ArticleInternational urology and nephrology2014
Scoring system for prediction of lymph node metastasis in radical cystectomy cohort.
Article in International urology and nephrology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
objectivesThe objective of the study was to assess whether pretreatment clinical parameters combined with computed tomography can improve the prediction of lymph node metastasis in patients with bladder cancer treated with radical cystectomy. PATIENTS AND
methodsIn a single-center retrospective study, demographic and clinicopathological information (initial transurethral resection [grade, stage, multiplicity of tumors, lymphovascular invasion], hydronephrosis, abdominal and pelvic computed tomography) and the presence of lymph node disease on final pathology of 183 patients with bladder cancer undergoing radical cystectomy and pelvic lymph node dissection were reviewed. Logistic regression and bootstrap methods were used to create an integer score for estimating the risk of positive lymph nodes. Various measures for predictive ability and clinical utility were determined.
resultsOn pathological examination, 59.6% of patients had positive lymph nodes. In a multivariable analysis, status lymph nodes on computed tomography and hydronephrosis were the most strongly associated predictors. The resultant total possible score ranged from 0 to 10, with a cut-off value of >4 points. The area under the receiver operating characteristic curve was 0.806. Relative integrated discrimination improvement was 14.3%. In the decision curve analysis, the model provided net benefit throughout the entire range of threshold probabilities. However, the final model was roughly equivalent to using the clinical exam.
conclusionsThe pre-cystectomy scoring system improved the prediction of lymph node status in patients with bladder cancer. Our model represented a user-friendly staging aid, but a large multi-center study should be performed before widespread implementation.
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