV = d(a + c)/[c(b + d) + d(a + c)] = Sp/(1 - Se + Sp), SAc = [a(b + d) + d(a + c)]/[2(a + c)(b + d)] = (Se + Sp)/2, and SIDR = [b(a + c) + c(b + d)]/[2(a + c)(b + d)] = (2 - Se - Sp)/2. Here, a, b, c and d refer to the case numbers of true positives, false positives, false negatives and true negatives; Se and Sp refer, respectively, to sensitivity and specificity.

CONCLUSION

SPPV, SNPV, SAc and SIDR are very useful for expressing and evaluating the value of a diagnostic test under standardized and comparable conditions.

摘要

目的

在标准化和可比较的条件下表达诊断试验的价值。

研究设计

提出了标准化阳性预测值(SPPV)、标准化阴性预测值(SNPV)、标准化准确度(SAc)和标准化错误诊断试验的四个新概念。定义了理论阳性预测值(SPPV)、理论阴性预测值(SNPV)、理论准确度(SAc)和理论错误诊断率(SIDR),它们不受疾病组和非疾病组不同构成比的影响,是在疾病组样本量等于非疾病组样本量的理论标准条件下获得的。基于这些概念以及统计和诊断试验评价的原理和方法,推导了相应的公式。

结果

公式为:SPPV = a(b + d)/[a(b + d) + b(a + c)] = Se/(1 + Se - Sp),SNPV = d(a + c)/[c(b + d) + d(a + c)] = Sp/(1 - Se + Sp),SAc = [a(b + d) + d(a + c)]/[2(a + c)(b + d)] = (Se + Sp)/2,SIDR = [b(a + c) + c(b + d)]/[2(a + c)(b + d)] = (2 - Se - Sp)/2。这里,a、b、c和d分别指真阳性、假阳性、假阴性和真阴性的病例数;Se和Sp分别指敏感度和特异度。

结论

SPPV、SNPV、SAc和SIDR对于在标准化和可比较的条件下表达和评价诊断试验的价值非常有用。

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