Abstract
OBJECTIVE: To provide a preoperative predictive model to support clinical decision-making regarding the selection of in renal cell carcinoma (RCC) patients who will benefit the most from lymph node dissection. METHODS: This retrospective analysis enrolled 374 RCC patients without distant metastasis who underwent surgical treatment from January 2006 to December 2017. The relationships between lymph node invasion (LNI) and age at surgery; gender; body mass index(BMI); the presence of clinical symptoms such as flank pain, hematuria or a palpable mass; clinical T stage (cT stage); clinical N stage (cN stage); and the results of routine hematological and serum biochemical analyses were investigated. All the variables were included in univariate and multivariate logistic regression analyses, and the significant variables were then included in a novel nomogram to predict the probability of LNI. Then, we calibrated the nomogram with an internal validation set. RESULTS: Six of eighteen variables were significant in the univariate logistic regression analysis. After multivariate logistic regression analysis, age at surgery (OR=0.643, 95% CI: 0.421-0.975), cT stage (OR=3.034, 95% CI: 1.541-5.926), cN stage (OR=6.353, 95% CI: 3.273-12.456), lymphocyte percentage (OR=0.481, 95% CI: 0.256-0.894), and the presence of clinical symptoms (OR=2.045, 95% CI: 1.065-3.924) were independent predictors of LNI and were included in the nomogram. The C-index of this nomogram was 0.824. CONCLUSION: Preoperative basic laboratory findings combined with the results of a physical examination and radiological examination can indicate the probability of LNI in RCC patients.