Development and validation of a clinical prediction model for the risk of lymph node metastasis in bladder cancer
Objective To select the most suitable lymph node dissection for patients by establishing a lymph node metastasis(LNM)nomogram prediction model for bladder cancer to support clinical decision making.Method A total of 7 109 patients diagnosed with bladder cancer by pathology from 2010 to 2015 were searched and screened using the SEER database,and they were randomly di-vided into a training group(n=4 980)and a validation group(n=2 129)in a 7∶3 ratio,and independent risk factors for lymph node metastasis in bladder cancer were screened using between-group difference analysis and multi-factor logistic regression analysis and No-mogram model was produced.The ROC curve,consistency index,and calibration curve were used to verify the discrimination and con-sistency of the nomogram model,and the decision curve analysis was used to assess the predictive efficacy of the nomogram model,and the model was internally validated using Bootstrap resampling 1 000 times.Results Multi-factor logistic analysis showed that bladder cancer tissue type,pathological grade,T and M stages of bladder cancer,age and tumor size were independent risk factors for predic-ting lymph node metastasis in bladder cancer.The nomogram prediction model was constructed based on the above six indicators,and its consistency index was 0.869(95%CI:0.856～0.882)and 0.865(95%CI:0.852～0.878)in the training and validation groups,respectively.The calibration curve and clinical decision curve suggested good model consistency and clinical application efficacy,re-spectively.Conclusion The lymph node metastasis nomogram prediction model for bladder cancer constructed in this study has good prediction accuracy and helps clinicians to make appropriate clinical decisions for bladder cancer patients.
Bladder cancerLymphatic metastasisSEERNomogramPrediction model
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NSTL
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