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Insights into Imaging

Table 3 Univariate and multivariate regression analysis of the clinical features

From: Exploring a multiparameter MRI–based radiomics approach to predict tumor proliferation status of serous ovarian carcinoma

Characteristics

Univariate regression analysis

Multivariate regression analysis

OR

95% CI

p value

OR

95% CI

p value

Age

 ≤ 55

1

     

 > 55

0.987

0.962–1.044

0.924

N/A

N/A

N/A

FIGO

      

 I – II

1

  

1

  

 III–IV

2.08

1.061–4.395

0.040

1.64

0.68–3.99

0.27

CA-125

 ≤ 1231

1

     

 > 1231

0.497

0.19–1.22

0.137

N/A

N/A

N/A

HE4

 ≤ 418

1

     

 > 418

0.483

0.194–1.116

0.109

N/A

N/A

N/A

NLR

 ≤ 3.73

1

     

 >3.73

0.513

0.968–1.643

0.111

N/A

N/A

N/A

  1. Chi-square test FIGO the International Federation of Gynecology and Obstetrics, CA-125 carbohydrate antigen 125, HE4 human epididymis protein 4, NLR neutrophil-to-lymphocyte ratio, OR odds ratio, 95% CI 95% confidence interval
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