A novel nomogram can predict pathological T3a upstaged from clinical T1a in localized renal cell carcinoma

• Autor(a) principal: Cao,Chuanzhen
• Data de Publicação: 2022
• Outros Autores: Kang,Xiangpeng, Shang,Bingqing, Shou,Jianzhong, Shi,Hongzhe, Jiang,Weixing, Xie,Ruiyang, Zhang,Jin, Zhang,Lianyu, Zheng,Shan, Bi,Xingang, Li,Changling, Ma,Jianhui
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: International Braz J Urol (Online)
• Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1677-55382022000500784
• topic: Carcinoma; Renal Cell; Prognosis; Nomograms

ABSTRACT Hypothesis: Nomogram can be built to predict the pathological T3a upstaging from clinical T1a in patients with localized renal cell carcinoma before surgery. Purpose: Renal cell carcinoma (RCC) patients with clinical T1a (cT1a) disease who are upstaged to pathological T3a (pT3a) have reduced survivals after partial nephrectomy. We aimed to develop a nomogram-based model predicting pT3a upstaging in RCC patients with preoperative cT1a based on multiple preoperative blood indexes and oncological characteristics. Materials and Methods: Between 2010 and 2019, 510 patients with cT1a RCC were individually matched according to pT3a upstaging and pathological T1a (pT1a) at a 1:4 ratio using clinicopathologic features. Least absolute shrinkage and selection operator regression analysis was used to identify the most important risk factor from 40 peripheral blood indicators, and a predictive model was established. Multivariate logistic regression analysis was performed with the screened blood parameters and clinical data to identify significant variables. Harrell’s concordance index (C-index) was applied to evaluate the accuracy of the model for predicting pT3a upstaging in patients with cT1a RCC. Results: Out of 40 blood indexes, the top ranked predictor was fibrinogen (FIB). Age, the ratio of the tumor maximum and minimum diameter (ROD), FIB, and tumor size were all independent risk factors for pT3a upstaging in multivariate analysis. A predictive ARFS model (Age, ROD, FIB, tumor Size) was established, and the C-index was 0.756 (95% CI, 0.681-0.831) and 0.712 (95% CI, 0.638-0.785) in the training and validation cohorts, respectively. Conclusions: Older age, higher ROD, increased FIB level, and larger tumor size were independent risk factors for upstaging. The ARFS model has a high prediction efficiency for pT3a upstaging in patients with cT1a RCC.