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Updated: Jul 12, 2026
Quantification of Tumor Cell Adhesion in Lymph Node Cryosections
Published on: February 9, 2020
NODESAFE Nomogram: A Novel Score System to Predict Lymph Node Involvement at the Time of Nephrectomy or Nodal
Cesare Saitta1, Giuseppe Garofano1, Jonathan A Afari2
1Department of Urology, UC San Diego Health System, San Diego, CA; Department of Urology, IRCCS Humanitas Clinical and Research Hospital, Rozzano, Italy; Department of Biomedical Sciences, Humanitas University, Pieve Emanuele, Italy.
Objective:
We sought to develop a preoperative nomogram called NODESAFE (NODE SAFEty) to predict nodal involvement (NI) at time of surgery or subsequent follow up in localized renal cell carcinoma (RCC), as the role of lymphadenectomy in localized RCC remains controversial.
Methods:
We conducted a multicenter retrospective analysis of RCC patients who underwent primary surgical resection. Patients with clinical metastasis at presentation were excluded. NI was defined as presence of histological RCC with lymphadenectomy at time of surgery, or subsequent development histologically proven NI. The dataset was divided into training (70%) and testing subsets to facilitate model evaluation which was constructed through a stepwise multivariable logistic regression (MLR) model. Accuracy was tested with receiver operator characteristic estimated area under the curve (AUC).
Results:
Total 3308 patients (2221 [67.1%] male) met inclusion criteria. During follow-up 25 patients (0.76 %) experienced nodal recurrence, and 22/25 were preoperatively classified as cN0. In our cohort, 112 (3.4%) patients had clinical lymphadenopathy preoperatively (cN1), and 34/112 were pN1. The following covariates were found to be statically significant on a MLR model: hypertension (Odds ratio [OR] 3.35, < .001), Charlson Comorbidity Index ≥ 5 (OR 1.93 P = .025), tumor size ≥ 6 cm (OR 2.63, P = .001), tumor necrosis at CT scan (OR 1.83, P = .036), cN1 (OR 5.59, P < .001) and CRP ≥ 8.5 mg/L (1.96, P = .018). Testing the prediction performance of the model in the validation set AUC of the model was 0.89. NODESAFE demonstrated a sensitivity of 83.9%, specificity of 86.1% and 99.1% negative predictive values using a 4% threshold probability.
Conclusion:
Combining clinical features, serum biomarkers and radiographic findings, we developed a model capable of predicting NI with high degree of accuracy. NODESAFE may refine clinical decision making with respect to the performance of lymphadenectomy at the time of surgery, postsurgical surveillance, and spur consideration for adjuvant therapy.
