Indicators of Prognostic Accuracy

Early recognition inventories should allow a correct identification of ''at-risk mental states''. This objective is attained when as large a proportion of at-risk persons as possible is classified as such (i.e. the test for diagnostic ascertainment is highly sensitive) and at the same time as large a proportion of risk-free persons as possible is identified as not being at risk (specificity). But there is no single symptom or single risk factor of sufficient diagnostic efficiency that early recognition could be based on. Usually a selection of several prodromal symptoms is used as a basis for a total score that indicates psychosis risk. Besides symptom scales, other risk factors can be taken into account, e.g. biological indicators such as smooth pursuit eye movement or MRI parameters, in order to create the best possible criteria. A technique for generating combinations of indicators is the Receiver Operating Characteristic Analysis (ROC Analysis), which helps to find out an optimum cut-off based on a combination of single items [112]. Further indicators of the predictive power of early recognition inventories are the positive and the negative predictive power (PPP and NPP). These measures are suited to assessing individual psychosis risk in actual test situations when the persons examined present or do not present a particular symptom (more generally: receive a positive or a negative test result, which usually represents a cut-off based on a selection of several features).

Contemporary early recognition instruments of high sensitivity for identifying large proportions of at-risk persons in the general population all have insufficient specificities. But even if sensitivity and specificity were satisfactory (e.g. 0.95), the number of false positive cases would be rather high, because of the low base rate of schizophrenia in the general population. Let us presume that 1% of the population at large is at risk for schizophrenia. By screening 1000 individuals only 10 at-risk persons would be identified. The problem is the high number of 50 false positives among the 990 persons not being at risk.

BiPolar Explained

BiPolar Explained

Bipolar is a condition that wreaks havoc on those that it affects. If you suffer from Bipolar, chances are that your family suffers right with you. No matter if you are that family member trying to learn to cope or you are the person that has been diagnosed, there is hope out there.

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