Dear Prof. Koen, Thank you very much. We really appreciate your help in resolving the problem. It’s very important for the statistical method in the diagnostic test. As your suggestion, we have to collapse Doubtful and Negative into Negative due to be "conservative" in our statistical choices. (That is, the Doubtful need to be considered as the Negative at our study). Based on this premise, we can also calculate the Specificity, PPV, NPV and other factors that combine to describe how valid a test is? But if we want to calculate the Specificity, we need to collapse Doubtful and Positive into Positive.
For example, there are 1000 people have participated in our study.
In fact, the MR examination (Method B) is considered as the gold-standard test (100 people have the disease and 900 are not the disease).
A new test named method A is 3-class classification (Positive vs Negative vs. Doubtful). 1000 people are also tested for disease by method A:
180 people have the disease (Positive), 720 people are not diseased (Negative) and 100 people are doubtful.
Moreover, in the 100 people who are doubtful by method A, 10 people have been diagnosed with disease and 90 without the disease by gold-standard test (method B).(see table S1)
Now, we calculate the Sensitivity and Positive Predictive Value (PPV), Specificity and Negative Predictive Value (NPV) and Accuracy.
When we calculate the Sensitivity and Positive Predictive Value (PPV),we need to collapse Doubtful and Negative into Negative due to be "conservative" in the statistical choices(we calculated them from the data in table S2, 100 people are doubtful need to be considered as negative).
Sensitivity:
(80/100) × 100=80%
Positive Predictive Value:
(80/180) ×100=44.4%
On the other hand, when we calculate the Specificity and Negative Predictive Value (NPV), the Doubtful need to be considered as the Positive (we calculated them from the data in table S3, 100 people are doubtful need to be considered as positive).
Specificity:
(710/900) × 100=78.9%
Negative Predictive Value:
(710/720) × 100=98.6%
Morever, when we calculate the accuracy, we should draw the data from the table S2 and S3 at same time.
Accuracy:
((80+710)/ (80+710+20+190)) × 100 =79%
Am I right? If it has any unreasonable point , please oblige us with your valuable comments .
Thanks a lot!
Dennis
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