Table 4.
Example Using a Specificity of 97%
| Model | Model Only | Model + AAb | Total | ||||
|---|---|---|---|---|---|---|---|
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| MAYO | Negative | Positive | Either Negative | Both Positive | |||
| No LC | 163 | 5 | No LC | 163 | 5 | 168 | |
| LC | 35 | 5 | LC | 27 | 13 | 40 | |
| Total | 198 | 10 | Total | 190 | 18 | 208 | |
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| |||||||
| Risk | 60% | 20% | |||||
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| Spec, Sens | 97%, 13% | 97%, 33% | |||||
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| PPV | 50% | 72% | |||||
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| |||||||
| RR | 2.8 (1.4–5.6) | 5.1 (3.2–8.0) | |||||
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| DLRp | 4.2 (1.3–13.8) | 10.9 (4.1–28.9) | |||||
Note: The effect of adding EarlyCDT-Lung at a reduced risk level (60%–20%) is to reclassify eight cancers from false-negative to true positive. This gave high performance statistics: PPV = 72%, RR = 5.1, and DLRp = 10.9.
AAb, autoantibody; LC, lung cancer; Risk, risk threshold; Spec, specificity; Sens, sensitivity; PPV, positive predictive value; RR, relative risk with 95% confidence interval; DLRp, positive diagnostic likelihood ratio with 95% confidence interval.