The commonly used statistical indicators for evaluating tumor markers are:
(1) Sensitivity = true positive/number of all tumor patients? 1%； Sensitivity is one of the main indicators to describe the diagnostic value of markers, which reflects the ability of the test to detect diseases. The higher the sensitivity, the greater the possibility of detecting diseases, and 1% sensitivity means that all patients can be detected.
(2) specificity = true negative/number of all non-tumor patients? 1%； Specificity is one of the main indicators to describe the diagnostic value of markers, which reflects the ability to identify diseases. The higher the specificity, the less likely it is to be misdiagnosed. 1% specificity means that all normal people are negative and only patients are positive.
(3) Positive predictive value = true positive/(true positive+false positive)? 1%； Positive predictive value refers to the chance of getting sick if a certain marker is positive. Positive predictive value is one of the indicators used to judge the prevalence rate of the population.
(4) negative predictive value = true negative/(true negative+false negative)? 1%； Negative predictive value refers to how likely it is not to get cancer if a certain marker is negative. Negative predictive value is one of the indicators used to judge the prevalence of population.
(5) Accuracy (effective rate) = (true positive+true negative)/total cases%; Accuracy is an index to comprehensively judge tumor markers. Generally speaking, the higher the specificity and sensitivity, the higher the accuracy and the higher the application value of the markers.