A Nomogram Predicting the Progression-Free Survival of Nonmetastatic Renal Cell Carcinoma Patients With Venous Thrombus After Surgery.

Autor: Zhang, Yu, Tian, XiaoJun, Bi, Hai, Yan, Ye, Liu, Zhuo, Liu, Cheng, Zhang, ShuDong, Ma, LuLin
Předmět:
Zdroj: Frontiers in Oncology; 3/24/2022, Vol. 12, p1-8, 8p
Abstrakt: Objectives: To demonstrate the progression-free survival (PFS) of nonmetastatic renal cell carcinoma (RCC) patients with venous thrombus after radical nephrectomy and venous thrombectomy (RN-VT) and to develop and validate a nomogram to predict the PFS of patients after RN-VT. Materials and Methods: We reported our prospective follow-up data of RCC patients with venous thrombus from January 2014 to September 2020 (n = 199). We used the Kaplan–Meier method to assess the PFS. The Cox proportional hazards regression model was used to determine the predictors. Nomograms predicting the PFS was established, and external validation was performed. Calibration curves and decision curves were generated to assess the predictive efficacy and clinical benefit. Results: After a median follow-up of 32 months, 79 patients (39.7%) had disease progression and the median PFS was 41.0 months (95% CI 34.8–53.2 months). The 1-year, 3-year, and 5-year PFS rates were 78.4%, 45.4%, and 30.0%, respectively. Multivariate analysis showed that Fuhrman grade [grade 4: hazard ratio (HR) 1.92, 95% CI 1.10–3.34, P = 0.02], pathological type (papillary RCC: HR 3.02, 95% CI 1.79–5.10, P < 0.001), perinephric fat invasion (HR 1.54, 95% CI 1.12–2.10, P = 0.007), sarcomatoid differentiation (HR 2.97, 95% CI 1.24–7.13, P = 0.02) were associated with a worse PFS, and adjuvant therapy (HR 0.32, 95% CI 0.18–0.59, P < 0.001) could lead to a better PFS. A nomogram based on the predictors was externally validated to have good discrimination and calibration, and it could improve PFS prediction to obtain a clinical benefit. Conclusions: We constructed and validated a nomogram to predict the 1-year, 3-year, and 5-year PFS of M0 RCC patients with venous thrombus after surgery. The model can help identify patients who can benefit the most from surgery and develop the criteria for clinical trial enrollment. [ABSTRACT FROM AUTHOR]
Databáze: Complementary Index