Table 1 Results of multivariate logistic regression analysis

From: Development and validation of a machine learning-based nomogram for predicting prognosis in lung cancer patients with malignant pleural effusion

Variable

Coefficient

OR (95% CI)

P

(Intercept)

-1.58

0.21 (0.02–1.65)

0.139

Total volume of pleural effusion

0.14

1.15 (1.01–1.32)

0.037

Appearance of pleural fluid (vs. Yellow)

   

Red

-0.10

0.90 (0.31–2.59)

0.847

Other colors

2.04

7.68 (0.83–193.56)

0.119

Smoking: Yes (vs. No)

0.20

1.22 (0.41–3.61)

0.717

Location of pleural effusion (vs. Left side)

   

Right side

0.25

1.28 (0.42–3.96)

0.662

Both sides

-0.12

0.88 (0.21–3.71)

0.867

High sensitivity C reactive protein in pleural fluid

0.02

1.02 (1.00–1.05)

0.073

Pulmonary disease: Yes (vs. No)

0.03

1.03 (0.32–3.29)

0.958

Pathological subtype of lung cancer (vs. Adenocarcinoma)

   

Squamous cell carcinoma

-0.04

0.96 (0.21–4.93)

0.962

Small cell lung cancer

0.36

1.43 (0.30–7.37)

0.656

Treatment regimen (vs. Untreated)

   

Targeted therapy

-3.46

0.03 (0.01–0.10)

< 0.001

Other treatment

-2.47

0.08 (0.02–0.28)

< 0.001

Presence of pericardial effusion: Yes (vs. No)

1.40

4.04 (1.16–16.21)

0.036

White blood cells

0.13

1.14 (0.96–1.39)

0.155