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Diagnositic & Clinical Utility Index Calculator
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Quickly find the Qualitative and Quantitative Accuracy & Utility of Diagnostic and Screening Tests
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Instructions: enter your data from diagnostic/screening test results in yellow cells and all others are automatically calculated // help? see www.clinicalutility.co.uk
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Data Entry
Data Table
Reverse LookUp
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Very Poor
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0.36Poor
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Enter Total # Cases:
60CASESNON-CASESIf prevalence is0.150.49Fair
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total by criterion standard
cases0.64Good
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# Cases Correctly Detected:
59>>>>1
TEST POSITIVE
59463>>>PPV= 0.937and sensitivity is0.8860.81
Excellent
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number of true positives
true positives
False negatives
true positivesfalse positivestotal positives
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Enter Total # Non-Cases:
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TEST NEGATIVE
13940>>>NPV= 0.975
and specificity is
0.985
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non-cases (aka controls) by criterion standard
non-casesfalse negativestrue negativestotal negatives0Tiny
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# Non-Cases Correctly Detected:
39>>>>46043103and sample is276113
Very small
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number of true negatives
true negatives
False positives
total casestotal non-casestotal tested...............then287Small
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Cases41.43477
Moderate
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......therefore you had a tested population of
103
Sensitivity= 0.983
Specificity= 0.907
Prevalence =0.583
TP =36.680442888Large
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0.971Non-cases234.6519877
Very large
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TN = 231.1
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Quantitative Results
Qualitative Interpretation
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Lower 95%CI
Upper 95%CI
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Sensitivity =>
98.33%95.09%100.00%
sensitivity (useful if you already know the number of cases)
The SENSITIVITY of the test is
HIGH…..meaning a positive test often occurs in those with the condition
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TP / TP+TN
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Specificity =>
90.70%82.02%99.38%
specificity (useful if you already know the number of non-cases)
The SPECIFICITY of the test is
HIGH…..meaning a negative test often occurs in those without the condition
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TN / TN+FP
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Positive Predictive Value = >
93.65%87.63%99.67%
positive predictive value (useful when you know the number of positive results)
The PPV of the test is
HIGH…..meaning false positives are uncommon in those who screen positive
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TP / TP+FP
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Negative Predictive Value = >
97.50%92.66%100.00%
negative predictive value (useful when you know the number of negative results)
The NPV of the test is
VERY HIGH…..meaning false negatives are rare in those who screen negative, suggesting a potentially useful screening test
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TN / TN+FN
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CUI Positive0.9210.8610.981
case-finding value (ruling-in true positives)
CLINICAL UTILITY of the test for case-finding (confirmation) is
EXCELLENT for case-finding
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SN*PPV
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CUI Negative
0.8840.8220.947
screening value (ruling out true negatives)
CLINICAL UTILITY of the test for screening (ruling out) is
EXCELLENT for screening (ie confirming a non-case)
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SP*NNP
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Prevalence = >
0.583n/an/a
The PREVALENCE of the condition is
BALANCED…..hence close to an ideal prevalence for diagnostic testing
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CASES/POPULATION
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Likelihood Ratio +ve =>
10.5714.1526.90
The total SAMPLE SIZE is
Small
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Sensitivity / 1-specificity
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Likelihood Ratio -ve =>
0.0180.000.129
Notes and cautions
LOW total sample size, be aware of all confidence intervals
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1-specificity / sensitivity
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Test Score (Fraction Correct) % =>
95.1591.0099.30
Value of this single test for *BOTH* screening and case-finding is
EXCELLENT (but depends on prevalence)
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TP+TN/POPULATION
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Added NPV Value
Added PPV Value
Take home message
This test is EXCELLENT for case-finding (ie confirming a case)
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Graphical2.5%55.8%35.4%6.3%
and its best feature is its
sensitivity (useful if you already know the number of cases)
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We would rate this test as
9/10
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Normalized Results (per 100 people)
Live Visual (tab #2 to view)
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CASES
NON-CASES
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TEST POSITIVE
57461
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true positives
false positives
total positives
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TEST NEGATIVE
13839
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false negatives
true negatives
total negatives
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5842100
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total cases
total non-cases
adjusted
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Normalized Results (per 1000 people)
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CASES
NON-CASES
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TEST POSITIVE
57339612
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true positives
false positives
total positives
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TEST NEGATIVE
10378388
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false negatives
true negatives
total negatives
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5834171000
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total cases
total non-cases
adjusted
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Open Graphic
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Everday description
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In a sample of 1000, where 583 are cases, this test would correctly identify 573 of 583 true cases but it would miss 10 cases (ie false negatives).
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Of the 417 non-cases, this test would correctly identify 378 non-cases but it would falsy identify 39 non-cases as false positives.
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If you ran this test 1000 times, 612 tests would be positive, but of these 39 would be false positives, which is 6.3%
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If you ran this test 1000 times, 388 tests would come back negative, but of these 10 would be false negatives, which is 2.5%
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If you ran this test 1000 times, 951 tests would be correct, and 49 would be false (incorrect) which means the fraction correct would be 95.1%
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but take note of the ...LOW total sample size, be aware of all confidence intervals
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and be aware that even an excellent test may require definitive 2nd stage lab test if the implications of the condition are serious
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