NODESAFE Nomogram: A Novel Score System to Predict Lymph Node Involvement at the Time of Nephrectomy or Nodal Recurrence in Nonmetastatic Renal Cell Carcinoma

IF 2.3 3区医学 Q3 ONCOLOGY

Clinical genitourinary cancer Pub Date : 2024-10-11 DOI:10.1016/j.clgc.2024.102232

Cesare Saitta , Giuseppe Garofano , Jonathan A. Afari , Hajime Tanaka , Dattatraya Patil , Kit L. Yuen , Luke Wang , Julian Cortes , Margaret F. Meagher , Dhruv Puri , Clara Cerrato , Mimi V. Nguyen , Kevin Hakimi , Masaki Kobayashi , Shohei Fukuda , Marco Paciotti , Massimo Lazzeri , Giovanni Lughezzani , Nicolò M. Buffi , Yasuhisa Fujii , Ithaar H. Derweesh

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引用次数: 0

Abstract

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.

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NODESAFE Nomogram：预测非转移性肾细胞癌肾切除术时淋巴结受累或结节复发的新评分系统

目的我们试图开发一种名为NODESAFE（NODE SAFEty）的术前提名图，用于预测局部肾细胞癌（RCC）手术或后续随访时的结节受累（NI）情况，因为淋巴结切除术在局部RCC中的作用仍存在争议。方法我们对接受初次手术切除的RCC患者进行了一项多中心回顾性分析。我们对接受初次手术切除的 RCC 患者进行了多中心回顾性分析。NI的定义是手术时存在组织学意义上的RCC并进行了淋巴结切除术，或随后出现组织学意义上的NI。数据集被分为训练子集（70%）和测试子集，以便于通过逐步式多变量逻辑回归（MLR）模型进行模型评估。结果共有 3308 例患者（2221 例[67.1%]男性）符合纳入标准。随访期间，25 名患者（0.76%）出现结节复发，22/25 在术前被归类为 cN0。在我们的队列中，112 例（3.4%）患者术前有临床淋巴结病（cN1），34/112 例为 pN1。以下协变量在 MLR 模型中具有统计学意义：高血压（Odds ratio [OR] 3.35，< .001）、Charlson 综合征指数≥ 5（OR 1.93 P = .025）、肿瘤大小≥ 6 cm（OR 2.63，P = .001）、CT 扫描时肿瘤坏死（OR 1.83，P = .036）、cN1（OR 5.59，P <.001）和 CRP ≥ 8.5 mg/L（1.96，P = .018）。在验证集测试模型的预测性能时，模型的 AUC 为 0.89。NODESAFE 的灵敏度为 83.9%，特异性为 86.1%，以 4% 的阈值概率计算，阴性预测值为 99.1%。NODESAFE 可以完善临床决策，包括手术时的淋巴腺切除、术后监测以及辅助治疗的考虑。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Clinical genitourinary cancer 医学-泌尿学与肾脏学

CiteScore

5.20

自引率

6.20%

发文量

201

审稿时长

54 days

期刊介绍： Clinical Genitourinary Cancer is a peer-reviewed journal that publishes original articles describing various aspects of clinical and translational research in genitourinary cancers. Clinical Genitourinary Cancer is devoted to articles on detection, diagnosis, prevention, and treatment of genitourinary cancers. The main emphasis is on recent scientific developments in all areas related to genitourinary malignancies. Specific areas of interest include clinical research and mechanistic approaches; drug sensitivity and resistance; gene and antisense therapy; pathology, markers, and prognostic indicators; chemoprevention strategies; multimodality therapy; and integration of various approaches.