Journal of Oncology / 2022 / Article / Tab 2 / Research Article
Dynamic Predictive Models with Visualized Machine Learning for Assessing the Risk of Lung Metastasis in Kidney Cancer Patients Table 2 Univariate and multivariate logistic regression for patients with lung metastasis of renal cancer. It is reproduced from that article in the below format Table
2 is reproduced from Li et al. 2022 (under the Creative Commons (attribution license/public domain).
Characteristics Univariate logistics Multivariable logistics OR CI OR CI Bone metastasis No Ref Ref Ref Ref Ref Ref Yes 18.9 17.12–20.86 <0.001 4.83 4.27–5.46 <0.001 Brain metastasis No Ref Ref Ref Ref Ref Ref Yes 31.29 25.98–37.69 <0.001 8.41 6.72–10.51 <0.001 Unknown 68.11 33.17–139.85 <0.001 6.13 2.35–15.98 <0.001 Grade Well differentiated Ref Ref Ref Ref Ref Ref Moderately differentiated 1.98 1.34–2.94 0.001 1.41 0.94–2.11 0.102 Poorly differentiated 7.83 5.34–11.47 <0.001 2.71 1.82–4.04 <0.001 Undifferentiated; anaplastic 21.49 14.64–31.55 <0.001 4.58 3.05–6.87 <0.001 Unknown 21.14 14.53–30.77 <0.001 6.34 4.29–9.37 <0.001 Liver metastasis No Ref Ref Ref Ref Ref Ref Yes 25.38 22.26–28.93 <0.001 4.23 3.6–4.96 <0.001 Unknown 51.12 29.63–88.2 <0.001 6.36 3.06–13.21 <0.001 N N 0Ref Ref Ref Ref Ref Ref N 116.41 14.94–18.02 <0.001 3.79 3.37–4.25 <0.001 N 25.03 3.52–7.19 <0.001 3.54 2.21–5.69 <0.001 N X5.97 5.26–6.78 <0.001 2.33 1.96–2.77 <0.001 Primary site C64.9-Kidney Ref Ref Ref Ref Ref Ref C65.9-Renal pelvis 0.81 0.68–0.98 0.027 0.38 0.3–0.49 <0.001 Sequence number One primary only Ref Ref Ref Ref Ref Ref More 0.46 0.42–0.5 <0.001 0.62 0.56–0.69 <0.001 T T 1Ref Ref Ref Ref Ref Ref T 28.21 7.26–9.27 <0.001 3.42 2.93–4 <0.001 T 38.96 8.07–9.94 <0.001 4.44 3.89–5.07 <0.001 T 428.5 24.58–33.04 <0.001 5.39 4.42–6.57 <0.001 T X32.71 27.97–38.25 <0.001 5.67 4.63–6.94 <0.001 Tumor size 1.02 1.02–1.02 <0.001 1.01 1–1.01 <0.001
