negative predictive value


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Related to negative predictive value: specificity, Negative Likelihood Ratio

negative predictive value

A numerical value for the proportion of individuals with a negative test result who are free of the target condition—i.e., the probability that a person who is a test negative is a true negative.

neg·a·tive pre·dic·tive val·ue

(neg'a-tiv prē-dik'tiv val'yū)
The probability of a negative test result indicates the absence of an analyte or a specific disease.

negative predictive value

The proportion of people whose test results are true negatives and who are truly disease free.

predictive value

a measure used by clinicians to interpret diagnostic test results. See also sensitivity, specificity.

positive predictive value
the probability that a patient with a positive test result really does have the condition for which the test was conducted.
negative predictive value
the probability that a patient with a negative test result really is free of the condition for which the test was conducted.
References in periodicals archive ?
Major finding: A composite prognostic index score of 18 yielded a negative predictive value of 90.
In this study we assessed agreement rates, test sensitivity, test specificity, positive predictive value, and negative predictive value.
This retrospective analysis is limited by its small size, but in this study's cohort it suggests that the cut-off value of [greater than or equal to] 6 is not sensitive enough, nor has robust enough likelihood ratios or negative predictive value to be used alone to guide a treatment strategy.
The sensitivity, specificity, and the positive and negative predictive values for GM and BDG were identical: 87.
The sensitivity, specificity, negative predictive value, and positive predictive value for each of the seven sinuses and the overall reading of the miniseries CT scan are reported in Table 1.
Test Result Yes No Positive True positive False positive (TP) (FP) Negative False negative True negative (FN) (TN) Characteristics of Screening Tests Sensitivity* = TP / TP + FN Specificity* = TN / FP + TN Overall accuracy = (TP + TN) / (TP + FP + FN + TN) Positive predictive value = TP / TP + FP Negative predictive value = TN / TN + FN Positive likelihood ratio = sensitivity / (1-specificity) Negative likelihood ratio = (1-sensitivity) / specificity Figure 1 Definitions of terms used to describe characteristics of screening tests.
Figure 1 shows that four quantitative characteristics [sensitivity (Se), specificity (Sp), positive predictive value (PPV), and negative predictive value (NPV)] are defined by two properties of the screening method (the false-positive rate, or, and the false-negative rate, [3) and by a property of the danger being assessed, the frequency of true hazards, P[H], where H is a true hazard.
Endpoints include the sensitivity, specificity, negative predictive value and positive predictive value of BronchoGen for identifying patients with malignancy.
1], results in a Negative Predictive Value (NPV) of 94% and Positive Predictive Value (PPV) of 74%, at a cancer prevalence of 32%.
Major Finding: The optimal levodopa equivalent daily dose cut off at baseline for predicting a poor impulse control disorder outcome was 161 mg or greater, resulting in a 46% sensitivity, 90% specificity, 93% positive predictive value, and 37% negative predictive value.
AUC, sensitivity, specificity, positive predictive value (ppv) and negative predictive value (npv) were reported.