Table 2.
The details of each predictive model
| Number of factors | Items of predictive factors | |
|---|---|---|
| Chen [11] | 7 | Age, density, lesion-lung border, lobulation, concentrated vessel, pleural retraction, PET |
| Cheng [12] | 6 | Age, vacuole, lobulation, calcification, diameter, PET |
| Guo [13] | 7 | Age, diameter, smoking history, spiculation, lobulation, cavity, PET |
| Honguero Martínez [14] | 4 | Age, sex, malignant history, PET |
| Lin [15] | 5 | Age, lobulation, concentrated vessel, pleural retraction, PET |
| Liu [16] | 3 | Age, spiculation, PET |
| Ma [17] | 4 | Age, concentrated vessel, calcification, PET |
| Pei [18] | 7 | Age, sex, size, spiculation, PET, border, concentrated vessel |
| Tian [19] | 6 | Age, smoking, gender, diameter, PET, spiculation |
| van Gómez López [20] | 2 | Age, PET |
| Wang [21] | 5 | Age, lobulation, concentrated vessel, pleural retraction, PET |
| Xiang [22] | 5 | Age, PET, lobulation, calcification, spiculation |
| Zhang [23] | 3 | Calcification, concentrated vessel, PET |
PET: positron emission tomography