Table 3.
Test performance of different probability to identify COVID-19 for the Overall Cohort Model and Unknown Contact History Model in the nomogram. Probability of 0.1, 0.2, 0.4 and 0.6 are stated and optimum probability cut-off for the two models. As an example of this table being utilised, if we use the overall cohort model and set 0.4 as the chosen probability cut-off to determine RT-PCR testing, patients scoring ≥0.4 on the nomogram would be tested and those <0.4 would not be tested. With this cut-off, the model indicates that on the validation cohort the following results: sensitivity 66.7%, specificity 90.9%, positive predictive value 63.6% and negative predictive value 92.0%.
| Probability | Sensitivity (95% CI) | Specificity (95% CI) | Positive predictive value (95% CI) | Negative predictive value (95% CI) |
|---|---|---|---|---|
| Overall Cohort Model | ||||
| Derivation cohort | ||||
| 0.1 | 97.6 (94.6,99.2) | 68.3 (64.6,71.8) | 48.9 (44.1,53.8) | 98.9 (97.5,99.7) |
| 0.18† | 91.5 (86.9,94.9) | 78.0 (74.7,81.0) | 56.4 (51.0,61.7) | 96.7 (94.9,98.0) |
| 0.2 | 90.1 (85.3,93.8) | 79.9 (76.7,82.8) | 58.2 (52.7,63.6) | 96.3 (94.4,97.7) |
| 0.4 | 73.1 (66.6,79.0) | 89.3 (86.7,91.5) | 68.0 (61.5,74.0) | 91.4 (89.0,93.4) |
| 0.6 | 56.1 (49.2,62.9) | 95.3 (93.4,96.8) | 78.8 (71.4,85.0) | 87.5 (84.9,89.8) |
| Validation cohort | ||||
| 0.1 | 91.7 (83.6,96.6) | 69.4 (64.3,74.2) | 41.6 (34.4,49.1) | 97.2 (94.4,98.9) |
| 0.18† | 88.1 (79.2,94.1) | 77.9 (73.2,82.1) | 48.7 (40.5,56.9) | 96.5 (93.6,98.3) |
| 0.2 | 86.9 (77.8,93.3) | 79.9 (75.3,83.9) | 50.7 (42.2,59.1) | 96.2 (93.4,98.1) |
| 0.4 | 66.7 (55.5,76.6) | 90.9 (87.4,93.7) | 63.6 (52.7,73.6) | 92.0 (88.6,94.6) |
| 0.6 | 47.6 (36.6,58.8) | 95.5 (92.7,97.4) | 71.4 (57.8,82.7) | 88.5 (84.8,91.5) |
| Unknown Contact History Model | ||||
| Derivation cohort | ||||
| 0.1 | 97.2 (93.9,99.0) | 63.4 (59.7,67.1) | 45.3 (40.6,50.0) | 98.6 (97.0,99.5) |
| 0.18† | 92.9 (88.6,96.0) | 74.0 (70.5,77.3) | 52.7 (47.5,57.8) | 97.1 (95.3,98.4) |
| 0.2 | 91.0 (86.4,94.5) | 75.9 (72.5,79.1) | 54.1 (48.7,59.3) | 96.5 (94.5,97.9) |
| 0.4 | 72.6 (66.1,78.5) | 87.2 (84.5,89.6) | 63.9 (57.5,70.0) | 91.1 (88.7,93.2) |
| 0.6 | 48.6 (41.7,55.5) | 94.9 (92.9,96.4) | 74.6 (66.5,81.7) | 85.6 (82.9,88.0) |
| Validation cohort | ||||
| 0.1 | 90.5 (82.1,95.8) | 65.2 (59.9,70.1) | 38.2 (31.4,45.3) | 96.6 (93.5,98.5) |
| 0.18† | 84.5 (75.0,91.5) | 73.4 (68.4,77.9) | 43.0 (35.4,51.0) | 95.2 (92.0,97.4) |
| 0.2 | 82.1 (72.3,89.6) | 74.5 (69.6,79.0) | 43.4 (35.6,51.5) | 94.6 (91.3,96.9) |
| 0.4 | 66.7 (55.5,76.6) | 88.4 (84.6,91.5) | 57.7 (47.3,67.7) | 91.8 (88.3,94.5) |
| 0.6 | 41.7 (31.0,52.9) | 96.6 (94.1,98.2) | 74.5 (59.7,86.1) | 87.4 (83.7,90.6) |
Sensitivity, specificity, positive predictive value and negative predictive value are stated in percentage with 95% confidence intervals in brackets.
This probability is the optimal cut-off determined by using the Youden method from the derivation cohort.