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Table 2 Independent analysis of training set patients

From: Leveraging a disulfidptosis-related signature to predict the prognosis and immunotherapy effectiveness of cutaneous melanoma based on machine learning

Characteristics

Univariate

Multivariate

HR

95%CI

P

HR

95%CI

P

Age

1.019

1.009–1.030

< 0.001

1.011

1.000–1.022

0.047

T stage

1.479

1.278–1.711

< 0.001

1.457

1.232–1.722

< 0.001

N stage

1.440

1.239–1.674

< 0.001

1.590

1.261–2.004

< 0.001

Risk score

2.807

1.958–4.023

< 0.001

2.389

1.679–3.400

< 0.001

  1. HR: hazard ratio; CI: confidence interval
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Molecular Medicine

ISSN: 1528-3658